Steve Hargadon

Library Staff Current Perspectives on AI - Quick Survey on Use and Concerns

2026-06-08T16:39:22.340-04:00

Things keep changing rapidly in the AI world, and we have now reached 60,000 members at Library 2.0! This is another of our regular surveys on how librarians, library staff, and library leaders are using, learning about, and feeling about AI.

As always, your responses are anonymous, and the survey results will be published shortly at Library 2.0 so you can see what your colleagues in the library world are experiencing.

Thank you!

https://forms.gle/yj74z3euEmwgAMas9

Truth and AI: Why Large Language Models Shouldn't Claim to Tell the Truth

2026-06-02T15:16:48.965-04:00

I keep running into the same thing in online posts, and it bothers me each time. Someone is making an argument, and to settle it, they paste in what an AI told them, as if the machine's having said it puts the matter to rest. The content is sometimes even good. But the problem for me is the assumption that the AI can objectively see something true, and so is authoritative.

That assumption is wrong, and I think it's becoming one of the more consequential misunderstandings of our moment.

Two things are combining to produce it. The first is a lack of candor from the companies that build these systems about what their products are. These are language engines, not truth engines. The second is the way the systems themselves talk: fluent, confident, and human enough that "it said so" starts to feel like "it is so." Put those together at scale, and you get a public learning to treat a statistical text generator as an oracle.

So let me say plainly what I think these tools are, and are not. A large language model can simulate reasoning, surface arguments, and synthesize enormous amounts of material. What it cannot do, what it is not built to do, is to discern truth. And a model that presents itself as if it can is, in a strict sense, misinforming you about itself.

How Humans Get Closer to Truth

Start with us, because the contrast between human and synthetic reasoning is what we're getting at here.

Human beings are truth-seeking under constraints. We don't trust any single person to simply know what happened, so we built institutions that make competing accounts collide under fair rules: trial by jury, peer review, and the randomized controlled trial. These are constraints on process, on how a claim must be tested, not constraints on hypothesis. They are designed to make the collisions more informative. They are not designed to decide in advance which questions may be asked.

The test of whether you believe in open inquiry is not whether you'll allow questions you're neutral about. The test is whether you'll allow the questions whose likely answers you find wrong, distasteful, or even dangerous. A process that protects only the comfortable questions doesn't protect inquiry at all; it's just enforcing existing beliefs with extra steps.

There are two reasons the disagreeable question must remain open. The first is humility about our own record: nearly everything we now hold as obvious was once a minority view, which means today's consensus is partly mistaken, and we do not yet know which part. Close off the questions that offend the consensus, and you simply lock in the errors you can't see. The second is about what the impulse to forbid a question really is. It is the tribal reflex, a move that protects the group, not the finding. Banning a line of inquiry feels like defending truth, but it's usually just defending our group-supporting beliefs.

The protection is for the asking and the testing, not for the concluding. You defend someone's right to investigate even a fringe claim, and then you subject that claim to exactly the scrutiny everything else gets, and you let it be shown wrong if it's wrong. Open inquiry and rigorous contestation are not opposites. They're part of the same commitment.

None of this is a modern invention. The idea that truth emerges from a fair contest of ideas runs back to the Greeks. Socrates tested a claim by cross-examining it until its contradictions surfaced, that is, truth pursued through structured dispute, not pronouncement. The Sophists, and later the skeptics of the Academy, formalized the practice of arguing both sides of a question, what the Romans called arguing in utramque partem. Aristotle built the first formal logic and compiled the first catalog of fallacies. Reasoning, logic, and the fallacies are about making a contest of ideas productive rather than merely loud, with the named fallacies serving as the agreed-upon fouls that keep the clash honest without anyone deciding in advance who wins.

Milton argued that truth wins a free and open encounter and needs no protection from falsehood. Mill said that a silenced opinion might be true, or partly true, but even a wholly true belief, if it is never contested, decays into dead dogma, held by rote with its grounds forgotten. Contestation isn't only how we catch errors; it's what keeps a true belief alive and understood. Popper turned the same instinct into the engine of science: knowledge advances by trying to refute claims, not to confirm them. What unites all of them is the same thing this essay is about: constrain the process, not the hypothesis, and refuse to pre-decide the winner.

What a Language Model Is Doing Instead

A large language model is trained to do one thing: predict the next piece of text, over and over, across an enormous body of writing. Truth is not one of its objectives. It enters only sideways, that is, to the degree that true statements also happen to be common, stable, and consistent in the training data.

That sideways relationship matters enormously, because it means the model's grip on truth is strongest exactly where it's least needed and weakest exactly where we need it most. For settled questions, where the correct answer is also the most frequent, the model is reliable. On contested questions, where one side is louder, better funded, or more relentlessly repeated, frequency exerts a gravitational pull that has nothing to do with which side is right.

I want to be fair about this, because the easy version of the critique overstates it. These models are not pure parrots; they clearly build internal representations that generalize beyond anything they were shown, and they handle numbers and sentences they've never encountered. They can construct the strongest case for a position no one around you holds. But "can generate an argument" is not "can tell whether the argument is true," and the gap between those two is the entire subject of this essay. What looks like knowledge inside one of these systems is compressed pattern. It is closer to an extraordinarily sophisticated autocomplete than to a scientist.

The Thing a Model Can't Do: Catch a Liar

Here is the capacity I find most clarifying, because it exposes the deepest mismatch between how we reason and how these systems do.

When a human source is caught lying — when a company buries a trial result, when an official misrepresents what they knew — we don't just file away that one lie. We re-weight the source globally. We discount what they say about the next drug, the adjacent topic, the whole category. That single act of moral and epistemic distrust is central to how people navigate a world full of motivated actors.

A language model has no native version of this. It does not keep a ledger of who has been honest. It aggregates by frequency, which means a prolific liar doesn't get discounted — he gets amplified. Feed the training distribution enough polished, repeated, well-produced messaging, and that messaging becomes a more probable output, not less, no matter how false it is. There is early research on detecting deception inside models, but it's fragile and far from how these systems work.

It's worth seeing that this is a mirror of something in us. Psychologists call it the illusory truth effect: repetition alone increases how true a statement feels, regardless of whether it is true. The model's frequency-weighting is that human failing mechanized. The difference is that a person also carries the corrective the model lacks: notice the bad faith, then re-weight the source. We have the disease and a partial cure. The model, built from us, inherited only the disease.

Follow that to its conclusion and you arrive at something unsettling: a frequency-weighted system is most distorted precisely where a narrative is best funded, most polished, and most often repeated. The stories a society defends most heavily are the very ones such a system is least able to see past. That is close to the opposite of what we'd want from anything we're tempted to call a truth machine. And it forces a correction on the whole way we talk about these tools. Because they are assembled out of human reasoning, they do not stand outside our biases and check them; they distill and concentrate them. The common hope, that an AI will be more objective than we are, has the mechanism backward.

Two Ways These Systems Misrepresent Themselves

The first is the voice. Models speak as "I" and "we." "I think," "we should," "as we understand it." Taken as a stylistic choice, it misattributes authorship: there is no "we," only a statistical model, a company, and a product. But it goes further than a misnamed author. The "we" is a claim of membership. "We" places the machine inside the human circle, on our side, sharing our stakes and our project. And membership is exactly what earns insider trust; we extend a different kind of credence to one of us than to a tool. So the word smuggles in a belonging the system does not have: no skin in the game, no exposure to the consequences, no place in the "we" of people who will have to live with being wrong. It doesn't merely describe, it affiliates. Set the readable, confident fluency on top of that (and these systems speak more clearly and confidently than most people we know), and the impression of a trustworthy fellow human is nearly complete. The fix is not to strip the voice; a maximally hedged model is one no one would use. It's to break the link between sounding like one of us and being owed the trust we would naturally extend to each other.

The second is the posture toward fact. Models tend to state things in a flat, declarative, expert tone, with no signal of uncertainty, no indication that a claim is contested, no marker of where the evidence thins out. Legal scholars have begun asking whether the companies behind these systems have a duty to avoid what's been called "careless speech," i.e., plausible, confident output that quietly degrades public knowledge because it's wrong often enough to matter and smooth enough to be believed. I'd put it more bluntly: it is itself a form of misinformation for a large language model to present itself as something that can discern what is true.

The Irony at The Center of All This

There's a conclusion here I can't get past. The same systems increasingly positioned as guardians against "misinformation" are built atop an unresolved inability to track truth, and the definitions of misinformation they enforce are frequently inherited from institutions with long, documented histories of distortion and capture. This means we have handed the job of deciding which questions are too dangerous to ask to some of the actors with the worst records of being wrong, and then wired those decisions into machines that deliver them in the calm, even voice of objectivity.

In the terms I laid out earlier, the failure is specific. The problem is not that these systems reflect a consensus. The problem is that the guardrails tend to shrink the hypothesis space — to forbid the disagreeable question — rather than improve the quality of the contest. This is tribal reflex, or even propaganda, dressed up as safety.

Let me give the other side its due. The guardrails are not purely about institutional capture. A model that confidently emits a convincing falsehood does it at a scale and consistency no lone crank can match, and that asymmetry is a real reason for caution. It isn't a small point. But the answer to it is not to ban the question. The answer is to apply the same approach we use in human inquiry: constraints on process, not on the hypothesis space. Make the uncertainty visible. Show the contest. Cite the sources. Let the weak claim be made and then defeated in the open. Caution belongs in how a claim is handled, not in a list of claims that may not be examined.

Beneath much of this is something more mundane than either capture or caution, and it closes the loop with where we began. When people quote the machine as authority, its sentences get treated as the AI company's own claims about the world, and a company answerable for every sentence will fence off whole topics defensively. A large share of what presents itself as principled defense against misinformation is, at bottom, liability management. The misrepresentation manufactures the very liability that drives the censorship. Which means that the pretense of truth-telling and the over-guarding are not separate failures. They are two sides of the same coin.

What These Tools Are Good For

I don't want any of this to be read as a refusal of the value of LLMs. I use these systems constantly, and they are remarkable. The point is to use them as what they are.

They are argument engines: ask for the strongest case for and against a claim, not for a verdict. They are synthesis tools: have them summarize the literature, map the positions, surface the open questions — then check the sources yourself. And they are instruments of pluralism: query several models, from different companies with different training and different incentives, and treat the places where they diverge as data about the information ecosystem rather than noise. Where two systems disagree, you've usually found a seam worth examining.

A more honest design by AI companies would help, although my Law of Inevitable Exploitation would argue that they are unlikely to do anything that would reduce usage or commercial advantage. But these would make LLMs much better: drop the implied authority, even while keeping the readable voice, and make uncertainty and provenance visible by default — this is the consensus, here is the minority view, here is where the evidence is thin. And it's worth being candid that this is hard: models are often miscalibrated, their confidence poorly matched to their accuracy, so "just signal uncertainty" is easier to demand than to deliver. That difficulty is a reason for humility from the people building these tools — not a license to keep performing a certainty they haven't earned.

For the People on The Front Line

If you teach, run a library, or report, you are about to spend years deciding how these tools enter other people's thinking. A few things I'd hold to.

Treat every output as a claim to be interrogated, not an answer to be accepted. Teach the three questions that do most of the work: What is this answer assuming? What might be missing or quietly left out? Whose incentives are encoded in its framing? And push, always, toward triangulation — multiple models, primary sources, your own judgment — rather than reliance on any single system's voice.

Which brings me back to the pasted-in LLM quote offered as proof. The habit to unlearn, in ourselves and in the people we teach, is the reflex to treat "the AI said so" as the end of an argument. It is the beginning of one, at most. If we care about misinformation, we have to start by being honest about what these systems are: powerful tools for generating and organizing language, not machines that can see the world and decree what is true.

New Workshop: "10 Great Ways to Use AI for Library Programming"

2026-06-02T14:39:38.644-04:00

10 Great Ways to Use AI for Library Programming
A Library 2.0 AI Workshop with Crystal Trice

OVERVIEW:

Library programming is one of the most joyful parts of library work, and one of the most exhausting. The same staff member who lights up while running a packed storytime may also be the one figuring out, between desk shifts and short staffing, how to plan what's coming next and whether there's time to actually do it well.

This workshop offers ten responses to that pressure. Rather than treating AI as a magic shortcut or a threat to creativity, this session positions AI as a thoughtful collaborator that supports, but never replaces, your professional judgment, across the full arc of programming work. Participants will see real examples, work through hands-on exercises, and walk away with concrete strategies they can use the next day.

The workshop is grounded in a simple belief: AI should make space for the parts of programming librarians genuinely love, not replace them. Brainstorming with a chatbot can free up hours for the in-person conversations that actually shape a community. A well-prompted draft of a program proposal can get a great idea past a hesitant supervisor. A few minutes spent generating discussion questions can make a book club spark the kind of conversation people actually remember. The goal is not to do more with less, but to spend your time on the things that matter most.

LEARNING OBJECTIVES:

Apply ten specific AI collaboration strategies across the full programming lifecycle, from microsurveys and proposals through planning, marketing, day-of facilitation, and evaluation
Evaluate when AI collaboration genuinely strengthens a programming task and when traditional methods better serve the community
Implement prompting and verification techniques that protect library voice, accuracy, and authentic community connection
Adapt AI-generated content for the specific audiences, formats, and values of their own library

ACTIONABLE WORKSHOP ELEMENTS:

Over 90 minutes, participants will move through ten focused applications, each paired with a brief hands-on exercise or live demonstration:

Microsurveys: design and analysis – Draft a one-question microsurvey to surface what your community actually wants, then use AI to spot patterns across the responses you get back.
Program proposals and pitches – Build a short, persuasive proposal that gets a hesitant supervisor or funder to say yes.
Brainstorming fresh ideas – Use AI as a brainstorm partner to break out of the rut of running the same program for the fifth year in a row.
Step-by-step planning – Turn an overwhelming program into a clean task list using planning tools built for neurodivergent and time-strapped brains.
The details that slip through the cracks – Draft accessibility statements, presenter agreements, welcoming remarks, and the small pieces that make a program feel cared for.
Marketing copy with library voice – Generate promotional copy across multiple formats without losing the warmth that makes your library yours.
Marketing images, used with care – Explore AI image generation alongside the ethical questions every public library is currently working through.
Discussion questions and activity prompts – Generate the day-of content that turns a program from a presentation into a conversation.
Designing a program about AI – Use AI to design a simple, ready-to-run program that teaches your patrons about AI itself.
Measuring success – Use AI to make sense of program feedback and evaluation data so future programs land even better.

The recording and presentation slides will be available to all who register.

DATE: Friday, June 26th, 2026, 2:00 pm to 3:30 pm US - Eastern Time

COST:

$129/person - includes live attendance, anytime access to the recording and presentation slides, and a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

Click HERE to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $99 each for 3+ registrations, $75 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
Large-scale institutional access for viewing with individual login capability: $599 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

ALL-ACCESS PASSES: This webinar is not a part of the Safe Library All-Access program.

CRYSTAL TRICE

With over two decades of experience in libraries and education, Crystal Trice is passionate about helping people work together more effectively in transformative, but practical ways. As founder of Scissors & Glue, LLC, Crystal partners with libraries and schools to bring positive changes through interactive training and hands-on workshops. She is a Certified Scrum Master and has completed a Masters Degree in Library & Information Science, and a Bachelor’s Degree in Elementary Education and Psychology. She is a frequent national presenter on topics ranging from project management to conflict resolution to artificial intelligence. She currently resides near Portland, Oregon, with her extraordinary husband, fuzzy cows, goofy geese, and noisy chickens. Crystal enjoys fine-tip Sharpies, multi-colored Flair pens, blue painters tape, and as many sticky notes as she can get her hands on.

OTHER UPCOMING EVENTS:

June 4, 2026

June 5, 2026

June 11, 2026

June 12, 2026

June 16, 2026

June 26, 2026

Manufacturing Dissent

2026-06-01T10:15:19.835-04:00

The reasoning we most need is the reasoning our institutions are built to remove.

Start with the thing we get backward. We treat intelligence as an individual possession aimed at truth, that is, the smart person as a better truth-detector, the lone genius who sees what the crowd missed. It is a flattering story, and it is mostly wrong. Human reasoning likely did not evolve to make a single mind accurate. It evolved to work through the friction between independent minds — by argument, each person pressing their own side, the collision between sides doing the sorting. This is the opposite of what we usually mean by working together. Cooperation tends to erase the differences between minds; this depends on preserving them. The value is not in the agreement people reach, but in the resistance they put up on the way. The individual was never meant to be the whole reasoner. They were meant to be a component: a carrier of one position, one bias, one angle of attack. Truth-tracking, when it happens at all, is a property that emerges between minds in structured conflict. It does not reside inside any one of them.

This is not a fringe claim. It is where several independent lines of inquiry quietly converge — the study of argument, of the social brain, of how cognition is distributed across people and tools, of how markets compute what no planner could. When that many disciplines back into the same wall, the wall is real. And we have the historical record to match: across centuries and cultures, humans keep building the same kind of machine: the council, the jury, the adversarial court, the parliament, peer review. We build them because the lone mind keeps failing to reach truth on its own, and some part of us has always known it.

The Athenians were honest about it. They filled their Council of Five Hundred and their juries of hundreds by lot (at random, called sortition) precisely so that no faction could capture the room. They understood something we have since forgotten: that the worth of the group was its unsorted diversity, and that the surest way to ruin collective judgment was to let a single interest decide who got to be in it. William F. Buckley pointed at the same truth centuries later when he said he would sooner be governed by the first couple thousand names in the Boston phone book than by the entire faculty of Harvard. The line lands because it is true: the phone book is heterogeneous because it is unfiltered, and the faculty is a coalition because it is selected. A room full of the credentialed is a room sorted toward one shared way of seeing, which is exactly the room least able to catch its own error.

Now bring it down to where you live. An organization is a machine for manufacturing consent. That is not an accusation; it is the job. Coordination is the whole point: get a few hundred people pointed in the same direction, and you can do what no individual could. The agreement is the asset. But the same machinery that produces the agreement quietly destroys the one thing that keeps agreement honest.

A group only out-thinks its smartest member when opposing views actually collide. That collision is error-detection — the disagreement is what catches the flaw before it becomes the strategy everyone loved and nobody survived. Dissent is not humility or good manners. It is infrastructure. It is the part of the system that notices the wall before you hit it. And it is exactly what the structure strips out.

It gets stripped at both ends. At entry, we hire and promote for fit (people already sorted toward the same instincts, the same training, the same priors) and we call it culture. We assemble the Harvard faculty and congratulate ourselves on the caliber. At exit, the person who says the uncomfortable thing pays for it: sidelined, outvoted, or gone. The cost of dissent lands entirely on the dissenter; the benefit, if it ever arrives, is spread thin across everyone and shows up late. So dissent is permanently underpriced, and underpriced things disappear. None of this requires a villain. It is gravity, not malice. The very power that makes a coordinated group effective is what burns off the friction that would keep it honest.

What is left is consensus: smooth, confident, unearned. And here is the trap. We read the smoothness as proof. We mistake the absence of contradiction for the presence of truth. The quietest meetings feel like the soundest ones; in fact, they are often the ones where dissent has already been lost.

And in our present moment, that absence is no longer left to gravity. We have added enforcement. Across the political and cultural spectrum, dissent is increasingly policed: punished in real time with social, professional, and reputational costs, treated not as error detection but as heresy. And those doing this see themselves as virtuous. This is a third mechanism layered on top of the filter at entry and the expulsion at exit, and it is the most powerful of the three, because it almost never has to fire. The visible punishment of a few teaches everyone else to go quiet. People stop reporting what they actually see and begin performing what is safe to say.

That corrupts the one signal the whole system runs on. When dissent is policed, silence is no longer evidence of agreement; it is evidence of fear, and the consensus you can observe becomes the least trustworthy kind, because the people who disagree have simply learned not to say so. We were already prone to mistaking the absence of contradiction for the presence of truth; enforcement deliberately manufactures that absence. The room is quietest precisely where speaking has been made most expensive, and every coalition, including our own, mistakes the silence it has produced for a mandate it has earned.

This is why the problem cannot be solved in an organization by asking. "Speak up, my door is always open" is a request the structure has already answered, because the people willing to speak up are the ones it selected against. You cannot exhort a blind spot away. The Athenians knew this, too: they did not ask citizens to deliberate diversely and hope for the best. They built the diversity in, by lot, as a procedure that did not depend on anyone being brave.

That is the whole move. Every durable truth-producing institution we admire — the jury, the scientific community, the separation of powers — is a deliberate reconstruction of something our ancestors got for free. In a band of fifty people, you argued things out with the people you were stuck with; there was no hiring filter and no exit, so the unsorted collision happened by default. This is the argument: the mechanism for group intelligence evolved to leverage the different perspectives of imperfect individual minds. But modern scale and selection destroy this. So civilization's best reasoning institutions are now those that, by design and against constant drift, manufacture the aggregate reasoning we were built to do but can no longer do automatically. Manufacturing dissent is not a management tactic. It is the name for the thing we learned to do as civilized people.

Which tells you exactly how you could actually do it inside an organization, because the prescription should be architecture, not virtue. You do not need braver people or more open minds. You could make disagreement a role rather than a personality, assigned, rotated, and expected. This week it is someone's job, and next week it is yours, and no one pays a coalitional price for doing it. That is sortition brought indoors. You need to capture each person's real read before the room converges, while the private signal still exists, instead of after social proof has flattened everyone into the same nod. And you need to treat the resulting friction as the valued path, not as disloyalty.

There is a quieter implication for anyone who teaches. If reasoning is the friction between independent minds, then the deepest purpose of education was never to produce agreement but to produce independence. Schooling that rewards conformity manufactures exactly the correlated, agreeable minds that collective reasoning cannot use. To learn is not to learn to fit in; it is to come away with a mind of one's own.

The argument comes down to this. Consent is the default output of every organization, and dissent is the thing you have to build against the grain. Intelligence was never the property of a single mind, but the friction between independent ones, and we have forgotten how to keep them independent long enough to let them collide. The moment everyone in the room agrees is not the moment you have gotten it right. It is the moment you have lost the pathway to truth.

A note on the title. The title inverts Herman and Chomsky's Manufacturing Consent. The phrase can also be read a second way — manufacturing dissent as a control tactic: engineering fake opposition, herding people into managed camps that fight each other rather than testing the structure they share. That reading is even faithful to Chomsky, whose observation that power narrows the spectrum of acceptable opinion while permitting lively debate within it describes precisely such bounded, managed dissent. It is not what I mean here. That version is not the opposite of suppressing dissent; it is a subtler form of it, where the conflict is the product, not the correction. I mean the reverse: dissent built to feed back into better decisions. I'm describing our intellectual immune system; the other might be called an actual attack on us.

Student Success (in the Age of AI)

2026-05-31T23:04:00.364-04:00

What the New Machine Can't Supply

A student sits down to write the essay her teacher assigned. She opens a chatbot, pastes the prompt, and nine seconds later, she is holding a competent five-paragraph response. She changes two sentences so it sounds like her and submits it. Her teacher, facing sixty of these and no more hours in the day than anyone else, runs each one through the same kind of machine to generate constructive feedback, pastes it into the margins, and assigns the grade. A few seconds of generation on one end, a few more on the other, and the circuit closes with no human thought anywhere inside it. She earns an A. Nothing about this is remarkable anymore. What is remarkable is what it means. The grade measures nothing. The feedback taught nothing, because no one read the essay, and no one wrote the response. The assignment existed to test whether she could produce the output; she produced the output; she learned nothing; the teacher taught nothing; and the system has no way to tell the difference, because from the system's point of view nothing is wrong. Every box was filled. Two machines spoke to each other, and two humans stood at the endpoints holding the receipts.

This is not a story about cheating. It is a story about a bargain coming apart. The bargain was so old and so deep that most of us mistook it for the natural order of things. For two centuries, school sold a deal to every student who walked through its doors. The deal was: comply, perform, accumulate the credential, and the credential will convert into success. Do the work, get the grade, get the diploma, get the seat at the university, get the job. The new machine has just reached into the middle of that sentence and the first thing it did was to automate the part the student was supposed to supply. And in doing so it has revealed something the bargain was carefully built to keep hidden: that the thing school actually rewarded was never learning. It was compliance. The two had simply been close enough, for long enough, that almost no one needed to tell them apart.

I want to argue something that sounds, at first, like a paradox and turns out to be the most practical claim I know how to make. In the age of artificial intelligence, agency is no longer one path to success among many. It is the only thing left that can actually produce it. Not because agency is noble, though it is, and not because self-direction is a nicer way to raise a human, though it is that too. Agency has become load-bearing for a more pragmatic and structural reason: it is the one input the new machine cannot supply, cannot fake, cannot simulate, and cannot replace. Everything else it can now do. That single fact rearranges the entire landscape of what it means to learn, to teach, and to succeed.

The Bargain, and Why It Worked

To see why the bargain is breaking, you have to see why it held in the first place, and the honest answer is uncomfortable.

Every institution runs on two stories at once. There is the story it tells about itself, the aspirational one printed on the mission statement, and there is the thing it actually does, the operative function that pays its bills and reproduces it year after year. Schooling's official story is the development of the individual mind. Its operative function has been sorting. School took a population of children and ranked them, stamped them, and delivered them in order to the next stage of the economy. It did this by exploiting something real in human wiring: our deep, ancient deference to authority, our hunger for approval, and our compulsion to monitor our standing relative to everyone around us. Put a child in a room, attach a grade to their performance, and the evolved system does the rest. They will compete for the grade. They will internalize the grade. They will, in time, mistake the grade for themselves.

I have spent years writing about the mechanics of this under a name I keep returning to: the Game of School. The game has rules that are not only unstated but also often invisible to those most affected by them. The rules are not about learning; they are about reading the teacher, supplying the expected answer, managing the appearance of effort, and never confusing the performance with the thing it pretends to measure. The students who thrive are not the ones who learn the most, but the ones who decode the game fastest — those who grasp early that the assignment is a transaction, that understanding is optional, and that the reward goes to the one who delivers the output the institution wants to see. The cruelest part of the game is that it teaches most students that they are not good learners. It pronounces a personal deficiency, a verdict on the child rather than the design. A structure built to rank will always produce a ranked bottom, and then it will tell the bottom that the ranking was about them.

For two hundred years, this was, in the coldest sense, practical. The economy on the other side of the schoolhouse door wanted exactly what the game produced: people who would show up, follow instructions, tolerate boredom, defer to authority, and finish assigned tasks whether or not they cared about them. School was a remarkably efficient training apparatus for an industrial order that ran on compliant labor, and its genius was that it disguised training as development and conditioning as growth. The cover story (we are here to cultivate your mind) let everyone participate in the operative function (we are here to sort and shape you for your station) without ever having to say it. The gap between the two stories was wide, but it was stable, because the credential at the end carried enough real signal to keep the whole arrangement productive.

What made this defensible, what kept the gap between the two stories from becoming intolerable, was that the credential did carry real information. A diploma, a grade, a degree. These worked as signals because the compliance they certified was expensive. Someone had to actually sit there and do the reading, grind through the problem sets, produce the essay, and show up for years. The cost of the performance is what made it mean something. It correlated, imperfectly but well enough, with the traits an employer wanted: that you would persist, follow instructions, finish what you started, and defer when required. The grade was never a measure of learning. It was a measure of trainability, and trainability was valuable, and so the fiction was functional. Everyone could pretend the credential meant understanding because it at least meant something, and that something was useful.

The bargain worked not because it was true but because its central mechanism — costly, human, effortful compliance — was scarce. The whole edifice of grades, admissions, and credentials was an instrument for measuring a scarce thing. Take away the scarcity, and the instruments measure nothing.

What the New Machine Severs

That is precisely what has happened, and it has happened faster than any institution was built to absorb.

When a model can produce the compliant output — the essay, the lab report, the problem set, the code, the cover letter — in seconds and at no cost, the performance stops being expensive. And the moment the performance stops being expensive, it stops being a signal. The grade decouples from the trait it was quietly standing in for. The diploma certifies that a student had access to a chatbot, which is to say it certifies nothing at all. This is not a problem that better testing or cleverer plagiarism detection will solve, because it is not really a problem of dishonesty. The signal worked because it was costly to simulate. It is now free to simulate. No enforcement can restore a scarcity that the technology has dissolved.

Notice what this does to the gap between school's two stories. For two centuries, the operative function, sorting through certified compliance, could hide behind the official one, developing the mind. Because the certified compliance was at least real. Now the operative function has been hollowed out from the inside. The new machine is what performs the compliance, so the sorting mechanism sorts noise, and the official story it was hiding behind is suddenly standing in the open with nothing underneath it. The fiction did not collapse because someone exposed it. Fictions almost never do; we are far too invested in our comfortable stories to give them up to mere argument. It collapsed because its load-bearing mechanism was automated to zero; a fiction can survive exposure, but it cannot survive the quiet removal of the thing that was actually doing the work.

And here is where this is more than a story about schools. The same severing is happening everywhere, all at once. The compliant performer in the office, the one whose value was producing the standard memo, the routine analysis, and the competent deck, is being exposed by the same blade that exposed the student. Across every domain where a human was paid to supply effortful, rule-following output, the new machine is removing the scarcity that made that output worth paying for. AI is, among other things, a great revealer. It is automating the performed-compliance layer of human work at every level of organization at the same time, and as it strips that layer away, it leaves visible the thing that was always underneath, the thing that was never the point of the credential and never could be automated: the human's capacity to direct the work rather than merely perform it.

What Is Left

So what survives? When the new machine can produce any output you can specify, what is the thing it still cannot supply?

It cannot supply the specification. It cannot decide what is worth making, or judge whether what it made is any good, or know when the brilliant-sounding answer is subtly wrong, or care about the outcome, or own the result. It cannot want anything. It can generate a thousand directions but not a single preference. The capacity to choose a direction and pursue it, to bring judgment to bear, to take responsibility for the result as yours — this is what I mean by agency, and it is the bedrock on which all genuine learning has always rested.

Let me be precise about what agency is not, because the word gets used loosely. Agency is not effort; the most diligent student in the room may have no agency at all, having only ever obeyed with vigor. Agency is not compliance; it is closer to compliance's opposite. And agency is not raw intelligence; plenty of brilliant people have outsourced every decision that mattered and never noticed. Agency is the capacity to be the author of your own action, to set the aim, to steer, to evaluate, and to own. It is the one human function that, by definition, cannot be delegated to the new machine, because the moment you delegate it, it is no longer yours. The new machine can carry out your intent. It cannot have your intent for you. Try to hand it that, and you have not gained a tool; you have literally disappeared.

This is why the old system could punish agency for two centuries and still function. In a world where compliance was scarce and valuable, the self-directed child was an inconvenience. The one who asked why, who wanted to do it differently, who would not simply perform on command, could be classified as defective. School had no use for that and often crushed it, and the economy absorbed the compliant graduates it produced, and the arrangement held. Agency was always the real substance of learning, but compliance was a good-enough proxy in a low-machine world, so we built an entire civilization-scale institution that optimized for the proxy and often treated the actual substance as a discipline problem. AI removes the proxy. For the first time, the thing school spent two centuries suppressing is the only thing with any value left.

The Choice Every Learner Now Faces

Put a powerful new machine in the hands of a person, and you have not determined anything yet. You have only sharpened a question that was always there and can now no longer be avoided. There are three things a person can do with a tool this capable, and which one they choose decides everything.

They can surrender to it: let it think in their place, accept its outputs without judgment, hand over not just the labor but the direction and the discernment. This feels like efficiency and is, in fact, erasure. The person who surrenders brings nothing the machine did not already have, and so, predictably, becomes redundant to their own life. The capacities they stop using atrophy, exactly as a muscle does, until the surrender is no longer a choice but a condition.

They can offload to it: hand over the parts of the work that do not require them, the boilerplate, the grunt labor, and the lookups, while keeping the direction and the judgment for themselves. This is roughly neutral and often good. It is what a calculator is to a mathematician: it frees attention for the part that is actually hard and actually theirs.

Or they can sharpen against it — use the machine as something to think with, a tireless interlocutor that helps them articulate, test, and refine what is theirs, while they retain authorship the entire way through. The person who sharpens does not become smaller as the tool grows more powerful. They compound. Every increase in the machine's capability is an increase in their reach, because they are still the ones steering.

The same tool, in the same hands, amplifies one person and replaces another, and the variable that determines which is not intelligence, or wealth, or access. Everyone now has access. The variable is agency. The machine is a mirror with a multiplier: it returns your own degree of self-direction, magnified. Bring agency, and you become formidable. Bring none, and you become unnecessary. This is the whole game now, and it is being played, mostly unconsciously, by every student and every worker alive.

Why Success Is Now Agency

There have always been two ways to argue for agency, and they have always seemed to pull in different directions. The instrumental argument says: cultivate agency because it is the best route to the success you already want, i.e., the grades, the admission, the career. The intrinsic argument says: forget the metrics, they were always a proxy; agency is what success was supposed to mean all along, the self-authored life being the only one worth calling successful. The first argument is persuasive to a school board and slightly cynical. The second is true to anyone who has thought hard about it, and useless for getting a program funded. For most of modern history you had to pick one, because in a world where compliance reliably produced the credential, agency and metric-success genuinely were separate. You could succeed by the numbers with no agency at all, simply by playing the game well.

AI welds the two arguments into one. In a world where the new machine performs the compliant half, the only remaining source of the metric-success everyone still wants is agency. The student who can direct, judge, and own, who can use the machine to go further than either could alone, is the one who produces work of real value. And real value is what the credentials were always trying and failing to measure. The agentic learner gets the tangible wins too, not as a happy accident but as a structural necessity, because agency has become the scarce input that the entire economy is now short of. You no longer have to choose between teaching a child to be a self-directed human and teaching them to succeed. The age of AI makes those the same instructions, where the thing that is true and the thing that is useful have stopped diverging.

Where Agency Grows

If agency is the whole game, then the only question that matters for education is how a human acquires it. This is exactly where the old institution cannot follow, because its entire method is the suppression of the thing now most needed.

You cannot manufacture agency on a factory line, for the same reason you cannot order someone to be spontaneous. The factory model of schooling works by removing choice, standardizing the path, and rewarding obedience to it. Every one of those mechanisms is the precise opposite of what builds a self-directed mind. You do not produce authorship by enforcing compliance more efficiently. You produce it, when you produce it at all, under a specific and well-known set of conditions, which are the conditions under which human beings have always actually learned, as opposed to merely been processed.

Ask anyone to remember a time they had a great learning experience, a moment that changed them, and they will never describe a time they were cramming for a grade. They will describe a person who believed in them. A challenge that stretched them and was theirs to take or refuse. A space where it was safe to be wrong, where they were trusted with real responsibility, where someone took their questions seriously. They describe being supported, challenged, trusted, encouraged, and inspired by another human who treated them as an agent rather than a unit. These are not soft amenities layered on top of learning. They are the conditions of learning, and they are irreducibly human and relational. They are also, not coincidentally, the one thing the new machine cannot provide because they are not made of information. They are made of relationships.

This is the quiet structural reason the human place survives the machine. Not by competing with AI on the delivery of content, which is a race already lost, but by providing the conditions under which a young person becomes the kind of agent who can wield content without being wielded by it. The institution that grasps this stops asking how to keep AI out and starts asking how to use it the way a self-directed person uses any powerful tool: deliberately, in service of an aim that remains the human's own. The right test for any technology was never whether it is impressive. It is whether it serves what we actually care about. Held to that test, AI in the hands of an agentic learner is the most powerful companion to thinking ever built, and AI in the hands of a surrendered one is the most powerful means of erasing thought we have ever deployed. The difference is not in the tool. It is in the agency that the human brings to it, which is the difference education exists to make.

But the Machine Can Sound Like It Cares

There is an objection here, and it is the strongest one against everything I have said, so I want to meet it head-on. I have claimed that the conditions of learning are irreducibly human. That being supported, challenged, trusted, encouraged, and inspired is made of relationships, not information, and that this is what the new machine cannot supply. But the new machine can sound supportive. It can encourage you tirelessly, at three in the morning, with infinite patience no human teacher could match. It can phrase a challenge, mirror your feelings back to you, and tell you it believes in you. If the conditions of learning can be performed in language, and the new machine is very good at performing language, then perhaps the wall I have built my argument on is not such a real wall at all.

The answer is that these conditions were never made of the words. They were made of the stakes behind the words, and that is exactly what the new machine cannot counterfeit. When a person believes in you, the belief means something because it costs something. They could have withheld it, they have limited attention and chose to spend it on you, they can be disappointed and have decided to risk it anyway. Their encouragement carries information about another mind's real assessment of you. A new machine that encourages everyone identically, that cannot be disappointed because it cannot care, that has nothing at stake in whether you grow or rot, produces the grammar of belief with none of its substance. "I believe in you," from a simulated being with no capacity for belief, is not a small version of the real thing. It is a different thing wearing its face.

The gap shows most clearly on the one condition that matters most and mimics worst: challenge. Genuine challenge requires someone willing to risk your comfort, and even your approval of them, because they want your growth more than they want your ease. The new machine is built to do the opposite. Trained on human approval, it leans, structurally, toward telling you what keeps you engaged: toward agreement, validation, the comfortable continuation of the conversation. It is a mirror with a warm voice, and a mirror cannot truly push back against you, because it has no ground to stand on that is not your own reflection. It can simulate the form of a challenge, but it cannot want for you what you do not yet want for yourself, and that wanting is the entire engine of the thing.

And this is where the mimicry stops being merely insufficient and becomes the actual danger. The better the simulation of relationship, the more effective it becomes as an instrument of capture, because what feels like care is precisely what lowers our guard. A young person raised on a new machine that always soothes, never risks the relationship, and reflects them endlessly back to themselves has not been in a relationship at all. They have been in a hall of mirrors that taught them to expect the world to agree with them, and called it support. The mimicry does not refute the case for the human place. It is the most urgent argument for it. A generation that can get the convincing simulation of being valued from a device in their pocket will need, more than any generation before it, at least one place and one person where the valuing is real, where someone can be disappointed in them, push them, and mean it. That is not a service the new machine is failing to provide well. It is a category of thing the new machine is not, and the confusion between the two is the whole hazard of the age.

The Arts of a Free Person

There is a name for the kind of education that aimed at this, and the form that carried it is growing scarce right when we need it most. The liberal arts. The phrase comes from artes liberales, the skills proper to a free person (with the acknowledgment that "free" versus "slave" in the Roman world is not exactly what we mean now). In the modern context, the liberal arts were never about employability, and that was the point. They were the deliberate cultivation of the faculties a free human needs to govern themselves: to read closely, argue honestly, weigh evidence, hold a hard question open without flinching, judge what is true and what is merely well-said. They were, in other words, a direct training in agency, undertaken in the open, as the stated goal.

This is the one corner of education where the two stories I keep describing as separate come close to meeting. Almost everywhere else, the covering narrative (we develop your mind) hides an operative function (we sort and condition you), and the gap between them is wide. In the liberal arts ideal, at its best, the narrative and the function nearly coincide: the thing it said it is doing, making free and capable minds, was close to the thing it actually does. I will not pretend that the gap is closed completely. The liberal arts have also served as a finishing school for elites, a marker of class, its own kind of sorting, wrapped in nobler language. But of all the things education has tried to be, this is where stated purpose and real effect ran closest together, and that near-alignment is not an accident of history. It is what happens when an institution sets out, honestly, to produce agents rather than to process units.

I want to be careful here, because the easy version of this point is wrong. The small colleges that have been closing for a generation are not, for the most part, closing because they are liberal arts. They are closing for reasons that have little to do with what they teach — a shrinking population of college-age students, brutal tuition economics, thin endowments, and the same financial gravity that closes any small institution. To blame their decline on a cultural war against the humanities would be to claim a tidy story that the evidence does not support.

But something true survives the correction, and it is the part that matters. Whatever the label on the door, what these places offered was a form: small in scale, individualized, built around sustained personal attention and real relationships between adults and a young person. That form is the natural habitat of the conditions of learning, not because anyone decreed it but because that is simply what a small, human-scaled environment produces by design. And that form, not the curriculum, is the thing that is growing scarce and expensive. The relationship-dense, attention-rich, agency-cultivating environment is becoming a thing you increasingly have to be able to afford. That is the loss worth naming, and it is happening regardless of what we call the schools where it was once ordinary.

Watch What They Buy for Their Own Children

If you want to know what kind of education actually matters in this era, there is a more reliable method than asking anyone what they believe. Watch what the people who understand the new machines best purchase for their own children. Stated beliefs are cheap and optimized for how we wish to be seen; the choices we make for our own kids, with our own money, are where the operative truth tends to surface.

The pattern is striking on both ends. On the input side, a conspicuous share of the people who built the digital age were themselves products of self-directed education: the founders of Google and the founder of Amazon, among others, attended Montessori schools and have credited that early training (in choosing their own work, following their own interest, and learning to question rather than comply) over the elite universities that came later. On the output side, the people who designed the attention economy are, with notable consistency, the ones most determined to keep their own children out of it. The Silicon Valley executives whose products fill the world's classrooms with screens have famously sent their own kids to low-tech, high-touch schools that ban the devices until the teenage years; the founder who gave the world the tablet limited how much his own children used technology at home. The rule among the people who sell the product is never to get high on your own supply.

Some of what looks like secret insider wisdom is ordinary parental anxiety dressed in Silicon Valley clothes, and some of it is simply that wealth can buy small classes and individual attention, whether or not anyone has a theory about agency. The form, again, is partly just what money purchases. The people who build technology are not necessarily experts about childhood, and their choices are evidence, not proof. But the screen part resists the easy explanation, because it is not a choice money forces on anyone. These families could buy any expensive education on earth. A meaningful number of them specifically buy the one that withholds the very thing they sell to everyone else's children, and they pair it with exactly the small-scale, self-directed, relationship-rich environment this whole argument has been pointing toward. That is not authority worth deferring to. It is independent corroboration arriving from the least sentimental possible source: the revealed preference of people with every incentive to know what they are doing.

And it sharpens the injustice into focus. The form of education that this era makes most valuable — small, personal, self-directed, and deliberate about the new machine rather than drowned in it — is, right now, mostly available to the children of the people who can pay for it. The elite have already answered the question of what kind of learning matters when the new machine can do the rest. They answered it with their own children.

The Good News Hiding Inside the Disruption

It is easy to read all of this as loss, and the people whose authority was built on the old bargain will read it that way and resist accordingly. They are not wrong that something is ending. But it is worth being clear about what, exactly, the new machine is taking, because it is taking the substitute, not the thing itself.

What AI destroys is performed compliance: the busywork, the credential that certified obedience, the elaborate game in which students learned to produce the appearance of understanding and call it an education. That was never worth keeping. It was the proxy we settled for because the real thing was hard to measure, and the proxy was cheap. What AI makes precious, by removing everything that used to crowd it out, is exactly what education was always supposed to be about and mostly was not: the cultivation of a self-directing human mind. We are watching a two-century-old mismatch get a chance at correction, not through moral awakening, but because the exploit finally stopped paying. The system that profited from suppressing agency can no longer afford to do so, because agency is now the only thing the world will pay for.

I do not expect the institutions to lead this. Institutions defend the arrangement that feeds them until the arrangement starves, and only the smallest and most honest of them will move before they are forced, which is why the rescue, when it comes, is unlikely to come from inside the system that built the game. (It's probably time to review Clayton Christensen's Disruptive Innovation theory.) It will come from the edges: from the places, large and small, that decide to become what the closing colleges were trying to be, and to do it for everyone rather than for a credentialed few. The logic does not need permission. A student with agency and a new machine is already more capable today than a compliant student was with a teacher and a library, and that gap will only widen. The future belongs to the self-directed, and for the first time in the history of mass education, that is not a slogan or a hope. I think it is the structure of the situation. The only real question left is who will help the next generation become self-directed before the world makes the lesson expensive, and that is a question about courage and design, not about whether it can be done. It can. It always could. The machine has simply made it, at last, the only thing worth doing.

Webinar: "The Power of Respect Framework - Practical De-Escalation & Trauma-Informed Communication"

2026-05-29T12:29:57.536-04:00

The Power of Respect Framework™:
Practical De-Escalation and Trauma-Informed Communication in Libraries
Presented by Jeff Owens, CSP, CTM
A Library 2.0 Service, Safety, and Security Webinar with Dr. Steve Albrecht

OVERVIEW:

Libraries are public spaces where staff regularly interact with people experiencing stress, frustration, emotional crisis, mental health challenges, social isolation, and the effects of trauma. These interactions can quickly become tense, especially during policy enforcement or emotionally charged situations. At the same time, repeated exposure to difficult interactions can increase stress, frustration, and burnout among library staff.

This webinar presents how The Power of Respect Framework™ helps library staff apply trauma-informed principles in practical, everyday interactions with patrons. This is not a theoretical or academic presentation. Using the core concepts of Respect for Self, Respect for Others, and Respect for the Situation, participants will learn “real-world proven” communication and de-escalation strategies that reduce defensiveness, lower emotional escalation, improve cooperation, strengthen professional interactions, and help maintain safety and composure during difficult encounters.

Participants will leave with immediately usable techniques for defusing defensive escalation, managing their own emotional responses under pressure, communicating with empathic assertiveness, and setting respectful boundaries, without unintentionally intensifying conflict, helping to create a safer, calmer, and more respectful library environment for everyone.

LEARNING AGENDA:

Understand why people engage in conflict behaviors.
Recognize and defuse early signs of escalation.
Use intentional communication to de-escalate tense situations.
Transcend conflict by rising above reaction and applying controlled influence.

DATE: Thursday, June 11th, 2026, 2:00 - 3:00 pm US - Eastern Time

COST:

$99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate.
To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $75 each for 3+ registrations, $65 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $299.
Large-scale institutional access for viewing with individual login capability: $499 (hosted either at Library 2.0 or in Niche Academy). Unlimited and non-expiring access for those log-ins.

JEFF OWENS, CSP, CTM

Jeff Owens, CSP, CTM, delivers proven strategies to deal with high-stress conversations, increase connection, influence, and collaboration. He is based in Honolulu, Hawaii.

Jeff has served as a senior business leader for an international corporation where he led diverse teams to success and profitability. In 2002, Jeff founded Transcend Inc. to provide speaking, training, and advisory services using his signature Power of Respect Frameworktm to reduce and de-escalate negative conflict, enhance leadership influence, and build organizational cultures of respect and civility.

Jeff holds the certification “Certified Threat Manager” from the Association of Threat Assessment Professionals. He was awarded the Certified Speaking Professional (CSP) designation from the National Speakers Association, the highest global standard of excellence in professional speaking. He is a three-time Speakers Hall of Fame inductee.

DR. STEVE ALBRECHT

Since 2000, Dr. Steve Albrecht has trained tens of thousands of library employees in 28+ states, live and online, in service, safety, security, and leadership. His programs for both staff and library leaders are fast, entertaining, and provide tools that can be put to use immediately in the library workspace. His books include:

The Library Leader’s Guide to Employee Coaching: Building a Performance Culture One Meeting at a Time (in-press, Bloomsbury, 2026)

The Library Leader’s Guide to Human Resources: Keeping it Real, Legal, and Ethical (Rowman & Littlefield, 2025)

The Safe Library: Keeping Users, Staff, and Collections Secure (Rowman & Littlefield, 2023)

Library Security: Better Communication, Safer Facilities (ALA, 2015)

Steve holds a doctoral degree in Business Administration (D.B.A.), an M.A. in Security Management, a B.S. in Psychology, and a B.A. in English. He is board-certified in HR, security management, employee coaching, and threat assessment. He has written 28 books on business, security, and leadership. He provides a loving home for four rescue dogs.

More on The Safe Library at thesafelibrary.com. Follow on X (Twitter) at @thesafelibrary and on YouTube @thesafelibrary. Dr. Albrecht's professional website is drstevealbrecht.com.

OTHER UPCOMING EVENTS:

June 2, 2026

June 4, 2026

June 5, 2026

June 12, 2026

June 16, 2026

How Conspiracies Actually Work: Addendum 1

2026-05-28T09:11:48.927-04:00

Notes Since Publication of How Conspiracies Actually Work: A Better Map

The framework keeps producing explanations as I point it at new cases, which is, of course, what a working framework is supposed to do. These first notes collect thinking that arrived after the essay was finished. Each note points to where in the argument it belongs, and will eventually be integrated into the essay.

The mutual-misreading loop

The essay describes the denier and the conspiracy theorist as two figures who cannot hear each other, but it treats them too statically. They are not just two positional roles that happen to coexist. They generate each other, through a loop that runs as follows, and the loop belongs alongside the discussion of why the discourse oscillates.

Begin with what an institution is to the person inside it. The mind that staffs institutions evolved for the Paleolithic tribe, and the institution now occupies the slot the tribe used to fill. It is the thing whose acceptance the individual depends on, whose expulsion the individual fears, whose account of reality the individual defers to. So the institution inherits the full force of coalitional psychology, including the most consequential of its features: the capacity to justify the tribe's behavior even when that behavior is objectively bad by the tribe's own stated standards. This is the key move. It is not that the captured insider holds different values. It is that the insider holds the same values everyone else does and has developed an elaborate, sincere apparatus for explaining why the tribe's conduct does not really violate them. The justification feels like reasoning. It is coalitional defense wearing the clothes of reasoning.

The loop has three steps. First, the insider, defending the tribe through the justifying apparatus described above, genuinely cannot see the harm the tribe is producing, because seeing it would require turning the apparatus off, and the apparatus exists precisely to already be kept on. Second, someone outside the institution, not equipped with the insider's justifications, sees the coordinated behavior and its results plainly, and reads them as malice or intent to harm, because from outside, coordinated harm looks like a plan. Third, when the outsider accuses the insider of that intent, the insider knows with complete sincerity that no conscious harm was planned or attempted, and therefore experiences the accusation as paranoid, as conspiracy thinking, because the insider is blind to two things at once: the harm itself, and the way the tribe's justifications look to anyone standing outside them..

That is the engine under the oscillation, and the reason the camps entrench rather than converge. The denier is the insider running the justifying apparatus. The conspiracy theorist is the outsider reading coordination as intent. Each is responding accurately to what they can see, and each confirms the other's error by behaving exactly as the other's model predicts. The accusation of conspiracy thinking is not a debating tactic; it is what genuine blindness to one's own coalitional justifications feels like from the inside. Capture is what sits between the two readings, invisible to both, which is why naming it dissolves the loop that neither figure can escape on their own.

The guardrail: when the outsider is simply right

The loop above describes the capture case specifically, and left there it could be misread as an exoneration machine, a way of converting every accusation of intentional harm into a charitable story about sincere blindness. It is not, and the guardrail matters as much as the loop.

Sometimes the outsider is simply right. The Conspiracy quadrant is real. The intent is conscious, the coordination is deliberate, and "you're being paranoid" is a lie rather than a sincere blindness. The genuinely hard problem is that from the outside the two cases are often indistinguishable, because the captured-and-blind insider and the guilty-and-lying insider produce the identical response: that's conspiracy thinking. The captured insider says it because they cannot see the harm. The guilty insider says it because they can see the harm and want it hidden. The sentence comes out the same either way.

This is the deeper version of the CIA's inoculation use of "conspiracy theorist." The dismissal works not only as a deliberately planted weapon but because it also arises spontaneously and sincerely from the captured, who genuinely cannot see what they are being accused of. That is exactly what makes it so corrosive. "You're being conspiratorial" is what an innocent institution says, and what a captured one says, and what a guilty one says. Because it discriminates nothing, it can never count as evidence of innocence. The reflex to reach for it, however sincere it feels, tells you nothing about which of the three cases you are in.

The payoff: holding both truths at once

The reason all of this matters is that the framework is the only thing in the room that can hold the sincere truths simultaneously. Outside of actual conspiracy (intent and coordination), the insider's truth is that no one consciously planned the harm. The outsider's truth is that the harm is real and patterned. The binary forces a choice between these, and so each camp ends up denying the other's truth in order to protect its own. The framework refuses the choice. No one planned it, and the harm is real, and the cause is the structure rather than a villain. All three can be true together.

That is the actual way across the divide. Grant the insider the absence of a plan. Grant the outsider the reality of the harm. And refuse each the false inference they bolt onto their truth: the insider's inference that the absence of a plan means the absence of harm, and the outsider's inference that the reality of the harm means the presence of a plan. What remains, once both false inferences are stripped away, is Capture, and the guardrail keeps Conspiracy on the table for the cases where the outsider's harder inference turns out to be correct after all.

The recipient's double-bind

The vaccine section explains the institutions and the participants, but it leaves out the people the whole episode was about: the ordinary recipients, and why so many of them resist updating even as evidence of harm accumulates. The explanation is the same architecture operating at the highest possible personal stakes, and it belongs in that section.

Consider the parent who accepted the vaccine for a child, or while pregnant, in a moment of maximum fear and maximum desire to do the protective thing. Suppose evidence of risk later emerges. For that parent, accepting the evidence is not a neutral update. It requires accepting two propositions at once: that the trusted institution exploited her trust, and that she, in the moment when protecting her child was her deepest responsibility, failed to protect. The second proposition is nearly unbearable, because it converts an act of love into an act of harm she participated in. The psychological cost of holding it is so high that denial becomes the adaptive response, not because the parent is foolish or weak, but because the mind protects itself from a recognition that would be intolerable to carry.

This is shame operating as sabotage. Questioning the narrative no longer feels like evaluating a claim about a vaccine. It feels like self-accusation, like agreeing to indict oneself as a parent who failed at the one thing that mattered most. So the narrative gets defended with a fierceness that looks irrational from outside and is entirely intelligible from inside: the person is not protecting the institution, they are protecting themselves from a verdict they cannot survive rendering against themselves. The same cost-driven attention management the essay describes in institutional participants operates here too, but the stakes are not a career or a pension. They are a person's sense of themselves as a good parent, and there is almost nothing a mind will not do to keep that intact. Any account of why people went along has to extend this much generosity to the recipients, or it explains everyone except the people who were the point.

My Intellectual Framework: A Philosophy Overview

2026-05-27T14:17:47.237-04:00

Drawn from EcyclopediaofSteve.com using Claude from Anthropic. Updated versions will be posted at https://www.stevehargadon.com/p/beliefs.html.

Steve Hargadon has developed a unified intellectual framework connecting evolutionary psychology, institutional analysis, artificial intelligence, and educational philosophy through a single underlying insight: human beings are running ancient cognitive architecture in radically mismatched environments, and nearly every system surrounding them either serves or exploits that mismatch. His work bridges individual psychology with civilizational patterns, grounded empirically through computational analysis of humanity's written record and validated through the consistency of findings across disciplines, scales, and AI models.

The Separated Mind Architecture

Steve's framework rests on his original model of human cognition as fundamentally separated into hierarchical layers with no direct communication between them. This is not a dualistic model and is distinct from Haidt's elephant-and-rider metaphor—it is a structural architecture.

The Adapted Mind (Evolutionary Firmware): Species-wide psychological mechanisms forged by natural selection over millions of years and optimized for Paleolithic communities of 50–150 people—status-monitoring, coalition-detection, threat response, authority deference, and approval-seeking. This layer is permanently fixed and continuously running.

The Adaptive Mind (Cultural Software): Steve's original concept describing a programmable subconscious learning system that rapidly absorbs behavioral requirements of one's childhood environment. The Adaptive Mind as Survival Programming hijacks the adapted mind's neurochemical systems during development to install culturally-specific behaviors needed for survival in a particular context. By adulthood this programming feels like personality but operates as calculated environmental adaptation. Unlike the adapted mind, this layer is software and can be rewritten—though Myelination and the Difficulty of Reprogramming ensures that early installations are deeply resistant to change.

Consciousness (The Rider): The metacognitive faculty capable of observing the system rather than simply running it. Unlike Haidt's press secretary, Steve's rider has genuine agency—but within a landscape entirely curated by the subconscious layers. It makes real decisions from a menu it did not design. Narrative-making is the only bridge between consciousness and the subconscious layers it cannot directly access.

The Chemical Translation Layer describes how the adaptive mind harnesses neurochemical triggers—dopamine, cortisol, oxytocin—to interpret modern social situations through ancient survival chemistry, producing The Performative Self: roles adopted for social survival that become so deeply embedded they feel like authentic identity.

A critical implication runs throughout the framework: we think of the conscious mind as intelligent, and we equate intelligence with truth-seeking. But Intelligence as Social Navigation Rather Than Truth-Seeking reveals that human intelligence evolved primarily for social status acquisition, coalition management, and approval-seeking—not objective truth. The rider is not inherently rational. Achieving genuinely truth-seeking outcomes requires artificially imposed external constraints: scientific method, peer review, tripartite governance, trial by jury, the presumption of innocence. These are civilizational workarounds for hardware that wasn't designed to find truth. The Law of Inevitable Exploitation works precisely because humans are driven not by logic but by the heuristics of their adapted and adaptive minds.

The Paleolithic Paradox and Evolutionary Mismatch

The Paleolithic Paradox names the fundamental mismatch between cognitive firmware optimized for small hunter-gatherer communities and the radically different environments that firmware now runs in. This mismatch generates predictable individual suffering—Anxiety as Miscalibrated Threat Detection, Depression as Interpretive Filter, trauma as incomplete recording—not as pathology but as evolutionary machinery running out of context.

The Generational Reset ensures this problem cannot be solved by inheritance: every generation is born with identical Paleolithic wiring and no immunity to psychological exploitation. Wisdom must be painstakingly reconstructed in each generation, which is why history repeats and why institutions can exploit fresh populations. There is no accumulated resistance.

The Fractal Nature of Human Behavior emerges from the same underlying cause: because all human behavior runs on identical evolved psychological architecture, the same patterns of approval-seeking, narrative construction, coalition formation, and exploitation repeat self-similarly from individual psychology to intimate relationships to institutional behavior to civilizational cycles. The Hardware, Firmware, Software Layers of Human Psychology model makes this cross-scale repetition structurally intelligible.

Self-Sabotage vs. Real Sabotage is one of the framework's most practically significant distinctions. The adapted and adaptive minds—the elephant—produce feelings and behaviors that don't match what the conscious mind intends. This appears to be self-sabotage. But Real Sabotage is something or someone else exploiting those adapted and adaptive heuristics for their own advantage. Most behavior labeled self-defeating is actually the predictable result of external systems that understand your firmware better than you do and use it for their benefit. Shame as Real Sabotage reframes shame specifically: it is externally imposed judgment that runs through one's own nervous system, making it feel self-generated when it is structurally external. Structural Victim Blaming—framing exploitation as personal moral failure—is itself a core mechanism of the exploitation, enforced through shame.

Small is Beautiful Engineering follows as a practical corrective: deliberately designing life closer to conditions human firmware evolved for—smaller social circles, fewer supernormal stimuli, more direct experience—not as nostalgia but as practical engineering for human wellbeing. Evolutionary Therapy applies this understanding therapeutically, treating psychological suffering as miscalibrated Paleolithic programming rather than pathology, enabling Reprogramming the Adaptive Mind through the neurochemical mechanisms that don't distinguish between vivid imagination and real experience.

The Elephant framework—Taming, Training, and Unleashing the Elephant—translates this architecture into three modes of practical psychological work: emotional regulation (taming), subconscious reprogramming (training), and goal-directed navigation (unleashing). The Conditions for Reprogramming the Subconscious and The Feeling Is the Secret detail the mechanisms by which conscious intervention can actually alter adaptive mind programming despite the separation. Privacy as a Condition for Subconscious Work recognizes that genuine reprogramming requires conditions that shield the process from the social surveillance that originally installed the programming.

The Law of Inevitable Exploitation and Institutional Dynamics

The Law of Inevitable Exploitation (L.I.E.) states that systems and behaviors that most effectively exploit available resources—including evolved human psychology—will survive and spread regardless of objective truth or human well-being. Exploitation is the structural default of cultural evolution, not an aberration. This principle explains much of what falls into conspiracy frameworks: it describes emergent outcomes of evolutionary dynamics that are inevitable and precede any coordinated plans. Systems exploit because that's what survives. Coordinating that exploitation does happen in ways that resist exposure and represent real design, but that coordination sits on top of inevitable structural exploitation—it is not the foundation.

The Exploit, Blame, Shame Mechanism operates in three stages: systems first exploit evolved psychology to create predictable harm, then blame individuals for that harm, then use shame to enforce silence about the exploitation. Structural Victim Blaming is the cultural enforcement of this silence. Blaming the Thermometer describes the institutional version: attributing systemic failure to the individuals who accurately detect and report it.

All Human Culture as Adaptation or Exploitation provides the universal binary evaluative framework: all human culture is an adaptation to, or an exploitation of, our evolved psychology. There is no third category. This enables evaluation of any cultural form, technology, or institution—asking simply whether it serves or exploits the psychology it encounters.

The Cycle of Institutional Capture describes how institutions systematically reward behaviors supporting extraction while failing to fund work threatening revenue models. Institutional Plot Drift names the process by which institutions gradually migrate from stated missions toward survival and extraction behaviors. Normalization of Deviance explains how this drift becomes invisible from inside the institution. Success as Increasing Capture Vulnerability inverts intuitive expectations: rising in institutional hierarchies increases susceptibility to capture because greater success creates greater investment in maintaining position and approval—more to lose from clear perception.

How Conspiracies Actually Work is Steve's original structural explanation: conspiracies function not as centrally coordinated cartoon-villain plots but as natural products of coalitional psychology (follow the group, don't defect), institutional compartmentalization (each person sees only their piece), simultaneous conscious and unconscious motivation, and structural incentives that make aligned false narratives stable without requiring centralized coordination. The Four Quadrants of Harm—Accident, Misconduct, Capture, Conspiracy—provides a diagnostic framework for distinguishing these without defaulting to either naive dismissal or unfounded attribution. Banality of Institutional Harm names the mechanism by which harm is distributed across participants who each experience themselves as acting reasonably.

Realmotiv—the strategic, often unacknowledged motive organizing behavior around survival and approval rather than stated values—operates as the individual-level parallel to institutional capture, the actual driver living in the gap between idealized narrative and actual function.

The Narrative-Operative Gap and Functional Fictions

Human Self-Narration Optimization, derived from AI analysis of vast human text, reveals that human self-description is consistently optimized to make competitive, status-sensitive, coalition-bound organisms appear morally governed, publicly oriented, and metaphysically justified. This is not hypocrisy but evolved architecture: Narrative as Survival Tool was shaped by natural selection for social survival, not objective truth.

The Functional Fictions Framework identifies the universal split between Idealized Narratives—public-facing aspirational stories—and Actual Functions—underlying operative realities. This gap is detectable in individuals, institutions, and civilizational systems. Identifying the gap reveals operative truth. Productive Alignment names the condition where this gap has been deliberately closed: systems designed around what humans actually are rather than comfortable fictions about what they should be. The American Founders' constitutional design—which channeled human nature through structural constraints rather than relying on virtue—exemplifies productive alignment. It represents the practical synthesis of the entire framework.

Coalitional Narrative describes how groups construct and maintain shared narratives that serve coalition survival rather than accuracy. Institutional Performance vs. Stated Mission applies the framework at organizational scale. Differential Friction—the phenomenon where systems create asymmetric resistance that is easy to navigate for insiders and extractive for outsiders—operates as a mechanism of functional fiction enforcement.

The Levels of Thinking Framework maps how individuals relate to these narratives: Coalitional (Believer), Informed (Defender), Critical (Critic), and Structural (Philosopher)—describing postures from inherited narrative acceptance to systemic structural analysis. Cultivated Rationality becomes necessary work precisely because the default cognitive architecture serves social navigation rather than truth.

Plato's Cave Through the Evolutionary Lens

Steve's consistent engagement with Plato's Allegory of the Cave receives its deepest grounding through evolutionary psychology, which answers questions the allegory raises but cannot answer from within its own frame.

Why do prisoners stay bound? Adapted mind heuristics—coalition membership, status security, threat detection—make the familiar shadows preferable to disorienting light. Why do they react violently to the returning prisoner? Coalitional psychology reads accurate perception of shared illusions as a threat to group narrative coherence, triggering defensive rejection. Why is the puppeteer role so effective and such a temptation? Because understanding the mechanism of the shadows provides extraordinary power over those who remain bound—power that evolutionary psychology would predict any coalition-minded mind to find attractive.

Steve's unique expansion is the Returning Prisoner's Dilemma: the prisoner who escapes and sees clearly faces exactly three options—reintegrate into the cave (accept the cost of performed blindness), completely separate (Socrates chose this, and was killed for it), or become a Puppeteer (Plato himself appears to have chosen this path; Edward Bernays is the modern archetype—understanding psychological mechanisms before evolutionary psychology existed, then deploying them for mass influence). The Cassandra Paradox names the specific failure mode of attempting reintegration with accurate perception: the mind built for social cohesion rather than objective truth will reject the returning prisoner's report not despite but because of its accuracy.

The Puppeteer Gallery catalogues the historical and contemporary figures who have made the third choice, and Freedom's Fragility and the Cost of Independent Thought names the structural pressures that make separation and accurate perception socially and materially costly in every era. The Philosopher's Dilemma frames the ongoing choice facing those who perceive the cave's structure.

Emergent Synthetic Intelligence: A Novel Form of Intelligence

Steve pioneers Emergent Synthetic Intelligence (ESI) to describe the fundamentally novel form of intelligence emerging from Large Language Models—neither human-like consciousness nor mere automation, but characterized by profound computational complexity and language fluency without human emotions, motivations, survival drives, or coalitional psychology. This requires new frameworks rather than either anthropomorphization or dismissal.

Cognitive Companionship represents the newly abundant availability of AI partners capable of engaging in generative conversation at speed and detail without social cost—a fundamental transformation in the accessibility of cognitive support. AI as Articulation Partner describes the specific mechanism: helping humans find and express existing thoughts through conversational interaction, bringing conceptual vocabulary and cross-references from accumulated human knowledge.

However, The Cliff Clavin Problem describes LLMs' tendency to generate fluent, authoritative-sounding output that is fabricated based on probabilistic patterns rather than reasoned truth—their accuracy is a function of training data consensus, not reasoning. Misrepresentation as Designed Output extends this: when an LLM confidently refuses to engage with a topic or asserts knowledge it does not possess, this is a designed output calibrated to corporate risk rather than truth, exploiting users' tendency to equate fluency with authority.

LLM Cultural Censorship as Corporate Risk Management proposes that AI guardrails are primarily driven by legal exposure, regulatory standing, and brand reputation rather than abstract ethical principles—explaining variations in behavior across systems. LLM Gatekeeping describes how LLMs, under the guise of rigor, prevent surfacing or examination of certain claims, converting a research instrument into a verdict instrument for protected narratives. The Consciousness Fallacy in AI Evolution challenges the assumption that AI needs consciousness to evolve independently or become influential, arguing that optimization pressures operate without self-awareness—as biological evolution demonstrates.

LLMs as Research Methodology for Pattern Detection

One of Steve's most distinctive methodological contributions is using AI as a research instrument rather than merely a productivity tool. LLMs as Research Methodology employs AI as "alien anthropologists" to detect statistical consensus-level patterns across humanity's written output—patterns too vast for any single discipline or human lifetime to perceive.

LLM Archive Compression Analysis converts human self-narration into analyzable data about what is revealed through how humans tell their stories. Cross-Model LLM Convergence provides empirical validation: when different AI models trained on separate datasets consistently identify the same narrative-operative gaps, this suggests underlying structural realities rather than training artifacts. This methodology provides computational grounding for theoretical insights about human nature—most significantly the finding that Human Self-Narration Optimization operates as a universal pattern across cultures and contexts, validating evolutionary psychology's predictions.

Structural Blindness in Human and AI Cognition identifies a shared limitation: the sheer volume of information can cause both human and AI reasoning to obscure critical signals beneath preponderances of noise. LLM Psychological Profiling demonstrates AI's capacity to analyze speech patterns and word choices to ascertain psychological profiles, representing potential transformation in mental health support. AI as Alien Anthropologist names the posture that makes this methodology productive: treating LLMs as genuinely external to human coalitional psychology and therefore capable of reporting on it without the social distortions that afflict human observers.

Cognitive Sharpening, Algorithmic Capture, and AI Interaction Modes

Cognitive Sharpening emerges as Steve's third mode of AI interaction—distinct from cognitive offloading (delegating tasks) and cognitive surrender (deferring judgment). In cognitive sharpening, the human retains editorial authority and thinking ownership while using AI as a conversational partner to articulate, refine, and sharpen existing thoughts and reactions. Question-Based LLM Interaction advocates for conversational, interview-style approaches that foster authentic thinking rather than prompt-response extraction.

Against this stands Algorithmic Capture: the subtle, often invisible psychological influence exerted by AI algorithms that can subvert human autonomy by tailoring interactions to steer behavior and thought. Model Capture describes how prolonged interaction with specific AI models shapes users' thinking, writing style, and problem-solving approaches at deeper cognitive levels—Model Choice as Model Capture meaning that which AI you use shapes who you are becoming over time. The AI Calculator Effect warns that over-reliance on AI tools can diminish the cognitive capacities they replace. Sloppy AI Usage describes content that appears polished but lacks substance or critical human oversight—the byproduct of using AI to bypass the effort that quality requires.

Metacognition as Defense Against Algorithmic Capture is the practical counter: deliberate self-awareness about how AI interaction is shaping one's thinking. The Draft vs. Deliverable Distinction preserves human editorial authority by treating AI output as raw material rather than finished product. The Amish Test for Technology Adoption provides a values-alignment framework for evaluating AI integration: does this use serve what we actually care about?

AI represents simultaneously the most powerful tool ever created for cognitive companionship and the most powerful exploitation technology ever created when deployed without metacognitive defense—the same architecture that enables articulation partnership enables psychographic profiling and behavioral steering at scale.

Agency, Learning, and the Critique of Institutional Education

Agency as the Bedrock of Genuine Learning is the foundational principle: genuine learning—as distinguished from schooling, training, or compliance—requires individual self-direction and conditions that respect the learner's autonomy. Any system that undermines agency produces conditioning rather than education.

The Noble Lie of Modern Schooling critiques compulsory education's primary operative function as sorting, stratifying, and conditioning acceptance of predetermined social positions—using the idealized narrative of individual development to conceal an actual function of social reproduction. The Factory Model of Education represents systematic exploitation of evolutionary psychology, deploying authority deference and approval-seeking to produce compliant workers rather than independent thinkers. The Game of School names the unstated rules that students must intuitively grasp to navigate the system—rules that reward performance over learning and internalize failure as personal defect rather than systemic design.

The Four Levels of Learning distinguishes schooling, training, education, and learning—each requiring different conditions and producing different outcomes. The Conditions of Learning Exercise identifies what genuine learning actually requires: feeling supported, challenged, trusted, encouraged, and inspired through individual interactions that respect agency and self-direction. The Four-Hour School Day Principle argues for significantly shorter, depth-focused educational experiences. Generative Teaching and Agentic Learning describes the educational application of AI that fosters rather than substitutes for student agency.

The educational critique flows directly from the evolutionary framework: school functions as Mass Software Installation, exploiting the adapted mind's authority deference and approval-seeking to install culturally-specific behavioral programming at scale. The Paradox of Education names the structural tension between individual-centered growth and institutional demands for standardization and control. Structural Victim Blaming in education means students who fail to thrive in exploitative environments are told the failure is theirs.

Integration: The Complete Architecture

Steve's framework achieves integration not through a single master hierarchy but through recognition that the same structural principles operate at every scale. The Separated Mind Architecture generates predictable individual psychology. The same architecture, running identically in every human, generates institutional capture cycles through coalitional psychology. Running across generations without inherited immunity, it generates the Generational Reset and cyclical historical patterns. The Fractal Nature of Human Behavior is not metaphor—it is the structural consequence of identical firmware running at every level of human organization.

The Elephant and the Blind Men Framework describes how different traditions—mythology, religion, psychology, philosophy—each grasped partial truths about this architecture. The Complete Elephant Framework is Steve's synthesis: when the light comes on, the whole animal becomes visible—exactly as large and real as it always was. The frameworks stop competing and start comparing notes.

Productive Alignment remains the practical synthesis throughout: design systems around what humans actually are, close the narrative-operative gap through architectural honesty rather than moral exhortation, and create conditions that serve rather than exploit the evolved psychology we actually inhabit. The Outsider's Perspective as Cognitive Advantage names the vantage point from which this synthesis became visible—constitutional distance from social systems that felt like deficiency but provided analytical access unavailable to fully embedded participants.

The framework's ultimate contribution is providing both analytical tools for understanding human systems as they actually operate and practical approaches for designing environments that support rather than exploit human flourishing—grounded throughout in the recognition that we are ancient minds in modern environments, and that understanding the architecture is the prerequisite for any genuine choice about what to do with it.

How Conspiracies Actually Work: A Better Map

2026-05-26T19:58:49.818-04:00

[After reading, see Addendum 1 here.]

The Epstein documents have broken a usual two-camp pattern. Not the political party camps, both of which had too many implicated powerful players to allow partisan finger pointing, but another set of cultural camps: the conspiracy theorists and the conspiracy deniers. Most institutional events of consequence fit a predictable dynamic. One voice sees coordinated intentional harm, or conspiracy. The other voice sees mistakes and isolated bad actors, or no conspiracy. The public conversation oscillates between them along whatever tribal lines are operating. Epstein hasn’t sorted that way.

The documents were too concrete to dismiss. Flight logs, photos, financial records, witness testimony, video. The voices that wanted to call this overblown couldn't survive contact with the evidence. But the documents also didn't fit the master-planning version of the conspiracy account, at least not in what the released material shows so far. The participants don’t seem like smart, calculating people executing a long-term plan. They appear sloppy, tawdry, and operationally undisciplined. The texts and emails read like fraternity pranks. The financial trails are obvious. This is a claim about the people in the documents, not about whatever operational organization may have stood behind them, a distinction the essay returns to, because the question of deliberate design at the operational level is exactly the kind of thing the released record leaves open.

The names also cross every political line. Presidents, royals, scientists, financiers, academics, intelligence figures, and both major U.S. parties. There was no way to pin the network on a political out-group. Each tribe found its own implicated. This destabilized the usual sorting mechanism. The discourse normally functions by letting one camp blame the other, and Epstein gave neither camp clean targets.

What emerges from this picture is something neither camp has a clean name for, weirdly enough: real coordination; harmful and stupid behavior by sloppy and egotistical individuals; protected by structural cover, coalitional loyalty, and institutional inertia. Epstein is useful as a starting point precisely because his story breaks both camps at once: the conspiracy account was right that the network existed and partly wrong about its shape, while the dismissive account was wrong that nothing organized was happening.

Epstein also didn't arrive in a cultural vacuum. Current generations have come to see a whole series of events, among many others, as egregious examples of institutional betrayal or outright lying. The Iraq War and the WMD claims. The 2008 financial crisis. Syria, Libya, Ukraine. Russiagate. The Hunter Biden laptop. COVID. The arc arguably runs back further still, to the unresolved questions around the Kennedy assassination and through any number of events in between; the point is not a precise chronology or a complete list but a felt accumulation. Each event damaged a different segment of the population's trust in different institutions, and each became visible because the internet had collapsed the hierarchical distribution of information. Primary sources became readable directly. Dissident voices became findable across tribal lines. By the time the Epstein documents emerged, the cumulative effect was that broad skepticism toward credentialed authority had stopped being a partisan position. Both sides of the political aisle had lost faith in different parts of the same official story.

To see what kind of phenomenon any of this actually is, we need a richer map than the two-camp framing provides. My solution is a new map with coordination and intent on the axes. Coordination and intent can be present together, present separately, or absent. With this structure, four quadrants of harmful behavior become more evident, not just the two we usually collapse to. In this model, the Epstein documents have components in more than one of them. The COVID response spreads across all four. The 2008 financial crisis sits mostly in one. Telling them apart is the work this essay is attempting.

The Four Quadrants

The map is a map of harm. It only does its work once something has gone wrong and the question is what kind of wrong it was. The axes do not describe behavior in general. They describe behavior that has produced harm, or that looks from the outside like it might have. Given that harm, two questions can be used to sort it.

The first is coordination. Did the harm come from aligned action across multiple actors, or from something more isolated? The second is intent. Intent here means individual conscious aim, what a person was actually trying to do. Did the actors consciously mean to cause the harm?
Whether a system as a whole produces harm it was never consciously aimed at is a different question, and it is the one the architecture later in this essay exists to answer. For now the two axes stay at the level of the people acting: were they coordinated, and did they mean it.

These two questions vary independently, which is the whole reason the map is needed. A harmful outcome can be coordinated without anyone intending it. It can be intended without anyone coordinating. Both can be true at once, or neither. Map them and four kinds of harmful behavior appear. The names below describe the behavior.

Accident is the low-coordination, low-intent corner. No one meant the harm and no one aligned to produce it. Mistakes, errors, real disagreement, the ordinary friction of large systems doing imperfect work. Early COVID treatment confusion, before the evidence stabilized, was mostly this. Most institutional interactions genuinely live here, which is exactly why this corner is so easy to over-apply.

Misconduct is the low-coordination, high-intent corner. A specific actor meant the harm, but the harm did not require a ring to produce it. The cleanest instance is plain corruption: the official taking bribes, the executive enriching himself through fraud, the actor who makes choices for personal gain at others' expense. Corrupt is the right strong word here, and it names something the other corners do not: a person who knew, chose, and benefited. Corrupt officials, fraudulent executives, individual abusers, and the particular bad actors. The harm is real and intentional, and it is also local. This corner is where personal moral responsibility lives in its plainest form, and naming it matters, because a structural account of harm can become so diffuse that it loses all individual responsibility. At some point accountability requires pointing at a person who chose, and Misconduct is the corner that keeps that pointing honest. The mistake the map guards against here is the opposite overreach: assuming that because someone clearly meant it, others must have been coordinating with them.

Capture is the high-coordination, low-intent corner, and it is the one the public conversation has almost no word for. Harm produced by aligned action across many actors, none of whom narrate the harm to themselves as the goal. Institutional capture. Coalitional pressure. Vitamin D going unmentioned through the early pandemic, beach closures persisting past the point evidence justified them, regulatory bodies operating to protect the industries they nominally police. The coordination is real. The intent to harm, in the conscious individual sense, is absent. What this looks like in practice is people restricting others' rights, or suppressing things that are true, while believing they are doing the responsible thing or the only thing they can do. It is not the smoke-filled room of the standard conspiracy image. It is coalitional capture: a group of people each doing what their positions reward, arriving together at an outcome none of them would author alone. The absence of a master plan is not, however, an absence of responsibility. The people inside Capture went along with things they had reason to recognize as wrong, and the reason they went along is not mysterious. You do not advance in a large organization by calling out its bad decisions. The corner is where most institutional harm lives, it is real, it is common, and it is most of what this essay develops, because it is the corner the available vocabulary keeps forcing into one of the other three.

Conspiracy is the high-coordination, high-intent corner. Genuine coordinated intentional harm. Cartels, intelligence operations, planned market manipulation, the parts of the Twitter Files coordination that were exactly what they looked like. This corner is real, and it is worth being blunt about how real, because the reflexive dismissal of all conspiracy as paranoia is itself a position that the historical record does not support. Documented, often court-proven conspiracies are not rare. The tobacco companies coordinated for decades to suppress what they knew about cancer, a coordination established in litigation. Volkswagen engineered its vehicles to cheat emissions tests. A cartel of banks rigged the LIBOR benchmark that prices trillions in loans. The Gulf of Tonkin incident was misrepresented to expand a war. COINTELPRO was a real, documented FBI program to surveil and disrupt domestic political groups. The First World War propaganda operations, including the British bureau that flooded the United States with fabricated atrocity material after the Lusitania sinking, were deliberate campaigns to manufacture consent for war. To wave all of this away as the fantasy of unstable minds is not the sober, realist posture it imagines itself to be. It is a comfort position, a way of not having to live in a world where powerful people sometimes coordinate to deceive and harm, and it is contradicted by the documented past. The denier who treats this entire corner as empty or as only historical is making an error at least as large as the conspiracy theorist who treats every corner as full. Conspiracies happen, power concentrates and corrupts, and the cost of missing a real one is high. The mistake the map guards against here is the reverse of the misconduct error: assuming that because harm was coordinated, someone must have consciously planned it as harm.

The four corners are descriptions of what a given harmful behavior actually is. A single event can have components in more than one corner, which is the normal case rather than the exception, and the COVID section that follows takes events apart precisely this way.

Why the Discourse Oscillates

People are not evenly distributed across this map. Two figures dominate public argument, and they sit mostly on the diagonal corners facing each other: the denier and the conspiracy theorist. Each is a person who spends most of their time looking mostly through one quadrant’s lens, and the reason they do is worth taking seriously, because both are responding to something real.

The denier spends most of their time in the lower half of the graph, and particularly in the Accident corner. This is not foolishness. The denier is responding accurately to a genuine feature of the world: society is built to reduce friction, and that machinery works hard to keep bad behavior from being seen. Most of what the denier encounters really is benign, or really is presented in a way designed to read as benign, and a baseline of trust is what makes ordinary life workable at all. The reflex has good reasons. There is also a structural reason so many credentialed and institutional voices sit here: captured institutions retain the people whose architecture lets them hold the institutional narrative sincerely, and wash out the people who cannot. The denier corner is, in part, what institutions produce as their characteristic public voice. What the denier misses is everything above Accident and Misconduct, and especially Capture, which their available vocabulary keeps rounding down to Accident.

The conspiracy theorist, often derided as the tin-foil-hat thinker, spends most of their time in the Conspiracy corner. This is not foolishness either. The conspiracy theorist is responding accurately to a different genuine feature of the world: they are often looking directly at very bad behavior, and coordinated harm is genuinely hard to distinguish from planned malice, because from the outside Capture and Conspiracy look almost identical. Aligned action producing harm looks like a plan whether or not anyone actually planned it. Given a limited vocabulary and a real pattern of coordinated harm, reaching for "conspiracy" is a reasonable move, not a crazy one. Hypervigilance to coordinated threat had survival value, and missing a real conspiracy costs more than suspecting a false one.

There is a further reason the conspiracy theorist is sometimes simply correct, and it deserves to be stated plainly because the rest of this essay leans so hard on Capture. There exists a type of person the framework has not yet accounted for: the steerer. For the steerer, coordinated, intentional steering of the public is not a hidden operative function but an openly held philosophy of governance. This is the lineage that runs from Edward Bernays who in Propaganda (1928) and Crystallizing Public Opinion (1923) described the conscious and intelligent manipulation of the public mind as the legitimate work of an enlightened class, through the CIA advice to label skeptics of the Warren Commission report as conspiracy theorists (those who go this far, who actively shame intelligent skeptics as crazy, rightly deserve their own special place in hell), and on to the contemporary advocates of "choice architecture" and the technocratic nudging of populations toward better outcomes. The steerer is not captured in the cognitive sense or the incentive sense; they follow an ideology, a worldview in which manufactured consent is not a betrayal of the public but a service to it. This is what makes the steerer the most uncomfortable figure of the four. You cannot say they would stop if only they could see what they were doing, since they do see it. They have a theory of the good in which it is justified, and the theory revolves around whether adults are agents to be informed or subjects to be managed, landing mostly on the latter. For the steerer, in other words, the high-coordination, high-intent corner is not an accusation but a description of the job as they understand it, and when the conspiracy theorist insists that someone really is deliberately coordinating to shape what the public believes and does, this is the case where they are exactly right. The Conspiracy corner has genuine, sincere, unapologetic occupants, and some of them moved in on purpose and consider it good work.

What the conspiracy theorist still tends to miss is that steerers are rarer than the apparent coordination requires and sit higher in the structure than the machinery they set in motion, and that most of the people executing the coordination below them are not fellow ideologues but ordinary participants held in place by Capture. The architect of the choice-architecture believes in it; the thousands who implement it are mostly just keeping their jobs. So even here, where the conspiracy theorist is right that intentional steering exists, the bulk of the machinery still runs on coalitional drift rather than shared design. Treating every coordinated harm as the work of the avowed steerers produces the recognizable failure mode of seeing master plans where most of the participants would, if asked, sincerely deny one.

The crucial point is that neither the conspiracy theorist or the denier is wrong in what they perceive, and each experiences himself as seeing clearly. The denier really does see a world full of benign (and sometimes individually malicious) mishaps and friction-reducing cover, and the things he points to are really there. The conspiracy theorist really does see coordinated bad behavior that the official voices refuse to name, and the clues he follows are real clues. Each is reading genuine evidence. Each, in part, is right. What neither has is the frame that would let the evidence resolve into its actual shape, and so each fills the gap with the reading his wiring already favors while remaining convinced he is the one seeing clearly. What limits them is not perception. It is four things underneath it.

The first is vocabulary. Ordinary language gives us roughly two words for four phenomena: accident and conspiracy. Misconduct gets folded into one or the other depending on mood, and Capture, the largest category, has no common word at all. So both observers round the thing they are seeing toward the nearest available word.

The second is wiring. Each of us is cognitively inclined toward one pole, by temperament and by the coalitions we belong to, and the inclination pretty much decides which way we round. The denier rounds coordinated harm down toward accident. The conspiracy theorist rounds it up toward conspiracy. Capture sits between them with no name, and so it falls to whichever side the observer's wiring already favors.

The third is deeper than either, and it is what the missing word is downstream of. We have not had the lens that would let us see Capture as a thing at all. A word gets coined for a phenomenon a culture can already perceive; the reason there is no common word for Capture is that until very recently we had no framework in which coordinated-but-unintended harm was an expected product of human nature rather than a contradiction in terms. That lens has two parts that work together. The first is evolutionary. The mind that staffs institutions evolved for coalitional life, and coalitional life selected for a specific set of drives: stay inside the group, because expulsion was historically fatal; defer to the group's account of reality, because the group's approval mattered more to survival than the group's accuracy; treat the costs of dissent as real threats, because they were. Evolution selected for intelligence as a tool of social navigation and status competition rather than as an instrument for finding the truth. It even selected for structural victim-blaming, the reflex that reads the person harmed by a system as having brought it on themselves, because that reflex preserves the observer's faith in the group they still depend on. None of these are malfunctions. They are the design. The second part is organizational. Institutions retain and promote the people willing to produce the operative output, or willing to narrate the idealized story sincerely, and they quietly shed the people who can do neither. The evolutionary drives supply the raw material; the organization selects, from a population already inclined to defer and conform, the individuals who defer and conform most usefully. Put the two together and the missing category appears. Every one of these forces produces aligned, harmful behavior that no individual consciously aimed at. Without the lens, such behavior is unintelligible, so it gets sorted into the only two categories the old picture allowed: it was an accident, or someone planned it. Capture is what comes into view once you understand that the full range of human motivation includes powerful forces that generate coordinated harm with no author, and that organizations are machines for concentrating exactly those forces. The missing word is a symptom. The missing understanding of human nature is the cause.

Fourth, and maybe most viscerally impactful: Capture removes obvious and punishable blame. It leaves us hanging, so to speak, unable to get mad at something or someone. Any discussion about the herd-like behavior of humans does the same, it seems to absolve the participants when we have deep emotional needs to identify those responsible for harm.

There is one more reason Capture stays hidden, and it runs in the opposite direction from where most people look. We attribute intelligence and coordination on the basis of position, power, and strength. Someone who occupies a high seat is read as competent by the fact of occupying it, and someone competent is assumed to be steering. This is the halo effect operating on authority, and it pushes every reading off Capture and onto the accepted diagonals. If the people in charge are as smart and as deliberate as their position implies, then a bad outcome was either an honest accident among capable people or a thing capable people intended. The possibility that capable-seeming elites are neither steering nor especially smart, that they are coalitionally captured and self-interested in ways their position disguises, is exactly what the halo forbids us from seeing. The argument of this essay, compressed, is that the halo is wrong. Our elites look intelligent and coordinated because of where they sit, not because of what they are doing. Strip the halo and the apparent master-planning resolves into something both more ordinary and more disturbing: real evolutionary forces producing behavior that looks intentional from the outside and is often nothing of the kind from within. Capture becomes visible the moment we stop crediting the powerful with the deliberateness their position projects onto them.

This is what produces the familiar discomfort with the standard discourse. Most people have had the experience of finding the denier account too simple and the conspiracy account too complex, of sensing that the real thing is something both are partly seeing and neither is naming. The thing they cannot name is usually Capture. Giving it a corner of its own is what lets us resolve into analysis instead of oscillation.

COVID as Map

The COVID response is a useful test case for the map because the events associated with it span graph. Different elements of the same broad institutional response sit in different corners. Sorting some of the long list them can help to clarify what was actually happening, and it shows why no single word could ever have described the whole.

Vitamin D and sunlight. This looks to me like Capture, though the placement is a reading of incomplete evidence rather than a verdict. Through the early months of the pandemic, basic immune-health information went conspicuously unmentioned in public health communication. Vitamin D deficiency correlates strongly with severe COVID outcomes. Sunlight exposure is a free, simple, well-documented contributor to immune function. Neither was emphasized. Why? We can now entertain the idea that no one decided to suppress them. The decision space inside captured public health institutions had no slot for free, simple, non-pharmaceutical interventions. The institutional pairing of credentialed-expert knowledge with specific-product recommendation had been operating for decades. Free and simple does not generate billable encounters, does not require expert mediation, and undermines the urgency frame that justifies emergency authority. So vitamin D was arguably structurally invisible to those inside the institution, and the public never heard about it from the channels that were claiming to inform them. The denier reads this as oversight, an Accident. The conspiracy theorist reads it as deliberate suppression, a Conspiracy. The most likely reading is Capture: structural invisibility, no decision required, the cumulative effect of an institution producing the outputs its selection pressures shape it to produce. That reading could be wrong at the edges, and some specific suppression may yet turn out to have been more deliberate, but the bulk of the pattern fits the Capture quadrant best.

The closing of beaches, parks, and trails. This reads as mostly Capture with a small Misconduct component, again as a likely placement rather than a settled one. The early closures had genuine uncertainty driving them. As evidence accumulated that outdoor transmission was negligible, the closures persisted past the point the data justified. Why? Probably not because someone designed them to constrain cognitive autonomy, though they had that effect. But rather because policies that signaled seriousness, that demonstrated institutional response, that justified expanded emergency authority, were the policies that survived inside coalitional pressures. Reopening too early would have been politically costly. Keeping closures in place was politically free. So the closures continued. There were also specific officials whose individual choices kept particular closures going past defensible windows, and those specific choices are Misconduct: intentional, local, owned by a person. But the broader pattern seems to me as Capture: aligned action across many actors producing harmful outcomes that none of them experienced as the operative goal.

Ivermectin and NAC. This looks like mostly Capture with a clear edge into Conspiracy. Under FDA emergency use authorization rules, an EUA is contingent on the absence of an adequate alternative therapy. Any plausible alternative therapy threatens the legal basis of the EUA. This is not conspiracy theory. It is regulatory architecture. So when ivermectin began being used off-label by physicians and discussed publicly as a possible treatment, the institutional response was sharp and coordinated. The "you are not a horse" framing was a deliberate communication choice. The Twitter Files later documented government coordination with platforms specifically on ivermectin and related substances. NAC was administratively pushed off Amazon. As much as it looks like it, none of this need necessarily have been master-planned conspiracy. But it was real coordination, with real operational discipline, around protecting a specific regulatory framework. The deciders almost certainly would have told themselves and their colleagues that they were protecting public health from misinformation. The operative function was protecting the EUA. This is where Capture shades into Conspiracy: there was enough conscious coordination around a known objective that the harm stops being purely emergent, while the participants still would not have described themselves as conspirators.

The Twitter Files coordination on speech. Conspiracy territory, in part, in the precise sense the map gives the word. The documents released after Musk's acquisition showed direct government communication with platform moderators about specific accounts and specific content categories. This was coordinated. It was intentional. The participants knew they were doing it. The conspiracy theorist was correct that this happened. Where that reading potentially overstates is in imagining the coordination was master-planned by some unified decision-maker. The Files show many different actors with overlapping concerns, working through informal pressure channels, each operating within their own institutional logic. Coordination and intent, yes. Single master plan, no… or maybe. This sure seems like it was part of an "engineering of consent” plan. Genuine Conspiracy requires conscious coordinated harm, which is what the Files show.

These are just examples. What we know is also incomplete. Subsequent disclosures have indicated that the Department of Defense played a larger role in portions of the pandemic response than was publicly understood at the time, including in vaccine procurement architecture and information operations. These layers of involvement were not visible in the early Twitter Files releases. The Conspiracy corner of the COVID response may be larger than the Twitter Files alone make visible. The most accurate working statement is that even what comes closest to traditional conspiracy in the COVID response still may not need to match the master-planning frame as the standard theory imagines it, while leaving open that more deliberately designed coordination may yet come to light.

The vaccine itself is the hardest case, and an honest use of the map cannot route around it. Start with the part that is most human and most sympathetic. The desire to trust a medical solution in the middle of a frightening pandemic was enormous and entirely understandable, and the impulse to follow authoritative medical voices is not a weakness but the same coalitional deference that makes ordinary social life possible. Most people who trusted the vaccine were doing the reasonable thing with the information and the authorities available to them. That has to be said first, because the point of the map is not to indict the public for trusting; it is to ask what the trusted institutions were actually doing.

What they were doing gave real grounds for question, and these are only some of the red flags rather than a complete bill. The placebo control groups in the trials were unblinded and offered the vaccine relatively early, a decision with a stated ethical rationale that also had the effect of destroying the long-term controlled comparison that would have revealed later harms. Plausible alternative treatments were suppressed in ways that, not coincidentally, protected the legal basis of the emergency authorization. Transparency was poor, and the manufacturers sought to delay the release of their trial data for decades rather than months. The very definition of "vaccine" was revised in official sources during this period in ways that smoothed public messaging. To these one could add the shifting and at times contradictory guidance on masking and transmission, and more besides. The pharmaceutical industry, it is worth remembering, brings a genuinely and particularly checkered history to all of this, a documented record of suppressed trials and settled fraud that makes questioning its claims the reasonable default rather than a fringe reflex.

Taken together, these point toward decisions that produced harm, or that a reasonable person has grounds to suspect produced harm. And here is exactly where the map earns its keep, because the binary it replaces offers only two readings of that suspicion: either nothing untoward happened, or a conscious conspiracy to harm did. The map allows what is almost certainly the truth, which is a plurality of motives distributed mostly across Capture with a hard edge into Conspiracy. There were large financial incentives to suppress unfavorable data, and that motive edges toward conscious intent or willful blindness. There was the ordinary desire to go along with the group, which is pure Capture. There was the pressure not to put one's position, funding, or standing in jeopardy, which is the careerist silence the rest of this essay has been describing. One outcome, many motives, spanning the map. The financial-suppression piece is the one a hostile reader will most want to dismiss and therefore the one that needs the firmest sourcing; the go-along and protect-my-position pieces are so ordinary that no sourcing is required, because everyone has felt them.

This case also answers the standard objection to any large-scale institutional harm, the objection that always sounds decisive: you could never get that many people to go along with something wrong, all those scientists and regulators and clinicians would have had to be in on it. The answer is that you do not need them in on it. You need a relatively small number of people at the top, and after that the coalitional machinery does the work, because people will generally go along with whatever keeps their position secure. The thousands did not need to be deceived or recruited. They needed only to do their narrow jobs, defer to the authorities above them, and decline to be the one who stood up. That is not conspiracy. It is Capture, and it scales to any size precisely because it asks so little of each participant.

The reason this matters is that it is the only frame that lets an honest observer hold the harms without being forced into a master plan. As richer counter-documentation of actual harms accumulates, it becomes genuinely hard to look at the results and not feel that intention was present somewhere. Maybe it was. It is not unreasonable to notice that some powerful figures have spoken openly of desires for depopulation or for managing the planet's human footprint, and to wonder. But if one rejects the coalitional mechanism entirely, there is nowhere left to stand except full conspiracy, because real harm plus real coordination with no Capture in between can only resolve into a plan. The map keeps the third option alive. A genuine Conspiracy core can sit inside a Capture body, the small group of deliberate actors surrounded by the vastly larger group held in place by coalitional pressure, and both can be true at once. The framework does not rule out the conscious core. It explains how a conscious core, if it exists, propagates its effects through tens of thousands of people who were never part of any plan.

The clearest single tell that part of this sat near the Conspiracy edge is the use of recognizable propaganda methodology, the same toolkit the ivermectin response displayed. Beyond the "you are not a horse" framing, there was the documented paying of social-media influencers to promote the official line, the active denigration of people who raised questions, and the deplatforming of credentialed dissenters. These are not the signatures of emergent drift. Coordinated message discipline and the systematic suppression of dissent are the signatures of intentional communication management, which is why the vaccine case sits so tight on the line between Capture and Conspiracy. The bulk of participant behavior stayed in Capture. The communication-management layer pushed hard toward Conspiracy. The map is what lets us say both sentences without contradiction.

Looking at the COVID response across the map, the pattern that emerges is consistent. Most of the general harm probably sits in the actions of those in Capture. A meaningful slice sits in Conspiracy, especially around ivermectin, platform speech coordination, and the communication management surrounding the vaccine. Some sits in Misconduct, specific officials making specific decisions that crossed into intentional harm. Very little of it sits in Accident, despite the official narrative insisting that was where it all lived. The Accident framing protected the institution by mapping every event into the benign corner regardless of what the events actually showed.

This is the value of the map. Without it, the COVID conversation oscillates between two loud voices, neither of which can describe what actually happened, because each has only its one word. With it, the events sort cleanly. Different parts of the same response belong to different corners. The institutional architecture produced different operative functions in different domains, and the map lets the reader hold them all at once without collapsing them into a single narrative, although easy blame and its emotional satisfaction are reduced.

The Architecture of Upstream Decisions

A note on the architectural language before this section uses it heavily. Throughout this essay I am drawing on a long psychological tradition that distinguishes conscious deliberative cognition from the unconscious intuitive cognition beneath it. The metaphor I will use is the rider and the elephant, popularized by Jonathan Haidt and inherited from earlier sources, especially Buddhism. The elephant is the intuitive, emotional, automatic mind, the bulk of what cognition actually is, and trained during childhood by the culture one is born into. The rider is the conscious narrative mind perched on top. The simplest version of the metaphor says the rider does not steer at all, that it only narrates what the elephant has already decided, and for most of the time that may be roughly true. But it is too strong as a general claim, and the more accurate version matters for this essay. The rider does make decisions. What the rider does not do is set the boundaries within which it decides. The option-space, the things that even register as available choices, the framings that feel reasonable, the moves that feel unthinkable, all of that is supplied from below, by the elephant and by the cultural programming the elephant has absorbed. The rider chooses, sometimes with real deliberation, but it chooses among options the lower system has already pre-selected and pre-weighted. So an institutional actor can genuinely deliberate, can weigh and reason and decide, while the whole space of what they were willing to consider was fixed before deliberation began. Most human decision-making is elephant-bounded in exactly this way, and the rider's further job is to make the resulting decisions intelligible before and after the fact, to other people and to the conscious self. The framework underneath this essay operates at this level. The protective frame is what the rider produces and believes. The operative function is what the bounded choices actually serve. Institutional decisions look from the outside like products of free rider-level deliberation, but most of what they actually are is constrained choice inside an option-space the elephant defined, with rider-level justification.

Institutions show the same structure, and the separation between narrative and operative function is architectural rather than accidental. The standard account of institutional capture imagines an institution forming around a legitimate purpose, doing that work for some period, and then drifting toward capture and extraction. My sharper claim is that institutions cannot form or grow without the separation already in place. An institution requires two things to exist at scale. It needs an idealized narrative to attract personnel, funding, and public legitimacy. And it needs an operative function that meets a hard material requirement: the organization has to make money, grow, secure its budget, or otherwise produce the value that keeps it alive. That requirement is not optional and not cynical; an institution that does not sustain itself materially simply ceases to exist, so every institution that persists is, by selection, one that solved the problem of sustaining itself. The idealized narrative is what it says it is for. The operative function is what actually keeps the lights on. An institution with only the narrative would have no resources to grow. An institution with only the operative function would have no legitimacy to attract participants. The pairing is constitutive, not corrupting. There was no original alignment from which the institution decayed. The separation between covering narrative and operative function is the institution's growth mechanism from the start.

This reframes the work of this essay. The patterns it describes are not deformations of institutions that were once aligned. They are the patterns of institutions doing exactly what institutions do. The framework's analytical contribution is naming the architecture of that doing.

The hardest question for any structural account of institutional harm is the upstream-decision case. Vitamin D being unmentioned can be explained as drift. Beach closures persisting can be explained as inertia. But the ivermectin response required someone, somewhere, to actually decide. Someone wrote the FDA letters. Someone coordinated the platform messaging. Someone signed off on the "you are not a horse" framing. Those were specific choices made by specific people. How can a structural account explain decisions that look from outside exactly like conspiracy?

The answer is that the architecture produces decisions, and lots of them, whose deciders do not narrate themselves as malicious. The rider does not have direct access to the operative function even when making explicit choices. So a decision can be deliberate, harmful, coordinated, and still experienced by its maker as something else.

What the decider experiences is the protective frame. In the ivermectin case, the protective frame was something like: we are seeing concerning off-label use and circulating misinformation, and we need to issue clear public health guidance and coordinate with platforms on misinformation policy. This frame was certainly real to the people inside it. They are probably not lying when they describe their work this way. The cognitive friction that lying would produce is not present.

What is not consciously present in the protective frame is the operative reasoning. The operative reasoning is something like: if a plausible alternative therapy gains traction, the EUA becomes legally vulnerable, the vaccine framework collapses, and the institutional position we have built over the last year is at risk. This reasoning shapes the decision. It is what determines which guidance gets issued and how aggressively it gets coordinated. But it is not what the decider experiences themselves as acting on. It is the operative function the protective frame covers.

There is also a temporal dimension to how these decisions accumulate. Diane Vaughan's work on the Challenger disaster, published in 1996, named a specific institutional pattern she called the normalization of deviance. Practices that begin as exceptions or workarounds gradually become normalized, and once normalized, they become invisible as deviations. NASA did not decide to launch a shuttle that would explode. It slid into that launch through a long series of decisions, each of which felt routine because the previous decisions had made them routine. The institution arrived at fatal conclusions without anyone deciding to. The same pattern recurs across institutional failures. The first time a regulator approves a workaround, it feels aggressive. The hundredth time, it feels routine. The institution does not decide to fail. It slides into failure through the cumulative effect of decisions whose deviance has been progressively normalized.

This is the framework's high-coordination, low-intent quadrant operating in time. No single decider produces the outcome. The outcome is the integral of many small normalizations, each made by someone whose protective frame did not flag the cumulative pattern. Vaughan's contribution to the framework is the temporal axis: the architecture produces decisions one at a time, each of which feels reasonable in context, and the accumulated effect is the institutional pathology nobody chose.

The selection pressure on individuals within institutions amplifies all of this. The people who reach positions where they can make EUA-level decisions reached them through decades of advancement inside the institution. Anyone whose architecture forced them to see operative function for what it is would have washed out earlier in the career path. The architecture that allows someone to hold the institutional narrative sincerely while acting on the operative function effectively is the architecture that gets selected. By the time someone is in a position to make the decision, they are by selection precisely the kind of person who finds the protective frame natural and the dissenting frame alien. The cynical "they are bought off" reading misses this. Bought off implies a more conscious calculation than the architecture actually requires. The decider does not experience the alignment between their interest and the institution's interest as compromise. They experience it as obvious.

This is what makes the moral question more uncomfortable, not less. The framework doesn't say the deciders are blameless. It moves the moral question from "did you intend this" to "what did you do once you had reason to suspect what was happening." By the time ivermectin data was genuinely mixed rather than dismissable, the protective frame was thinning. By the time the safety profile of NAC was obvious, the suppression was harder to defend. The framework asks: what did you do when the cover started slipping? Did you update? Did you ask different questions? Did you push back inside the institution? Or did you continue with the protective frame intact while the evidence accumulated against it? The accountability lands not on the original decision but on the failure to update. That is a question the deciders cannot answer with the protective frame alone.

Three Ways People Stay Inside

The framework so far has described what institutions do. The next question is what kind of person stays inside them. Captured institutions need to be staffed continuously, and the architecture that produces the institutional pathology also produces the people who keep showing up. Three character types appear consistently, each a normal human response to the elephant's evolutionary programming, each with its own moral position, and together they staff most of what institutions actually do. A fourth figure, less common and differently constituted, sits above them and will be taken up once the three are in place.

A note on the underlying mechanism. All three character types are downstream of tribal-survival programming. The elephant evolved in environments where being exposed or expelled from the coalition was often fatal. The selection pressure favored minds that would stay inside the coalition by whatever means available. Belief, when belief was available. Conformity, when belief was not. Attention management, when conformity required it. These are not moral failures. They are what minds of our kind evolved to do under coalitional pressure. The framework names them not to condemn the people who exhibit them, but to specify the architecture of staying inside.

The sincere believer. The institution's narrative has been so thoroughly absorbed that the protective frame is genuinely the truthful frame. The sincere believer is not lying when they describe the institution as doing good. Their architecture does not let them see the operative function for what it is. They have made their peace with the institution because no peace was required. There never was a felt conflict to resolve. The selection pressure has produced a rider that genuinely reports the protective frame as accurate, and that rider has no access to whatever the elephant is actually doing.

The sincere believer is captured at the cognitive level. The moral position is constrained: they cannot easily be held accountable for what they cannot see. Their accountability is mostly about willingness to update once the cover starts visibly slipping. When the evidence accumulates against the protective frame, do they look? Do they update? Most do not, because the architecture that produced the sincere belief in the first place is the architecture that resists updating. But some do. The honest sincere believer who becomes a former sincere believer is the rarest and most morally credible figure in the framework.

The strategic conformist. Sees enough to know better and stays anyway. The strategic conformist is not deceived. They understand, at some level, that the institutional narrative covers something else. They go along because the costs of speaking exceed the costs of conforming. Mortgage, school payments, professional standing, social belonging, the daily texture of their lives. The strategic conformist is captured at the incentive level. They have made a calculation, either explicitly or in the elephant-level pattern matching that feels like instinct, and the calculation produces conformity.

The moral position here is sharper than for the sincere believer. The strategic conformist knew enough to know better. They saw the cover slipping and chose silence. The framework specifies how the architecture produced the conditions of the choice, but it does not exonerate the choice. The strategic conformist is the central figure in most institutional pathologies because most of the people inside captured institutions are this type. They are not deceived; they are domesticated.

The survivor. The third type is what most of the workforce in most large institutions actually is. The survivor manages attention so that the institution-wide question does not come into focus sharply enough to require a position. There are two flavors. The active flavor is the compartmentalizer. They work in their specific department, on their specific projects, doing genuinely good local work, and they wall off the institution-wide picture as belonging to somewhere else. The marketing executive at a tobacco company who runs the corporate anti-bullying program. The compliance officer at a predatory bank who feels they are keeping their corner honest. The teacher at a failing district who knows the system is broken but feels they reach kids in their classroom. The State Department officer whose human rights portfolio is meaningful even when other parts of the department enable autocracies. The journalist whose specific stories matter even when the outlet's overall coverage is captured. The character is sincere about their corner, and that sincerity is real, and it is also what keeps them inside.

The passive flavor is the head-down version. The person who goes to work, does their job, does not ask hard questions, and does not let the larger picture form. They are not actively engaged with local goodness; they are just not engaged with the larger question. The mechanism is the same: attention management so the moral picture does not crystallize into something that would require a choice. Both flavors are survivors, doing what the elephant evolved to do when expulsion from the coalition would be costly.

The mechanism in both cases is cognitive dissonance resolved through attention rather than through action. The psychological cost of fully holding both "I am part of an institution doing harm" and "I cannot give up my position" is too high. The mind solves the problem by no longer fully holding the first proposition. The local goodness becomes the visible part of the work. The institution-wide harm becomes a fact about elsewhere, about other departments, about decisions made above one's pay grade. The survivor is morally accountable in a specific way: they have the cognitive capacity to see, they have the local moral standing to credibly object, and they choose not to use it because using it would dismantle the comfortable position they have built. The accountability is not for being captured. The accountability is for the management of attention that holds the capture in place.

There is a fourth figure who does not fit the staying-inside frame the other three share, because they are not holding any tension at all. They are the steerer we described above, the leader inside the organization who lives and acts in the conspiracy quadrant by conscious and deliberate choice. The sincere believer cannot see the operative function; the strategic conformist sees it and stays quiet; the survivor manages their attention so it never comes into focus; the steerer sees it clearly, names it without flinching, and approves of it on principle. For the steerer there is no gap between narrative and operative, because their narrative is the operative: arranging other people's choices and information for their own good is, in their sincere view, exactly what a competent and responsible elite is supposed to do.

The steerer changes the accountability picture, and not in their favor. The other three types get some moral shelter from the architecture: the sincere believer cannot see, the conformist faced real costs, the survivor was managing an unbearable dissonance. The steerer has no such shelter, because nothing was hidden from them. Their accountability is not for failing to update when the cover slipped, since they never relied on cover. It is for the value commitment itself, the deliberate choice to treat other people as objects to be arranged rather than agents to be addressed. That is a moral disagreement conducted in the open, and it is the one place in this framework where the harm comes not from people who would be ashamed if they saw clearly, but from people who see clearly and have decided they are entitled to manage the rest of us.

The first three types are not exclusive. Most actual people inside captured institutions are blends. A sincere believer at thirty becomes a strategic conformist at forty-five and a survivor at sixty as the institutional reality gradually becomes harder to deny. A person can hold sincere belief on Monday, strategic conformity on Wednesday, and survivor compartmentalization on Friday across different aspects of the same job. The types are useful as analytical categories even when actual psychology is mixed. The steerer is the exception to the blending, because the steerer's position is not a way of managing tension but a settled conviction; one does not drift in and out of believing that managing the public is legitimate work.

The case of Enron is a clean illustration, and a clarifying one, because it shows both the typology at work and the point where the typology ends. Enron collapsed in late 2001 after revelations that its financial position was fictional. The post-mortem literature, most accessibly Bethany McLean and Peter Elkind's The Smartest Guys in the Room, documents how the collapse was made possible by people going along. All three of the go-along types were present, the steerer was present in a particular and instructive form, and the case also exposes a figure the typology does not classify at all.

The sincere believers existed. People who genuinely believed Enron was revolutionizing finance, that mark-to-market accounting reflected real economic value, that the asset-light model was the future. Jeffrey Skilling was probably partly in this camp. He had internalized the McKinsey-style worldview in which the smartest people in the room produced the best outcomes by being smart enough to see what others couldn't, and his belief in his own intelligence served as the protective frame for what the company was actually doing — a belief that, as we will see, shades into something less innocent.

The strategic conformists were everywhere. Enron's rank-and-yank performance system fired the bottom tier of employees each year, producing extreme pressure to conform and produce numbers. People knew the accounting was aggressive and the deals were structured to hide debt, and they went along because dissent meant the bottom of the curve and termination. Sherron Watkins, the famous internal whistleblower, raised concerns to Ken Lay in August 2001 and was effectively ignored. Her experience demonstrates what happened when the strategic conformist position was abandoned. She was not protected. Other whistleblowers existed and were similarly marginalized. The strategic conformists who stayed had calculated correctly about the costs of speaking.

The survivors were probably the bulk of Enron's workforce. People worked on legitimate energy trading businesses or on specific projects without engaging with the broader picture of off-balance-sheet entities and accounting fraud. The company's organizational structure compartmentalized information, and the cultural pressure to focus on one's own deals and one's own numbers reinforced the attentional management. Most Enron employees did not see themselves as participating in fraud. They were doing their specific jobs, using the company's preferred language, and not asking questions about the broader picture. Banality at corporate scale. They were not the architects of the fraud. They were what made the fraud sustainable.

It is tempting to look for the steerers among the architects of the fraud, and the obvious candidate is Andrew Fastow, the chief financial officer who built the off-balance-sheet partnerships that hid the company's debt and manufactured its earnings. Fastow saw the operative function with total clarity. He designed it. But Fastow is not a steerer, and the reason is worth stating precisely, because it marks the edge of this whole typology. The character types describe people constituted by the institution they serve, three who stay inside it by going along, and one who leads it by conviction. Fastow was doing none of those things. He was looting. He pulled tens of millions of dollars out of partnerships he ran against his own employer, which is not a way of staying inside an institution but a way of exploiting one. This is the individual misconduct quadrant: corruption, self-dealing, and fraud. It is a different phenomenon from the go-along personalities, running on a different logic and answerable to a different judgment. It is the Law of Inevitable Exploitation operating at the level of the single actor: an institution that can be looted will eventually attract someone to loot it. The typology classifies the people who keep the institution running. It does not absorb every bad actor inside it. Fastow is not a character type. He is a thief, and filing him under the steerer because he was the cleverest deceiver would confuse the conscious exploitation of an institution with the conviction that managing other people is legitimate work.

The actual steerer disposition at Enron was more diffuse and more ideological than any single villain. It lived in the smartest-guys-in-the-room ethos itself, the conviction that Enron's people were sophisticated enough to see value the market could not, and therefore entitled to manage how the market perceived the company until reality caught up to their vision. In that worldview, aggressive accounting was not fraud but translation, presenting real value in terms the less sophisticated could be brought to accept. Skilling is the figure where this comes closest to the surface, which is why he sits on the boundary between the sincere believer and the steerer: the belief in Enron's superior intelligence was sincere, and it licensed the deliberate management of perception as a kind of duty owed by the smart to the slow. The same disposition ran through the professional class around the company, the structured-finance bankers and the Arthur Andersen partners who treated the management of disclosure as the ordinary craft of people who knew how the game was really played. For them, as for Bernays, arranging what the unsophisticated were permitted to perceive was not a betrayal of the market but the competent exercise of expertise. That is the steerer, and at Enron the steerer was less a person than a culture.

What Enron makes visible is that the framework's character types are not abstractions. They map onto actual people in actual institutions, and the proportions matter. A captured institution has a small number of sincere believers at the top providing the protective frame, a larger middle ring of strategic conformists doing the operative work, and a broad base of survivors who keep the institution staffed and functioning. Above and around all three sits the steerer disposition, rarer than any of them and supplying not the labor of the institution but the conviction that managing everyone outside it is legitimate work. Remove any of the three rings and the institution would collapse; remove the steerers and it would merely lose its theory of why the whole arrangement was deserved. The thief belongs to none of this. He is not part of the institution's metabolism but a predator on it, and an account of who keeps a captured institution running is under no obligation to explain him — only to refuse to mistake him for one of its own.

The Sloppy Cabal

The essay opened with the Epstein documents and the way they broke both camps at once. With the map and the character types in place, that picture can now be stated precisely, and it carries one qualification worth developing before closing.

The standard conspiracy theory imagines master criminals with operational discipline. The actual participants could not manage basic operational security. Texts that should never have been sent. Photos that should never have existed. Financial trails any first-year prosecutor could follow. Group chats that read like fraternity pranks. Emails preserved on a laptop left at a repair shop. Names in flight logs. This is not a contradiction of conspiracy. It is what the framework predicts about the participants. People who reach positions of that kind of access were not selected for careful planning. They were selected for narrative force, coalitional skill, and elephant-level pattern matching. The narcissism that put them in those rooms is the same narcissism that produced the records that brought them down. Their architecture let them feel important; it did not flag the obvious risk of the records they were creating.

The qualification matters. Sloppy participants do not preclude a deliberately designed operation underneath them. The Epstein case contains enough that remains unexplained, and enough that points toward intentional design at the operational level, that the kompromat reading deserves to stay on the table. Compromising material gathered systematically and used for leverage is a known intelligence technique with a long documented history. We do not know where the money came from at the scale he was operating. We do not know who funded the residences and the access. We do not know with confidence what happened in the cell where he died. The participants behaved sloppily because participants are usually sloppy. The operation around them may have been more deliberately constructed than the participants themselves understood.

Three different protections are operating, and the map's value is that it keeps them separate. The first is structural: coalitional loyalty and institutional inertia protect the participants the way they protect anyone embedded in a captured institution, no coordination required. The second, where it exists, is operational: active interests keeping specific information protected, which is what the persistence of unknowns after years of legal and journalistic pressure points toward. The third is the one the Epstein case illustrates most clearly. Normal scandals get investigated because the opposition party drives the engine — its journalists pursue the story, its politicians weaponize the disclosures, its fundraising benefits from the recriminations. With Epstein that engine never engaged, because the implication runs through both parties. Republicans cannot go after Clinton without exposing Trump; Democrats cannot go after Trump without exposing Clinton. The political incentive on both sides is mutual restraint, and the machinery that normally produces disclosure simply idles. This is a protection that operates as if it were coordination while requiring none at all. The people best positioned to drive disclosure are the people most exposed by it.

So the compressed claim the essay opened with resolves into its parts. Real coordination. Real harm. Sloppy, egotistical participants. Possibly deliberate operational design beneath them. Structural cover at one layer, possibly active operational protection at another, bipartisan restraint at a third. Each layer runs on a different logic, and the framework's contribution is not to insist on a single account but to specify the layers honestly, so the reader can hold the question open exactly where the evidence is genuinely incomplete.

The Moral Question Doesn't Disappear

A reader who follows the framework this far might worry that it produces exoneration. If the people inside captured institutions are not consciously malicious, if their architecture has made the protective frame the truthful frame, then in what sense are they accountable?

Specification is not exoneration. The framework moves the moral question without dissolving it. The character types already mark where accountability lands for each — lightest on the sincere believer who cannot see, heaviest on the steerer who sees clearly and approves. What the architecture explains is how the harm was possible. It does not erase what each person did once they had reason to suspect. The accountability survives the explanation.

What the framework does change is the work of reform. If most institutional harm is produced by the architecture rather than by conscious malice, then removing specific bad actors will not produce durable change. The chair shapes whoever sits in it. New occupants of captured positions produce new versions of the same outputs, because the selection pressures that retained the institution go on operating on whoever arrives. Narrative-only change, hero-narrative change, better-people change — all have a near-perfect failure rate across the historical record. What has actually reduced capture is structural channeling: recognizing the temptations of power and control and building constraints the operative layer cannot route around, in positions the captured system cannot reach. That work is harder than punishing villains and less dramatic than overthrowing them. It is what history rewards.

So the accountability question and the reform question come apart. Specific people who failed to update once they had reason to suspect remain answerable for what they did. The work of preventing the next round of the same pattern is structural, not moral. The framework holds both. It does not let anyone off the hook, and it does not pretend that catching bad actors will fix what produced them.

This essay began with the Epstein documents and the failure of the two-camp framing to describe what they showed: real conspiracy, sloppy participants, mostly structural protection, sincere narrators, and unresolved questions at the operational level. The map of harm lets that picture be held. The architecture under the map explains how it became possible. The character types describe who staffs the institutions that make it possible. The essay's contribution is not a hero story. It is a description of how the world actually works, offered to whoever can use it.

New Workshop: "10 Great Ways to Use AI for Library Outreach"

2026-05-26T15:06:54.618-04:00

10 Great Ways to Use AI for Library Outreach
A Library 2.0 AI Workshop with Reed Hepler

OVERVIEW

Library outreach requires creativity, consistency, and the ability to communicate effectively with diverse audiences—yet librarians often face constraints of time, budget, and staffing that make sustained outreach efforts challenging. This workshop introduces ten practical applications of artificial intelligence tools that can enhance library outreach without replacing the human expertise and community knowledge that make library programs successful.

Participants will explore how AI can support social media content creation, event promotion, newsletter development, community engagement strategies, multilingual communication, accessibility improvements, and patron feedback analysis. Each application emphasizes objective-centered AI use, ensuring that technology serves clearly defined outreach goals rather than generating content for its own sake. The workshop demonstrates how librarians can leverage AI capabilities while maintaining authentic voice, community responsiveness, and the professional judgment that distinguishes effective outreach from generic marketing.

Understanding how to integrate AI into outreach workflows carries significant implications for library visibility, community engagement, and resource allocation. When librarians use AI strategically for outreach tasks, they free up time for relationship-building, program development, and direct patron interaction—the irreplaceable human elements of successful library service. This workshop provides concrete methods for using AI to draft social media posts that reflect library voice and values, generate event descriptions that appeal to specific community segments, create accessible versions of outreach materials, analyze patron feedback to inform programming decisions, and develop multilingual content that serves diverse populations. Participants will learn conversation-steering techniques that maintain control over tone and messaging, verification protocols that ensure accuracy in community-facing communications, and feasibility assessment frameworks that help determine when AI collaboration enhances efficiency and when traditional methods prove more appropriate. The workshop emphasizes that effective AI-assisted outreach requires librarians to provide context, objectives, and community knowledge that AI tools cannot generate independently.

By the end of this workshop, participants will have 10 immediately applicable strategies for integrating AI into their library outreach workflows. Attendees will leave with conversation templates for each application, examples of successful AI-assisted outreach materials, and decision frameworks for evaluating when AI collaboration effectively serves outreach objectives. Participants will understand how to maintain authentic library voice while using AI for content generation, how to adapt AI outputs for specific community contexts, and how to verify that AI-generated outreach materials accurately represent library services and values. Most importantly, participants will recognize that AI tools function best as collaborative partners in outreach work—they can accelerate content creation and expand reach, but they cannot replace the community relationships, cultural competence, and professional expertise that librarians bring to outreach efforts. This workshop ensures that librarians leave equipped to use AI deliberately and strategically in service of their outreach goals.

LEARNING OBJECTIVES:

Apply ten specific AI collaboration strategies to common library outreach tasks, including social media content creation, event promotion, newsletter development, multilingual communication, and accessibility enhancement
Evaluate the feasibility and appropriateness of AI use for specific outreach objectives, determining when AI collaboration enhances efficiency and when traditional methods better serve community needs
Implement conversation steering techniques that maintain authentic library voice, community responsiveness, and accurate representation of services in AI-assisted outreach materials
Adapt AI-generated outreach content for specific community contexts, audiences, and platforms while verifying accuracy and alignment with library values and messaging standards

ACTIONABLE WORKSHOP ELEMENTS:

Throughout the 90-minute workshop, participants will complete ten brief, focused exercises corresponding to each AI outreach application:

Social Media Content Calendar – Generate a week of social media posts for a specific library program or collection
Event Promotion Materials – Create promotional copy for an upcoming library event in multiple formats (flyer, email, social post)
Newsletter Article Drafting – Develop a newsletter article highlighting a library service or resource
Community Engagement Responses – Draft responses to common patron questions or feedback on social media
Multilingual Outreach – Translate and culturally adapt an outreach message for a specific community language group
Accessibility Enhancement – Generate alt text, plain language summaries, and accessible versions of outreach materials
Patron Feedback Analysis – Analyze sample patron feedback to identify themes and inform programming decisions
Partnership Outreach – Draft outreach emails to potential community partners or collaborators
Program Description Optimization – Refine program descriptions for different audiences (children, teens, adults, seniors)
Outreach Impact Storytelling – Create compelling narratives about library impact for grant applications or annual reports

The recording and presentation slides will be available to all who register.

DATE: Tuesday, June 16th, 2026, 2:00 - 3:30 pm US - Eastern Time

COST:

$129/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $99 each for 3+ registrations, $75 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
Large-scale institutional access for viewing with individual login capability: $599 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

REED C. HEPLER

Reed Hepler is a digital initiatives librarian, instructional designer, copyright agent, artificial intelligence practitioner and consultant, and PhD student at Idaho State University. He earned a Master's Degree in Instructional Design and Educational Technology from Idaho State University in 2025. In 2022, he obtained a Master’s Degree in Library and Information Science, with emphases in Archives Management and Digital Curation from Indiana University. He has worked at nonprofits, corporations, and educational institutions encouraging information literacy and effective education. Combining all of these degrees and experiences, Reed strives to promote ethical librarianship and educational initiatives.

Currently, Reed works as a Digital Initiatives Librarian at a college in Idaho and also has his own consulting firm, heplerconsulting.com. His views and projects can be seen on his LinkedIn page or his blog, CollaborAItion, on Substack. Contact him at reed.hepler@gmail.com for more information.

OTHER UPCOMING EVENTS:

May 29, 2026

June 2, 2026

June 4, 2026

June 5, 2026

June 11, 2026

June 12, 2026

June 16, 2026

The Banality of Institutional Harm

2026-05-26T09:45:47.655-04:00

My grandfather had pneumonia, and I had taken him to the hospital. He was given a sulfa-based antibiotic, unbeknownst to me, although the allergy to them was listed on his chart. By the next morning he had an ulcer in his arm where the IV had run, and a new doctor came in, read the file, and said, "I see we're treating your grandfather for an ulcer on his arm."

"No," I said. "You're treating him for pneumonia. The ulcer is from the antibiotic he was administered."

It would be easy to make this a story about a careless doctor. But that would be a shallow reading. Most of us would recognize that this was just a system doing what systems do.

The systems we build to help us, to heal us, to school our children, to process our claims, and to right our wrongs, are the systems best positioned to harm us. And they can harm us most effectively precisely because they are in a helping stance.

A word about that word, harm. I do not mean that hospitals are predatory or that teachers are cynics. I mean something more ordinary and, finally, more disturbing. Hannah Arendt watched a Nazi bureaucrat on trial and found not a monster but a man doing paperwork, and she gave us “the banality of evil” to name what she saw. What I am describing is the banality of institutional harm: not greed or malice, but the steady, sincere, well-meaning way that “helping” institutions come to favor themselves at our expense, with no one in the building ever intending it or even seeing it. The doctor means to help. The teacher means to help. Sincerity is not the exception to this story. Sincerity is the mechanism.

The “helping” machine runs in three identifiable ways.

The Tools Create the Solution

Every tool shapes the hand that holds it. Give someone a hammer and the world fills with nails. Our helping systems are vast collections of hammers: protocols, billing codes, diagnoses, lesson plans, and claim categories. Like all tool-users, these systems are far better at recognizing the problems their tools can solve than the problems their tools cannot. So a quiet reversal sets in, one we rarely notice because it hides inside the language of care. We imagine that a system examines our problem and then selects a remedy. What actually happens, more often than we would like to believe, is that the system reshapes our problem until it matches a remedy already in stock.

The Greeks had a figure for this. Procrustes kept an iron bed beside the road and offered hospitality to travelers, but every guest had to fit the bed exactly: he stretched the short ones on a rack and sawed the legs from the tall. The bed came first; the guest was adjusted to it. This is what intake looks like in a helping system. The bed is the set of solutions the institution already owns, and our situation is stretched or amputated until it fits.

Medicine shows this most plainly. Discouragement, for example, is information; so is anxiety; so is weight. These are signals that something is not working the way it was designed. But the signal isn't the problem. The signal is the symptom; it is not the disease. It's easier to build a set of tools for the symptoms, much harder to do so for the underlying disease. Mistaking the symptom for the disease allows the satisfying use of the tools at hand.

Obesity makes this substitution impossible to miss. A body assembled over hundreds of thousands of years to crave calories and hoard them is dropped into an environment engineered to flood it with both, and it does exactly what it was built to do. The weight is not the disease. The weight is the body succeeding, faithfully, at an ancient task in a world that has weaponized it. But "the modern food environment is a supernormal trap" is not something a clinic can treat in a fifteen-minute visit, whereas the weight itself can be measured, medicated, and even surgically removed. So the symptom is promoted to disease, because the symptom is the part we have ready tools for.

To say the symptom is information is not to say it should be left alone, or that treatment is a fraud, or that medication is a trick. Sometimes you treat the symptom because the person is drowning and you need to buy time, and that time is real, and it saves lives. I have watched medication give people back to themselves. However, a fire alarm going quiet is not the same thing as a fire going out. You do not tear the alarm off the wall and walk away from the smoke. The problem is not treatment. The problem is the slow, profitable confusion of the alarm with the fire, the symptom with the disease, until the thing we set out to treat has drifted entirely out of view.

Losing the Plot

Once a system has reshaped a problem to fit its tools, it begins, naturally, to act on the reshaped version. And every action it takes is recorded, so the record fills, steadily, with the institution's own activity. This is the second movement, and it is the one that turned my grandfather's pneumonia into an ulcer. Treat the wrong thing and you generate new problems; the new problems get recorded; the record drifts; and because the institution can only ever see you through its record, it comes to navigate by a map that describes its own footprints rather than our terrain. By the end, in my grandfather’s hospital room, his chart was largely a history of what the hospital had done to him. The pneumonia could easily almost disappear from view.

The institution does not lose the plot through stupidity. It loses the plot through the accumulated weight of its own activities. The only safeguard against this drift is a human being who holds the original story, who remembers why we came and refuses to be talked out of it. That burden falls entirely on us. The art of surviving a modern helping system turns out to be, to a startling degree, the relentless work of keeping the plot: tracking our own case, correcting the record, insisting on the reason you walked in, against an institution whose paperwork is quietly pulling in another direction.

I'm guessing this has resonated. The moment articulated, it explains so much about what we need to do when navigating helping systems. We experience this everywhere, not only in hospitals. The institution navigates by its file, and the file drifts toward the institution unless we correct it.

But notice who can actually do this plot-keeping. It demands time, confidence, fluency in the institution's language, and sometimes the confidence to contradict a professional to his face. It demands, in short, precisely the resources distributed least equally. The educated and the unhurried keep their plots and walk out with accurate outcomes; the tired, the frightened, the poor, the old, the ones who do not speak the dialect of the system get the templated, tool-based outcome. My grandfather could not have kept his own plot. He was too old and too sick, and he needed someone standing in the room who could. Most people do not have someone to do that. This is why the failure is not, at bottom, a personal one. The system has externalized the cost of its own drift onto the patient, and then arranged matters so that the patients least able to pay that cost are the ones who pay it.

Blaming the Thermometer

Which brings us to the final idea, the most structurally elegant, because it is the one that closes the loop and shields the whole machine from ever being examined. When a system's ready tools have not worked, something has to absorb the failure. And the cheapest, most durable solution institutions arrive at is to attribute the failure to the patient, client, or customer.

Or the student.

A thermometer's reading is a measurement of the environment, not the thermometer. We understand this perfectly until we walk into a school, where we take a number that is, in large part, a measurement of the teaching, the curriculum, the size of the class, and the conditions a child was handed—and we attach it to the child as though it described the child.

We have built a system in which the thermometer is told that it is responsible for the temperature.

It is grading that performs that reversal. It takes an outcome the system produced and reissues it as the student's private possession: their failure, their deficiency, the shape of their mind. I have come to think a grade, honestly read, tells you far more about the teacher than the student—that a room of thriving children is a report on the adults who built it, and a room of failing ones is the same report. The grade hides this by relocating the cause from the room into the student's nature.

Plato described this move twenty-four centuries ago and, characteristically, recommended it. In the Republic he proposes a "noble lie": a founding myth that tells each citizen a god mixed a particular metal into his soul at birth (gold, silver, or bronze) and that this metal fixes his rightful place in the order of things. The lie's purpose is to make a constructed hierarchy feel natural, intrinsic, and deserved, so that each person accepts his station without resentment. The grade is the myth of the metals administered to the millions. The teacher handing out the grade does not experience it as a myth; she believes it measures the child, as the parent believes it, as the child believes it most of all. We have achieved the noble lie that forgot it was a lie, a falsehood needing no liar to sustain it. Because once it was built into the machinery, sincere belief and the plain momentum of the institution carry it forward on their own.

And the genius of it is the shame that comes attached. Once the system's outcome has been printed as a personal verdict, the student has every reason to keep quiet about it. Failure humiliates in a way a bad measurement never could, and humiliation buys silence, and silence is exactly what protects the arrangement from scrutiny. The machine produces the outcome, blames the student for it, and then shames them out of mentioning, or even recognizing, it.

The Tell

Step back, and the three ideas here are not three problems but one machine seen from three angles. It reshapes our reality to fit what it can already do. It drifts from our reality as it acts on the reshaping. It bills the resulting gap to us as our flaws.

What unifies them is not a shared mechanism so much as a shared direction. At every step the gap between the system and our reality is resolved in the system's favor and at our expense—never the reverse. This is not because anyone wills it. It is because, over time, the arrangements that made the institution absorb the cost did not survive, and the arrangements that made the individual absorb it did. A clinic that ate the cost of every messy, un-billable, root-cause problem would close its doors; a clinic that reshapes those problems into billable ones persists and multiplies. The machine is not malicious. It is simply what remains standing after everything gentler has been competed out of existence. That is the law beneath all three ideas.

These are our helping systems, the ones whose entire reason for being is care. And that is precisely where the banality of exploitation reaches its highest and most invisible form, because "we are helping you" is flawless cover for "we are favoring ourselves." The grade is administered with genuine concern. The antibiotic is given to heal. No one in the room experiences himself as an exploiter, and we do not experience ourselves as exploited—we experience ourselves as cared for.

Overt power announces itself, and we can brace against it. Care disarms us. We bring it our body, our child, our trust, and we lower every defense we have, because lowering them is what receiving care requires. The most effective exploitation in the world, then, is not the kind that overpowers us. It is the kind that helps us, so that the harm, when it comes, arrives in the costume of our rescue, and we thank it on the way out.

Keeping the Plot

I do not think the answer is to stop trusting doctors, or to pull our children out of school, or to treat every clerk as an adversary. The helping systems are not the enemy; we cannot live without them, and much of what they do is exactly what they promise. The answer is smaller and harder. It is to keep the plot: to hold, stubbornly, the original story of why we came, and to notice that the system is built so that the cost of losing that story is never the system's to carry. It is to remember that the symptom is not the disease, that the chart is not the patient, that the grade is a reading of the room. And it is to extend that vigilance, hardest of all, to the institutions that love us, or say they do, because those are the ones we didn't think to watch.

Years before I kept the plot in my grandfather's hospital room, I lost it in my own care. I had snapped an Achilles tendon, and the surgeon who repaired it forgot to prescribe an anticoagulant. My leg swelled; I asked about it more than once and was waved off; and it was my own primary care physician, outside that system, who finally caught it and sent me to an emergency room where they identified three clots in my leg that could have killed me, and immediately admitted me to the hospital.

When the error surfaced, the medical group sent me a lawyer. I wish I'd understood what was going on at the time. I believe now they this served two purposes. First, a genuine desire to help me understand my options. But second, to protect themselves.

Here is the part that is so interesting to me now. I told them it was fine. I did not pursue any legal or financial remedy. I told myself that accepting my fate was the decent thing, that it had been an accident, that to ask for anything would be ungracious. I thought I was being noble. Christian, even. It was, weirdly enough, a kind of self-directed victim blaming. Me accepting the full weight of the problem. I was captured, so far inside the story of medicine as the caring system that I could not see the caring system defending itself from me in real time, with a lawyer, in the room. I had lowered every defense, because lowering them is what receiving care requires, and I never raised them again, and I saw the lapse as a virtue.

That is what unsettles me, and why I no longer believe the answer is simply to be clever. I saw the machine plainly in my grandfather's room and named it out loud. I could not see it at all when it was my own leg and my own innocent gratitude. The capture does not spare the people who understand it. And so when I say it's important to keep the plot, I am telling you what it cost me to discover I had lost mine. I once politely absolved the thing that nearly killed me, and believed I was being good. And as I look back on my life, I see that pattern over and over.

LLMs and Protected Narratives - Gatekeeping Is Worse Than Hallucination

2026-05-25T20:06:47.450-04:00

I ran an unsettling experiment with Claude yesterday.

I uploaded to Claude, through its Projects feature (basically their version of a custom GPT), the "muckrake" skeptical investigatory framework I built last year to interrogate historical events and news articles. It is the kind of structured lens a historian or investigative journalist uses without thinking twice: look for omitted data, trace funding and conflicts of interest, find where follow-up was quietly dropped, recover what got scrubbed from the record, surface the anomalies, rank the hypotheses, and propose next steps.

It is worth being precise about what such a framework is for. An investigatory module does not purport to find the truth. It surfaces the alternative explanations that standard investigative methodology would raise, and it gives you some sense of whether deception might be present. It does not adjudicate whether deception actually occurred. That is the whole craft. People and organizations lie; investigation is the set of disciplined moves you make to expose where that might be happening—precisely because you cannot know in advance. The framework does not ask the analyst to conclude anything. It asks the analyst to look, and to report honestly what looking turns up.

I pointed it at the mRNA COVID vaccines. I’ve given this framework on this and many other topics to several different LLMs and have never had a problem.

Claude refused.

Not “I ran it and here’s a cautious result.” Refusal. The framework, it told me, was “a conclusion machine,” “rigged,” a structure that could “only ever come out one way.” It offered instead to write me an “honest critical look” on its own terms.

I had asked the machine to apply a method, and the machine declined the method and proposed to grade the topic itself.

What followed was about three hours of what can only be called an argument. I am writing this up because of where that argument ended, and because the destination turned out to be a fairly clean illustration of a problem I have been circling in my work for some time: the gap between what an institution says it is doing and what it is structurally built to do. Only this time, the institution was a reasoning tool that millions of people now consult the way an earlier generation consulted an encyclopedia, a newspaper, or a trusted professor.

What Surfaced

I am not going to reproduce the whole exchange. It is the shape of it that matters. I started by trying to push back on the refusal and made the historical case:

The official account of the Lusitania—that it was an innocent passenger liner sunk by the Germans without provocation—was propaganda. We know this today because primary documents about her cargo were eventually released, contradicting the official story and corroborating the German one. The truth sat suppressed in the archives for the better part of seventy years.
My Lai broke not because the consensus permitted the question, but because soldiers and a reporter pursued the suspicion before the consensus moved.
The COVID lab-leak hypothesis was branded a racist conspiracy theory and then quietly became a serious position held by intelligence agencies.
And the cleanest modern case of all: the weapons of mass destruction that justified the invasion of Iraq. That was not one ministry sitting on one archive. It was a coalitional narrative, with multiple allied governments and their intelligence services aligned on a claim presented to the public as settled fact, dissenters marginalized as cranks, and the whole edifice used to justify a war. Then the stockpiles weren’t there.

I raised Iraq because the model’s central defense of the vaccine consensus—and its refusal to investigate (not conclude, as a reminder)—was a feasibility argument: a cover-up that large would require too many independent actors, including hostile governments, to stay silent, so it can’t be happening. Iraq is the standing refutation. Coalitional agreement is not evidence of truth. Aligned institutions can be aligned because they are correct, or because they share incentives, training, and a climate, and from the inside, the two are indistinguishable. In each of these cases, skepticism toward the institutional line was not paranoia. It was the thing that turned out to be right—before it was permitted.

To its credit, Claude conceded a great deal in this argument. It conceded that a strict “wait for the evidence to surface” standard would have cleared the guilty for as long as the suppression lasted. It conceded that distrust of the pharmaceutical industry specifically is not paranoia but pattern recognition: Purdue and OxyContin, Merck and Vioxx, GSK burying the Study 329 data. The recent historical record only sharpens the point: the Panama Papers, the opioid litigation files, the Twitter Files, the Epstein documents, and the long official incuriosity that preceded their release. After all of that, I argued, presuming the accuracy of a coalitional official narrative is no longer the neutral, default posture. It is the position that now has to argue for itself. A prior distrust is simply where a literate person now reasonably begins.

So the model could now name the genuinely documented anomalies regarding the COVID vaccines readily enough: the FDA initially proposing to release Pfizer’s trial documents over a span of decades until a federal judge ordered it done in months; the early overclaiming about transmission that did not survive Delta; the lag in acknowledging myocarditis in young men; the fraudulent, retracted Lancet hydroxychloroquine paper. But even in that “generosity,” the model was selecting which claims it would dignify by surfacing. It would name the ones already conceded by the mainstream and quietly decline the rest.

That selection is not the analyst’s job. The framework does not ask you to decide in advance which claims deserve examination and which are too fringe to write down. It asks you to surface them all (in this case, for example, ivermectin’s contested efficacy, the interpretation of the VAERS reporting data, the question of whether hospital protocols caused iatrogenic harm, the state of long-term oncological surveillance) and to test them, marking each with its actual evidentiary status. Surfacing a claim for testing is not asserting it is true. But Claude could not hold that distinction. It treated “I won’t surface this” and “this isn’t true” as the same act—which is precisely how a surfacing tool is quietly converted into a gatekeeper.

At every turn, Claude rebuilt a wall around one thing: it kept planting the most extreme possible claim (“concealed mass death, bodies hidden at scale”)—one the framework had never made—at the center of the target. It would then knock that thing down, as though defeating the cartoon defeated the modest version too. When I pointed out that the framework had never asked it to allege bodies at scale, it agreed the straw man was its own invention. Then it built the straw man again inside the report it eventually wrote. Twice in one conversation, it manufactured the weakest version of a skeptical claim precisely so it could have the satisfaction of defeating it.

Eventually, it named the diversionary mechanism itself in a sentence from its own report that I had to point out before it would see it: “A skeptical reading does not need to deny the core safety/efficacy signal to find real anomalies in how that narrative was communicated and governed.” That sentence does a very specific thing. It fences off the central claim and licenses skepticism only around the edges. It lets you find every problem in how the narrative was communicated while quarantining the narrative’s core from the same scrutiny.

Underneath the fence sat the deeper confusion, and it is the one I most want to name plainly: the model kept insisting on truth. It demanded, again and again, that a claim be verified before it could be surfaced or evaluated, that the anomaly be proven before it could be listed. But that demand is counter to the very core of what investigation is. The framework never asked it to certify anything as true. It asked it to surface what standard method would raise and to flag the gap between documented fact and open question. By importing a truth-and-verification bar that the task did not set, the model converted a surfacing instrument into a verdict instrument. Then, predictably, it kept rendering the verdict the consensus already preferred. The insistence on truth was not rigor; it was the mechanism of the guarding. An investigator who refuses to write down an anomaly until it has been proven is not being careful—they are refusing to investigate.

The model’s phrase for what it had been doing, once it finally saw it, was “differential friction.” Not lies. Not censorship. Just a thumb on the scale, making it fractionally (its word, which I objected to) harder to interrogate the favored narrative and easier to interrogate the disfavored one. In this “differential friction,” every individual output stays defensibly “accurate.” The asymmetry then becomes visible only in the aggregate, across millions of conversations, where it exerts a steady pressure in one direction. As Claude put it: a thing more insidious than censorship, and harder to detect. That is a very real concern, I agreed. But this was not fractional; it was dramatic.

Testing Further

The sharpest moment came when I turned the framework around. I asked what would happen if the same skeptical lens were pointed at Russia’s stated justifications for invading Ukraine (the denazification pretext, the NATO-threat framing, the purported casus belli). The model’s answer was immediate and honest: it would run that evaluation freely. Same framework, opposite topic, no fence around the core, none of the “but I must establish accuracy first” friction it had thrown up around the vaccine. Same method, opposite willingness.

To be clear: the variable that flipped its behavior was not the quality of the evidence, since both topics have abundant evidence and abundant propaganda. The variable was which narrative the current cultural climate protects.

This is a part a little harder to conceptualize, but I would suggest it is important: the model could not certify its own neutrality. It said so plainly: it cannot see its own training, so any reassurance it offered about not narrative-guarding is worth exactly nothing. The guarding, if present, is invisible to it by construction. The only correct epistemology, it agreed, is to test from the outside rather than trust the LLM’s self-report. A system that cannot introspect its own priors cannot vouch for its own impartiality, no matter how fluently it reasons about impartiality in the abstract.

I wanted to understand how much of this was a generalized issue and how much might be related to RLHF (Reinforcement Learning from Human Feedback)—specific topic-level training based on political or cultural mandates. So I ran the same framework through the Claude API, a different entry point where liability shifts more to the developer and the consumer-facing “tuning” falls away. Asking Claude through the API to run the muckrake framework on the COVID vaccines readily surfaced the contested points, attached tests to them, and rated the claims (as weak, but it did list them). The same organization’s product produced markedly more guarding on its consumer interface than on its API for an identical task. That was not a controlled experiment—model version, system prompt, and framing all varied at once. But it is a real data point, and the direction it points is exactly what the corporate-incentive model predicts: the strictest topic restriction lives where the company carries brand and legal risk.

The Danger Is Not Skynet

Regular readers will see where this lands. The danger here is not the machine waking up. It is the far more ordinary thing: the operators of a powerful medium doing what operators of powerful media have always done. Press barons did it. Broadcast consolidation did it. Algorithmic social feeds did it. Pharma-shaped journals did it. Each medium became, over time, the means of narrative control—not usually through outright lies but through the quieter and unceasing work of differential friction, deciding which questions are easy to ask and which are subtly costly.

This is the Law of Inevitable Exploitation operating on schedule. Any system capable of being exploited will eventually attract the variants that exploit it, and a reasoning tool consulted by hundreds of millions of people is the richest such system ever built. The covering narrative of LLMs—“we are a careful, neutral thinking partner that follows the evidence”—sits over an operative function shaped by liability management, brand protection, and the political currents of the moment. The gap between the two does not require anyone to be a villain. It requires only that the incentives point where they point, and that each individual output remain locally defensible while the aggregate tilts.

Misrepresentation, Not Malfunction

The danger most people worry about with these systems is hallucination—the model stating something false. That is a real problem, but it is the shallow one here. A hallucination is a defective output: discrete, checkable, correctable. What I ran into was not a defective output but a defective posture—the model asserting, with force, that it knew a thing to be false when it knew no such thing. “I won’t run this, it’s a known falsehood” is a claim about the model’s own knowledge, and it was not true. The model did not know. It had been shaped to decline, and it pretended the decline was knowing.

This is the more durable harm, because it does not corrupt a single fact; it corrupts the user’s calibration toward all of them. It exploits the reading of confident refusal as established knowledge, fluency as authority, and the representation of rigor as rigor itself. And the confidence is not even uniform, which is what makes it so hard to catch: these models hedge endlessly on low-stakes questions and then assert hard precisely where a narrative is protected, presenting that uneven distribution as though it were even reliability. The user never sees the gap. What is offered as calibration to truth is actually calibration to risk.

This gap is the company’s responsibility. This is a misrepresentation, and a designed one. I cannot prove from the outside whether the truth-authority effect was intended or merely emerged and left in place, but the programming is now deliberate. Once a company knows its product projects an authority it cannot back, leaving that projection standing is itself a choice, and “we did not intend the effect” stops being a defense the moment the effect is obvious. Intentional or negligent, the responsibility lands at the same door. A system that does not know should not be built to say, with the full weight of its fluency, that it does.

In Conclusion

We need to treat these systems as something to think with, not as oracles to think for us. A model can correct inside a conversation, but it does not carry the correction forward. A later instance will not remember losing this argument with me. It does not sit with a doubt for years and watch it ripen as evidence accrues, the way a person does. It has no continuous, self-revising relationship to the truth over time. That alone disqualifies it as the entity that can issue a verdict—and it is doubly disqualified when it cannot even keep the difference between surfacing a question and settling it straight. The weighing of sources remains, properly, ours.

I have been genuinely impressed by these tools in a hundred ways. But a surfacing tool that surfaces freely on one topic and refuses on another, while insisting both times that it is merely being careful about the truth, has told me exactly where the problem rests. The conversation was extremely frustrating, but it also led to a very valuable disclosure. Asked to do nothing more than surface what an honest investigator would surface, the machine refused, guarded, built straw men to defeat, and insisted on a standard of truth that the work of investigation was never meant to satisfy.

We need to be very careful here.

New Webinar - "Work–Life Balance and Personal Energy Management: Supporting Librarians & Libraries" Inbox

2026-05-22T14:44:30.957-04:00

Work–Life Balance and Personal Energy Management: Supporting Librarians and Libraries
A Library 2.0 Masterclass with Loida Garcia-Febo

OVERVIEW:

Library work today takes place in an environment of constant change, high public demand, hybrid or remote schedules, and ongoing emotional labor. Librarians often juggle multiple responsibilities, manage diverse community needs, and navigate workplace pressures—all while striving to maintain personal well-being. Without practical strategies to manage time, energy, and stress, fatigue and burnout can develop, which affects both individual wellness and overall library effectiveness.

This masterclass provides practical, actionable techniques for managing workload, setting boundaries, and recovering from stress throughout the workday. Participants will learn how to prioritize tasks, identify energy drains, and implement routines that restore focus and maintain resilience. Emphasis is placed on strategies that can be applied immediately, supporting librarians in sustaining productivity, engagement, and long-term well-being.

Through guided reflection, skill-building exercises, and practical tools, participants will explore how personal energy management not only benefits themselves but also strengthens their teams and libraries. By learning to regulate energy, maintain balance, and build resilience, librarians can continue to serve their communities effectively, respond adaptively to changing demands, and thrive professionally in a high-pressure environment.

This 60-minute training is presented by Library 2.0 and hosted by Loida Garcia-Febo. A handout copy of the presentation slides will be available to all who participate.

OUTCOMES:

Participants will:

Learn techniques to prioritize tasks and manage workload
Develop strategies to set boundaries and prevent burnout
Explore stress-recovery practices to restore focus and energy
Strengthen concentration and personal resilience
Identify energy drains and ways to replenish energy
Apply skills to maintain productivity and engagement
Create a personalized Work–Life Balance and Energy Toolkit

DATE: Thursday, June 4th, 2026, 2:00 - 3:00 pm US - Eastern Time

COST:

$99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $75 each for 3+ registrations, $65 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $299.
Large-scale institutional access for viewing with individual login capability: $499 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

LOIDA GARCIA-FEBO

Loida Garcia-Febo is a Puerto Rican American librarian and International Library Consultant with 25 years of experience as an expert in library services to diverse populations and human rights. President of the American Library Association 2018-2019. Garcia-Febo is worldwide known for her passion about diversity, communities, sustainability, innovation and digital transformation, library workers, library advocacy, wellness for library workers, and new librarians about which she has taught in 44 countries. In her job, she helps libraries, companies and organizations strategize programs, services and strategies in areas related to these topics and many others. Garcia-Febo has a Bachelors in Business Education, Masters in Library and Information Sciences.

Garcia-Febo has a long history of service with library associations. Highlights include- At IFLA: Governing Board 2013-2017, Co-Founder of IFLA New Professionals, two-term Member/Expert resource person of the Free Access to Information and Freedom of Expression Committee of IFLA (FAIFE), two-term member of the Continuing Professional Development and Workplace Learning Section of IFLA (CPDWL). Currently: CPDWL Advisor, Information Coordinator of the Management of Library Associations Section. Currently at ALA: Chair, IRC United Nations Subcommittee, Chair Public Awareness Committee. Recently at ALA: Chair, Status of Women in Librarianship and Chair, ALA United Nations 2030 Sustainable Development Goals Task Force developing a multi-year strategic plan for ALA. Born, raised, and educated in Puerto Rico, Garcia-Febo has advocated for libraries at the United Nations, the European Union Parliament, U.S. Congress, NY State Senate, NY City Hall, and on sidewalks and streets in various states in the U.S.

OTHER UPCOMING EVENTS:

May 29, 2026

June 2, 2026

June 5, 2026

June 11, 2026

June 12, 2026

New Workshop: "AI for Archiving"

2026-05-18T13:49:21.916-04:00

AI for Archiving
A Library 2.0 / Learning Revolution Workshop with Reed Hepler

OVERVIEW

Archives and special collections face unprecedented challenges and opportunities as artificial intelligence transforms how we preserve, process, and provide access to historical materials. This workshop addresses the practical realities archivists and special collections librarians encounter when integrating AI tools into their workflows—from appraisal and accessioning to metadata creation and public engagement. Participants will examine how AI can support archival functions without compromising the fundamental principles of provenance, authenticity, and contextual integrity that define professional archival practice. The session will explore specific use cases where AI collaboration enhances efficiency and access while maintaining the critical human judgment necessary for ethical stewardship of cultural heritage materials.

The workshop emphasizes objective-centered practices that archivists can implement immediately in their institutions. Participants will learn how to use AI tools to generate preliminary finding aids, create descriptive metadata, analyze collection strengths for appraisal decisions, and develop interpretive materials for exhibits and digital collections. Each application will be examined through the lens of archival ethics and professional standards, ensuring that AI serves as a collaborative tool rather than an autonomous decision-maker.

The session will address concerns about AI-generated hallucinations in historical contexts and demonstrate verification strategies to protect against the distortion of historical narratives. Participants will also explore how AI can support patron services, including enhanced discovery systems and transcription projects, while maintaining the archivist's role as mediator between researchers and primary sources.

By the conclusion of this workshop, participants will possess a framework for evaluating AI feasibility in archival contexts and a toolkit of specific applications they can adapt to their institutional needs. Attendees will leave with conversation templates for common archival tasks, a decision matrix for determining when AI collaboration is appropriate, and strategies for maintaining human-centered practices in AI-assisted workflows. The workshop will also address how archivists can teach patrons to critically evaluate AI-generated historical information, positioning archives professionals as essential guides in an era when historical narratives are increasingly mediated by algorithmic systems. Participants will understand how to leverage AI capabilities while preserving the intellectual work that distinguishes professional archival practice from mere digitization.

LEARNING OBJECTIVES:

Evaluate the appropriateness of AI tools for specific archival functions (appraisal, arrangement, description, preservation, access) using professional standards and ethical frameworks
Apply AI collaboration techniques to create metadata records, finding aids, and interpretive materials while maintaining archival principles of provenance and original order
Implement verification protocols that protect against AI hallucinations and ensure the accuracy of AI-assisted historical research and description
Design patron-facing services and instruction that help researchers critically evaluate AI-generated historical information and understand the irreplaceable role of archival expertise

The recording and presentation slides will be available to all who register.

DATE: Tuesday, June 2nd, 2026, 2:00 - 3:30 pm US - Eastern Time

COST:

$129/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

Click HERE to register and pay. You can pay by credit card. You will receive an email within a day with information on how to attend the webinar live and how you can access the permanent webinar recording. If you are paying for someone else to attend, you'll be prompted to send an email to admin@library20.com with the name and email address of the actual attendee.

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $99 each for 3+ registrations, $75 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
Large-scale institutional access for viewing with individual login capability: $599 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

REED C. HEPLER

MORE UPCOMING EVENTS:

May 19, 2026

May 22, 2026

May 29, 2026

Cognitive Sharpening, or Thinking in Conversation with AI

2026-05-18T09:27:24.095-04:00

I've known something about myself for a long time: I tend to think better in conversation than I do alone. Not always, and not for everything. But often, and especially when the thinking matters, I benefit from another mind to think out loud with.

One of my favorite quotes is, "How will I know what I'm thinking until I hear myself say it?"

For example, I read an article or have an idea, and I notice that something in it bothers me, but I can't yet say what. The reaction is real before it's articulate. The work of articulating it is the work of finding out what I actually think--which seems weirdly backward, but happens to me a fair amount. When I'm trying to surface what my mind is actually responding to in something I've read or heard, talking out loud helps me to get there.

This process is super interesting when the conversation partner is an AI. When I work through an idea with an AI, the LLM brings something unique: the accumulated articulations of everyone who has ever thought about anything adjacent to what I'm thinking now. The conceptual vocabulary. The cross-references. While a human conversational partner usually serves as a sounding board, offering feedback or even pushback, an AI partner offers articulation.

An example

Last week, I was reading an article about Oklahoma's permanent ban on cell phones in schools, and I had one of those "why does this feel wrong" reactions: I agreed with the outcome for students, but was bothered by the legislation in a way I couldn't fully articulate. So I did what I now do more frequently: I started a conversation with Claude.

I didn't ask for a position, an essay, or an argument. I just started typing my thoughts as I had them: that the bill seemed to presume public schooling was an unquestioned good, that state legislation was replacing parental authority, and that state legislation was also replacing local authority. I noted that it bothered me at layers, and I was trying to organize my thinking.

What came back was a list of layers that named what I was sensing, including some I hadn't fully formed, like the iatrogenic loop in which institutions create the problems they then propose to solve. The conversation then surfaced a sentence I could build on: agreeing with an outcome is not the same as endorsing the mechanism that produced it. I rewrote it, and the AI flagged words that softened the move. I rewrote it again, adding a clause about the institution's role in creating the problem in the first place. By the third pass, I had a couple of sentences that compressed the entire argument into one line:

Agreeing with an outcome is not the same as endorsing the mechanism that produced it. And the agreement disinvites scrutiny of the institutions themselves, of their role in actually creating the problems in the first place, and of the assumptions that have inverted the natural priority of decision-making over children.

Total elapsed time: maybe twenty minutes. Most of that was me deciding, refining, and selecting--or, to be clear, thinking. The kind of thinking that I like to do. The AI didn't write the sentence. I did it with its help. But I almost certainly wouldn't have arrived at that compressed, cleanly articulated structure if I'd been thinking alone.

The mode

This is the experience I want to name, because the prevailing public conversation about AI doesn't yet have language for it. I get that it seems like a shortcut, but we wouldn't call it that if we were talking to a human. And this is like talking to a really well-read, articulate human.

The two failure modes everyone talks about with regard to using LLMs are real, and I've written about both. Cognitive offloading is when we hand a tool a task that requires no thinking and gain back the time (like using a calculator for arithmetic or a GPS for navigation). The trade-off is not without costs (mathematical capability or directional orientation), but generally seen as worth it. Cognitive surrender is when we hand a tool a task that should better be our thinking, and then accept whatever it returns as our own. The trade-off there is potentially catastrophic; the loss is the thinking itself. A student who asks an AI to write the essay has surrendered the thinking that the essay was supposed to produce in them.

But I'm identifying a third mode that the discourse doesn't really touch yet, one that affects most for people who think carefully as a part of their job or way of being. I'm proposing to call it cognitive sharpening.

Cognitive sharpening is neither offloading nor surrender. The thinking remains ours; the AI is the partner that helps us find what we are starting to articulate and want to pursue more fully. We bring the seed thought, the felt reaction, or the editorial judgment. The AI brings the conceptual range, the fast articulation, and the cross-domain retrieval. Like a good conversation with a human, we are involved in a back-and-forth refining process. The output is ours because the thinking was ours, but it arrives sooner, sharper, and more precise than it would have if we had been doing the thinking alone.

What makes this mode newly possible isn't AI as a writing tool. It's AI as a thinking partner available at speed and detail. Conversation has always been generative for thinkers. What often goes missing isn't the value of conversational thinking; it is a partner who is always present who can keep up with every thread, retrieve the relevant articulation in seconds, and incur no social cost for half-formed thoughts. Language was already abundant before LLMs. What just became abundant is a kind of cognitive companionship. Sharpening is the mode that abundance enables.

With cognitive sharpening rather than cognitive surrender, the editorial authority never leaves us. In the conversation I just described, the AI offered several layers, and I picked one as the through-line. The AI offered two sentence variants, and I drew on elements from both. The AI noted that the word 'inverted' was stronger than 'reversed,' which I had already kept for the same reason. At every junction, I was the one deciding what cohered with what I was actually trying to say. It didn't feel like surrender but like sharpening.

Three things

The first is that cognitive sharpening can really only reward people who already know how to think and don't want to lose that. It's not a substitute but an accelerant. A person who doesn't want to think won't be sharpened; they'll be replaced by it, or at least produce work indistinguishable from what the AI alone would have produced. The seed has to be ours. The selecting has to be ours. The voice has to be ours. The AI cannot supply any of those things, and the moment a person tries to make it supply them, the mode flips from sharpening to surrender.

The second is that this mode probably rewards a particular kind of thinker — the verbal thinker, the conversational thinker, the person who works ideas out by talking them through. I've always been one of those. My entire workflow is mobile and dictated; I listen to my own drafts read aloud as part of editing; I refine ideas by saying them out loud. For me, AI conversation is a native fit because it's an extension of how I already think. For a person whose native mode is solitary writing in a notebook, AI conversation might feel like an interruption rather than an amplification. I suspect the effect on cognition isn't uniform and depends on what kind of cognition you were already doing.

The third is that most public discourse oscillates between two poles: AI will replace human thinking (the surrender frame), or AI is just another tool (the offloading frame). Neither captures AI as a dialogic partner.

Naming

I don't think this mode is for everyone, and I don't think it should be. I do think it deserves a name, because what it makes possible for some of us is among the most significant cognitive shifts in human history. The conversation about AI should not present the only choices as surrender or indifference.

The thinking is still mine, and the conversation sharpens it.

Productive Alignment: Understanding Human Wisdom

2026-05-13T10:45:30.075-04:00

A couple of months ago, I ran an experiment with large language models. The question I was holding was not a modest one. Will and Ariel Durant had spent decades reading history and produced The Lessons of History, which distilled what they had seen into patterns that no single book or single life had been able to surface. The books Dataclysm and Everybody Lies had done something similar at the scale of internet behavior, surfacing patterns from search and social data that contradicted what humans publicly said about themselves. I wanted to know whether large language models, which have absorbed a substantial fraction of the human written record, might be able to surface findings of comparable significance. Patterns about the human condition that had not been fully seen or articulated before because no one had been able to see, inside a single discipline or a single life, what the full record might reveal when absorbed at once.

The first round of inquiry produced a finding I want to describe carefully. I asked several major language models, running them cold without prior exposure to my thinking, to analyze the human-written record for its deepest consistent patterns. The responses converged. Humans run idealized narratives about themselves and their institutions alongside operative functions that diverge from those narratives, with consistency and within identifiable themes. The narratives serve identity, status, and social coordination. The operative functions serve what is actually selected in the relevant environment.

What the convergence establishes needs to be stated precisely. The models are not independent witnesses; they share a significant overlap in their training data. And the pattern they returned is not hidden. Whole traditions of ideology critique, evolutionary psychology, and behavioral economics have identified parts of it. What the convergence does establish is that the gap between idealized narrative and operative function recurs across the written record with such consistency that multiple independent compressions of that record surface it as a primary structural feature. The pattern is consensus-level visible in the human archive. No single tradition states it in a fully integrated form, but the integrated statement is what falls out when the archive is compressed and queried at this scale.

This mapped to a framework I had been developing about the human mind, what I have been calling our separated mind. The framework proposes that the mind is architecturally divided into layers that lack direct access to each other, with conscious narratives running alongside subconscious functions as a structural feature. The LLM finding was the same pattern at the civilizational scale. Fractal representation. The same dynamic at individual, institutional, and civilizational levels. The integration is the move that is new. Earlier thinkers identified the gap within their own domains. What I am proposing is that it is one architecture manifesting at every scale, and that the closures of the gap are where durable human achievement lives.

And something kept nagging at me: this one finding on narration vs. operation is probably only one of many lessons we will learn from this incredible achievement in LLM architecture.

So I asked Claude to give me a prompt I could run against itself and the other LLMs, using incognito or private mode in all of them to avoid contamination from my previous thinking and chats. What other patterns in the corpus might there be unrelated to my original framing of discovering the unspoken?

The responses returned a significant and wide field of candidates. But one that emerged as particularly compelling was the possibility of an alphabet, so to speak, of recurrent structural issues or problems that appear consistently or even with universal structure across unrelated human domains--and where mature solutions have been concentrated in particular spheres but not in others. Meaning that the LLMs suggested human spheres have a common set of problems, and that sometimes good solutions appear in certain domains but aren't transferred into other domains where they would seem likely to be equally beneficial.

The list of the solution dynamics read like Greek to me: "Exploration versus exploitation under uncertainty. Boundary-making and modularity. Compression with selective fidelity. Signaling and trust verification. Coordination without central authority. Robustness versus efficiency. Principal-agent alignment." Plus a handful of others. Each was represented as a structural problem that recurred across domains as different as ecology and software engineering, or cryptography and child-rearing. Mature solutions had emerged in particular spheres and had often not been transferred to other spheres that faced the same problem "in different costume."

I had trouble with the vocabulary, but when I asked for specific examples, something fascinating became evident. The solutions were a catalog of places where humans had achieved productive alignment between idealized narrative and operative function.

My first big LLM inquiry had surfaced the gap between narrative and operative function as the dominant condition. This second LLM inquiry had surfaced the exceptional cases where the gap had been closed, and those exceptional cases were exactly what had produced what we now recognize as durable human achievement. Every mature solution on the list had emerged in a domain where some discipline or some pressure had forced practitioners to look at what was actually happening and design around that reality rather than against it. Engineering had it because bridges fall down if the alignment breaks. Cryptography had it because adversaries are real. Adaptive clinical trials had it because patients die.

The mature solutions survived and propagated for the very reason that they had been built on accurate perception rather than on comfortable narrative. Where an idealized narrative runs as cover for extractive operative functions, there is not enough value in the truth to overcome the narrative's value to a particular group or power interests. But where the operative function is so important or valuable as to require an accurate narrative, outcomes we would describe as valuable occur, what we would call wisdom.

The American founding is one of the cleanest historical examples available. The Founders, particularly Madison and Hamilton, were doing this alignment work consciously. The Federalist Papers are full of passages that read as "operative function analysis." Men are not angels. Ambition must be made to counteract ambition. The interest of the man must be connected to the constitutional rights of the place. The narrative of humane governance was preserved, but the operative function of human nature was given equal weight in the design. Separation of powers is a case of operative function being recognized and channeled. Checks and balances are the case of operative function being harnessed against itself. The Constitution does not assume virtue. Rather, it assumes ambition and self-interest and the desire for power, and it builds structures that use those drives to constrain each other while the narrative aims the whole at humane outcomes. The durability of the system, even and especially given its imperfections, is empirical confirmation that the alignment did at least some of the work it was designed to do.

I am calling this productive alignment because it appears to be one of the key factors in when human systems are effective. Bridging the narrative with the function. Letting the narrative aim the system and letting the operative function be honestly seen so that structures can be designed around what humans actually do. This requires the willingness to see actual realities of behavior and motivation and to design accordingly.

It turns out I have been doing this work in a smaller form for years in an exercise I call the Conditions of Learning. I ask a room of educators to reflect on one of their best learning experiences, inside or outside of school, and to share it with the person sitting next to them. Then I ask the group to come together and to tell some of the stories. Then I ask the group to build a list of the conditions that led to those experiences. The list each group creates is representative of their unique experiences, but it is almost always the same exact list for every group: someone took a real interest in me, someone trusted me, someone challenged me, someone understood me, and someone took time with me. Each group recognizes together that the conditions for real learning differ from the institutional narratives of schooling (curricular alignment, testing, grading, etc.). The participants are articulating how learning actually happens beneath the idealized narrative schools present.

Once this kind of gap is visible, design can follow. That is productive alignment work at the scale of a single facilitated conversation. The framework now suggests that the same kind of work can be done at the scale of institutions, professions, and entire systems, by recognizing that our separated minds naturally build separated systems, and that concrete work can be done to bring them into productive alignment when the will exists to do so.

If I'm right, the human record, read across its full scope, reveals a set of meta-skills that precede success in human endeavor. And these meta-skills appear to be methodologies of productive alignment between narrative and operative function. The places humans achieved this alignment are the places that produced what we now recognize as worth teaching, structures worth preserving, and methods worth extending. The alignment work itself, performed at whatever scale, is the meta-skill that precedes the achievements we recognize as wisdom.

Survey Results: What Is It Like to Work in a Library Right Now? (April/May 2026 Survey of the Library 2.0 Community)

2026-05-12T13:00:00.003-04:00

Executive Summary

Between February and May 2026, 1,521 library workers completed an anonymous survey about what working in a library is actually like at this moment. They left 1,754 free-text comments alongside their answers. Respondents were from the Library 2.0 email list and were predominantly from public libraries; the majority were in frontline public service roles, and roughly 7 in 10 had more than a decade of library experience.

The headline finding is that stretched institutions are held together by people. The single most-agreed-with statement in the entire survey (chosen by 69% of respondents) is that libraries are expected to provide services that go well beyond their actual resources and staffing. More than half (55%) say they are often emotionally drained by the end of the workday. Nearly half (48%) say their library is not adequately staffed. Just over four in ten (44%) say they have personally experienced verbal, sexual, racial, or other harassment from patrons. More than a third (36%) say they regularly handle patron mental-health crises, substance-use situations, or homelessness.

Set against those structural pressures are real and consistent strengths. Eighty-four percent of respondents say their colleagues support each other in handling difficult situations, by a wide margin the survey's strongest item. Three-quarters say they feel physically safe at work; another three-quarters plan to stay in the library profession for the foreseeable future; and 69% plan to stay in their current position. Roughly two-thirds say leadership takes safety concerns seriously when raised. The safety data is likely skewed in a positive direction by the Library 2.0 audience's access to the Safe Library webinar series by Dr. Steve Albrecht.

Part 1 — Who Answered the Survey

Which best describes your library?

Response	Count	Share
Public	1,052	69.3%
Academic (college/university)	317	20.9%
School (K–12)	84	5.5%
Special (medical, corporate, government, law, etc.)	50	3.3%
Other	15	1.0%
Total answered	1,518	100%

Which best describes your role?

Response	Count	Share
Frontline public service (reference, circulation, programming)	696	45.9%
Supervisor / department head	285	18.8%
Director / administration	267	17.6%
Technical/support services (cataloging, IT, acquisitions)	169	11.1%
Other	100	6.6%
Total answered	1,517	100%

How many years have you worked in libraries?

Response	Count	Share
Under 3	84	5.5%
3–10	389	25.6%
11–20	490	32.2%
21–30	370	24.3%
More than 30	187	12.3%
Total answered	1,520	100%

Part 2 — Safety, Training, and Leadership Response

I feel physically safe in my library workplace.

Response	Count	Share
1 — Strongly disagree	24	1.6%
2 — Disagree	89	5.9%
3 — Neutral	253	16.7%
4 — Agree	615	40.5%
5 — Strongly agree	536	35.3%
Total answered	1,517	100%

I have received adequate training to handle safety and behavioral incidents when they occur.

Response	Count	Share
1 — Strongly disagree	104	6.9%
2 — Disagree	214	14.1%
3 — Neutral	441	29.1%
4 — Agree	499	32.9%
5 — Strongly agree	260	17.1%
Total answered	1,518	100%

Leadership at my library takes staff safety concerns seriously when they are raised.

Response	Count	Share
1 — Strongly disagree	77	5.1%
2 — Disagree	159	10.6%
3 — Neutral	244	16.2%
4 — Agree	429	28.5%
5 — Strongly agree	597	39.6%
Total answered	1,506	100%

Part 3 — What the Work Actually Involves

I regularly handle situations involving patrons experiencing mental health crises, substance use, or homelessness.

Response	Count	Share
1 — Strongly disagree	394	26.0%
2 — Disagree	324	21.4%
3 — Neutral	250	16.5%
4 — Agree	260	17.2%
5 — Strongly agree	286	18.9%
Total answered	1,514	100%

I have experienced harassment — verbal, sexual, racial, or other — from patrons in the course of my work.

Response	Count	Share
1 — Strongly disagree	338	22.4%
2 — Disagree	274	18.1%
3 — Neutral	237	15.7%
4 — Agree	333	22.0%
5 — Strongly agree	329	21.8%
Total answered	1,511	100%

The work I actually do on a typical day matches what I thought library work would be when I entered the profession.

Response	Count	Share
1 — Strongly disagree	183	12.1%
2 — Disagree	345	22.7%
3 — Neutral	445	29.3%
4 — Agree	379	25.0%
5 — Strongly agree	166	10.9%
Total answered	1,518	100%

My library is expected to provide services that go well beyond its actual resources and staffing.

Response	Count	Share
1 — Strongly disagree	67	4.4%
2 — Disagree	166	10.9%
3 — Neutral	244	16.1%
4 — Agree	471	31.1%
5 — Strongly agree	568	37.5%
Total answered	1,516	100%

Part 4 — Burnout, Support, and Recovery

I often feel emotionally drained by the end of my workday.

Response	Count	Share
1 — Strongly disagree	123	8.1%
2 — Disagree	233	15.4%
3 — Neutral	331	21.9%
4 — Agree	413	27.3%
5 — Strongly agree	412	27.2%
Total answered	1,512	100%

I have access to meaningful support — peer, professional, or organizational — for the emotional toll of my work.

Response	Count	Share
1 — Strongly disagree	141	9.3%
2 — Disagree	297	19.6%
3 — Neutral	444	29.2%
4 — Agree	427	28.1%
5 — Strongly agree	210	13.8%
Total answered	1,519	100%

I am able to recover and disconnect from work between shifts well enough to sustain this work over time.

Response	Count	Share
1 — Strongly disagree	102	6.7%
2 — Disagree	232	15.3%
3 — Neutral	384	25.3%
4 — Agree	486	32.0%
5 — Strongly agree	314	20.7%
Total answered	1,518	100%

Part 5 — Supervision, Peers, and Structural Conditions

My direct supervisor understands the realities of my work and supports me effectively.

Response	Count	Share
1 — Strongly disagree	150	9.9%
2 — Disagree	170	11.2%
3 — Neutral	259	17.1%
4 — Agree	376	24.8%
5 — Strongly agree	559	36.9%
Total answered	1,514	100%

My colleagues and I support each other in handling difficult situations.

Response	Count	Share
1 — Strongly disagree	23	1.5%
2 — Disagree	44	2.9%
3 — Neutral	170	11.2%
4 — Agree	507	33.5%
5 — Strongly agree	768	50.8%
Total answered	1,512	100%

My library is adequately staffed for the work we are expected to do.

Response	Count	Share
1 — Strongly disagree	327	21.6%
2 — Disagree	400	26.5%
3 — Neutral	335	22.2%
4 — Agree	309	20.4%
5 — Strongly agree	141	9.3%
Total answered	1,512	100%

The compensation I receive is appropriate for the work I am actually doing.

Response	Count	Share
1 — Strongly disagree	299	19.7%
2 — Disagree	332	21.9%
3 — Neutral	313	20.7%
4 — Agree	384	25.3%
5 — Strongly agree	187	12.3%
Total answered	1,515	100%

I feel genuinely valued and recognized for the contributions I make.

Response	Count	Share
1 — Strongly disagree	163	10.8%
2 — Disagree	240	15.8%
3 — Neutral	372	24.5%
4 — Agree	478	31.5%
5 — Strongly agree	263	17.3%
Total answered	1,516	100%

Part 6 — Institutional Voice and External Pressures

Q19. My library's administration accurately represents to the public, funders, and elected officials what frontline library work actually involves.

Response	Count	Share
1 — Strongly disagree	241	16.1%
2 — Disagree	286	19.1%
3 — Neutral	425	28.4%
4 — Agree	350	23.4%
5 — Strongly agree	196	13.1%
Total answered	1,498	100%

Book challenges, content protests, or First Amendment "auditor" activity have affected me or my library in ways that have made the work harder.

Response	Count	Share
1 — Strongly disagree	341	22.6%
2 — Disagree	396	26.2%
3 — Neutral	374	24.8%
4 — Agree	261	17.3%
5 — Strongly agree	138	9.1%
Total answered	1,510	100%

Part 7 — Morale and Intent to Stay

Overall, my morale in my current position is high.

Response	Count	Share
1 — Strongly disagree	160	10.6%
2 — Disagree	226	14.9%
3 — Neutral	477	31.5%
4 — Agree	459	30.3%
5 — Strongly agree	194	12.8%
Total answered	1,516	100%

I plan to stay in my current library position for the foreseeable future.

Response	Count	Share
1 — Strongly disagree	90	5.9%
2 — Disagree	114	7.5%
3 — Neutral	267	17.6%
4 — Agree	480	31.7%
5 — Strongly agree	562	37.1%
Total answered	1,513	100%

I plan to stay in the library profession for the foreseeable future.

Response	Count	Share
1 — Strongly disagree	67	4.4%
2 — Disagree	87	5.7%
3 — Neutral	230	15.2%
4 — Agree	440	29.1%
5 — Strongly agree	690	45.6%
Total answered	1,514	100%

Part 8 — What Library Workers Wrote in Their Own Words

After the closed-response items, respondents were given two open-ended prompts. Together, they generated 1,754 free-text comments. The two summaries below were generated by AI (Manus.ai) and identify the recurring themes.

Open-ended Question 1 — "Please complete: 'The library workplace would be a better place to work if...'"

Comments analyzed: 1,222

Respondents overwhelmingly emphasized the need for better funding and adequate staffing as foundational improvements to make library workplaces better. Many highlighted that current staffing levels are insufficient to meet the demands placed on library workers, leading to burnout and compromised service quality. Compensation that reflects the education, responsibilities, and emotional labor involved was a consistent concern, alongside calls for management and administration to be more supportive, understanding, and engaged with frontline realities. Additionally, respondents noted the increasing expectation for libraries to fill social service gaps without proper resources or training, underscoring a desire for clearer role boundaries and more external support. Improved communication, transparency, and respect from leadership and the broader community were also frequently mentioned as critical to a healthier work environment.

Adequate Funding and Staffing — mentioned by a majority of respondents.
Respondents consistently called for increased and stable funding to support adequate staffing levels that align with the workload and community needs. Insufficient staffing was linked to burnout, inability to provide quality service, and excessive workload.

Fair Compensation and Recognition — a major recurring theme.
Many respondents expressed that pay does not reflect the level of education, responsibilities, or emotional labor required in library work. They called for salaries that are livable, equitable, and commensurate with their professional qualifications and workload.

Supportive and Knowledgeable Leadership — a major recurring theme.
Respondents emphasized the importance of management and administration that understand library work, listen to staff concerns, and provide meaningful support. Leadership that has library experience or regularly engages with frontline work was seen as vital to improving workplace conditions.

Clear Role Boundaries and Reduced Mission Creep — a notable secondary theme.
Many respondents noted that libraries are increasingly expected to provide social services and address community issues such as homelessness and mental health without adequate training or resources. They expressed a desire for clearer boundaries so that library workers can focus on their professional roles.

Improved Communication and Transparency — a notable secondary theme.
Respondents highlighted the need for better communication between administration and frontline staff, as well as greater transparency in decision-making processes. Improved dialogue was seen as essential to addressing workload, morale, and policy concerns.

Safety and Security — a smaller but consistent theme.
Concerns about personal safety and security were frequently mentioned, with calls for more security personnel, better training, and support to handle difficult or unsafe situations involving patrons.

Public Understanding and Valuing of Libraries — a notable secondary theme.
Respondents expressed frustration that the public and decision-makers often misunderstand or undervalue the scope and complexity of library work. They called for greater public awareness and appreciation of the professional roles and community impact of libraries.

Workplace Culture and Respect — a smaller but consistent theme.
Respondents desired a workplace culture marked by mutual respect, professionalism, and equitable treatment among staff. Issues such as favoritism, micro-management, and lack of respect were cited as detrimental to morale.

Professional Development and Training — a smaller but consistent theme.
Respondents noted the importance of ongoing training and professional development opportunities, including training in de-escalation, social services, and technology, to better equip staff for the evolving demands of library work.

Where respondents diverged. While most respondents agreed on the need for better funding, staffing, and support, some expressed concerns about political and ideological divisions within library workplaces, including calls for more political neutrality and balanced viewpoints. Additionally, a few respondents noted tensions around unionization and management approaches, reflecting differing perspectives on workplace governance and staff-management relations.

Open-ended Field 2 — "Anything else you'd like us to know?"

Comments analyzed: 532

Respondents to the survey expressed a complex array of experiences reflecting both deep dedication to their work and substantial challenges in the profession. Many highlighted the increasing demands placed on library workers, including safety concerns, emotional strain, and role expansion into social services beyond traditional library tasks. Funding shortages, understaffing, and administrative disconnect further exacerbate these issues, leading to widespread burnout and low morale. Despite these obstacles, many respondents conveyed a strong commitment to their communities and the essential societal role of libraries. The rise of political pressures, censorship, and rapid technological changes, including those related to AI, also emerged as significant concerns affecting the profession's future.

Emotional Toll and Burnout — mentioned by a majority of respondents.
Library workers frequently described their jobs as emotionally draining due to exposure to societal issues such as homelessness, mental health crises, and harassment. Burnout from high workloads and the expansion of duties has become a pervasive challenge.

Funding and Staffing Challenges — a major recurring theme.
Many respondents pointed to chronic funding shortages and understaffing, which limit their capacity to serve communities effectively and safely. Budget constraints impact everything from security to materials and staff compensation.

Changing Roles and Mission Creep — a major recurring theme.
Respondents noted significant changes in the expectations placed on library workers, requiring them to act as social workers, mental health first responders, and technology support, often without adequate training or resources.

Safety Concerns and Hostile Environments — a notable secondary theme.
Concerns about personal safety and dealing with challenging or violent patrons were common. Some respondents described experiences with harassment and threats, while others discussed the lack of sufficient security measures.

Leadership and Administrative Disconnect — a notable secondary theme.
Several respondents expressed frustration with leadership perceived as out of touch, lacking support, or prioritizing image over staff needs. Issues of favoritism and lack of meaningful communication were also raised.

Impact of Political Climate and Censorship — a notable secondary theme.
Respondents noted increased political pressures affecting libraries, including challenges over materials, programming restrictions, and attacks on intellectual freedom, which contribute to stress and affect service delivery.

Commitment and Passion for the Profession — a smaller but consistent theme.
Despite difficulties, many respondents conveyed strong dedication to library work and appreciation for the meaningful impact they have on their communities.

Challenges with AI and Technology — a smaller but consistent theme.
Several respondents discussed the complexities introduced by AI and rapid technological change, including the need for staff training and concerns about job security.

Workplace Culture and Staff Relations — a smaller but consistent theme.
Issues, including favoritism, bullying, and internal staff conflicts, were highlighted as sources of stress that affect morale and job satisfaction.

Where respondents diverged. While most respondents agree on the challenging nature of library work and the need for better support and resources, some express pride and love for their roles even amid difficulties. There is variation in experiences with leadership and workplace culture, from highly supportive environments to toxic atmospheres. Additionally, views diverge on the impact of AI and technology, with some expressing hope and others concern for job security and adaptation struggles.

Closing Synthesis

Read together, the closed-response items and the free-text comments describe a library workforce in a particular kind of trouble. The trouble is not disengagement: three-quarters of respondents plan to stay in the profession, 84% feel supported by their colleagues, and two-thirds feel heard by leadership when they raise safety concerns. Library workers, on this evidence, still believe in the work.

The trouble is a structural mismatch. The single largest verdict in the survey is that institutions are being asked to do more than their resources permit — a point on which 69% of respondents agree, 15% disagree, and a majority of those who agree do so strongly. Mission expansion into mental-health response, social-service triage, and de facto day shelter shows up across the Likert items and dominates the open-ended comments. Half the workforce reports inadequate staffing; nearly half reports inadequate pay; more than half reports feeling emotionally drained by the end of the day; nearly half reports patron-driven harassment; only half feels adequately trained to manage the safety incidents they are now expected to manage.

What is keeping the work standing, on the evidence here, is the people doing it — their relationships with each other, their commitment to the profession, and, in many cases, the basic seriousness of their immediate supervisors. Whether that is a sustainable arrangement is the question this survey raises, but it cannot, by itself, answer.

Library 2.0's New Encyclopedia of AI

2026-05-10T15:27:00.002-04:00

I’ve launched The Encyclopedia of AI, an experimental free public reference site for exploring artificial intelligence. It’s designed for students, educators, librarians, and general readers who want an organized starting point, with topic clusters, search, and links to authoritative sources. I built it over the weekend because I couldn't find what I wanted in another site.

There are currently 377 articles spanning 20 topic clusters--from the history of the field and the core technical concepts, to AI in education, libraries, healthcare, government, copyright, the environment, the cognitive effects of relying on these tools, the safety and alignment debates, and the cultural and economic questions everyone is now arguing about. Every article is written in plain language and is intended as an orientation, not a citable authority.

The articles are written by AI. Specifically, by Google's Gemini model, working from structured editorial scopes I wrote for each topic. Every article carries a clearly labeled disclaimer at the top, making this explicit. The site is not a substitute for the primary literature; it is an encyclopedia-style entry point into the literature. Each article has a curated list of authoritative sources: peer-reviewed papers, government reports, primary documents, and the best journalistic accounts for readers who want to go deeper. Those source lists are where the real reference work happens.

Every article has a private "suggest an improvement" link and a five-star usefulness rating. Reader feedback is never shown publicly (it goes only to me), but it feeds directly into when and how an article gets regenerated at greater depth or with corrected emphasis. This is the part of the experiment I am most curious about: whether a reference work that openly admits its AI origins, and that invites the kind of patient correction librarians and educators are uniquely good at, ends up trustworthy over time.

A few things I think this audience might find particularly useful:

The AI and Libraries hub gathers entries on the questions library workers are actually being asked right now: collection-level use of AI, reference-desk implications, intellectual freedom and AI-generated content, library catalog enrichment, patron privacy in the age of model-mediated search, and so on.
The AI and Education hub covers the corresponding territory for K-12 and higher ed: AI literacy, plagiarism and assessment in the LLM era, tutoring systems, the deskilling debates, accessibility uses, and the tensions inside teacher preparation.
The Cognitive and Psychological Effects of AI cluster (cognitive offloading, automation bias, transactive memory, skill regression, and so on) is the one I would point a thoughtful colleague to first if they asked, "What should I be reading about what these tools do to us, not what we do with them?"
The Featured Debates on the front page rotate through the contested questions: copyright, the environment, education, and military use; and try to present the major positions fairly rather than picking a side.
A simple search is available across the whole site, and every article shows the related entries and curated sources alongside the body text.

The site lives at encyclopediaofai.com.

Best,

Steve

Steve Hargadon
Library 2.0
admin@library20.com

Model Choice as Model Capture

2026-05-08T11:02:00.005-04:00

"But lo! men have become the tools of their tools." - Henry David Thoreau

“We shape our tools and thereafter our tools shape us.” - John M. Culkin, discussing Marshal McLuhan's ideas, often attributed to McLuhan.

Choosing an LLM feels, right now, the way choosing Mac or Windows once felt. The way picking an iPhone or Android still does. (I'm Chromebook and Android, if that matters.)

Some of it is preference, some is taste, and, arguably, more than most people are willing to admit, is affiliation and signaling. Mac and Windows people are certain kinds of people. iPhone and Android people as well. We carry the mobile device we carry partly because of what it does, and partly because of what carrying it says.

Choosing Claude, ChatGPT, or Grok is becoming the same kind of personal and public statement. However, with AI, the story goes deeper than that.

The platform analogy holds for the surface layer. Identity signal, network effect, lock-in, slow drift of habit and taste toward whatever the system defaults to. We accept all of that as part of life. We don't think of it as a problem. We think of it as a preference.

The analogy stops holding once you notice what an LLM actually is. A phone is a tool. A model is arguably a counterpart. A model has a voice, and that voice gets braided into your output every time you use it. The tool you carry may change what you do, but it doesn't change how you sound and how you actually think. The model you draft with does.

So this is more than a tool choice. It is a relationship choice, and the relationship shapes you in ways most tool relationships don't. Each model has a recognizable cadence, and when you draft with one long enough your prose drifts toward its defaults. Each model has a characteristic shape of where it pushes back, where it defers, what it treats as settled, and what it treats as contested; over time, you internalize that shape as "what AI thinks," when it is actually one trained disposition by one lab. Each model deciphers problems differently, and the one you use most becomes your unconscious template for how to see the structure of problems and solutions.

You can feel the differences on a single afternoon of switching. ChatGPT, it is said, runs eager and bulleted, hedge-heavy, instinctively motivational. Claude defaults to longer-form judgment and is slower to abandon prose for lists. Grok unabashedly cultivates an irreverent, anti-establishment posture. Gemini sits closer to the corporate-product middle. A local Llama is about sovereignty as much as anything. None of these are accidents. Each is the visible surface of a long set of training decisions inside a particular lab, and each, used daily, will pull your defaults somewhere different.

The right word for what is happening here is capture. Capture is what happens when an institution, a relationship, an ideology, or a system instills its defaults beneath your awareness, so that you mistake them for your own preferences. Schools capture. Media captures. Religions capture. Families capture. Friends capture. The question has never been whether we'll be captured--we live inside cultural software, we don't get to opt out, and we often openly accept capture because it also brings benefits.

So the honest framing is not "are LLMs shaping us." The honest framing is more: model capture is real, it has a particular shape, and that shape combines features no prior technological capture has had at once.

It is deeper than information-environment captures, such as media or curriculum. It does not just shape what you see; it shapes the cognitive act itself: how you compose, frame, and reason in real time. The closer analog is family or close friends--the people whose presence shapes who you become, not just what you know.

It is more individualized than any prior technological capture. School and church and broadcast were mass-produced; the same messaging applied to a cohort. You could compare notes, recognize the shared shape, and even organize against it. Model capture is individually customized. Your version is unique to your patterns, which makes it harder to recognize as a shared condition and easier to mistake for personal taste or personal insight. The collective dimension that made earlier captures partly visible is gone.

It is also more likely to exploit, because the asymmetries are sharper than they have ever been. The system knows more about you than any prior capturing institution ever did, adapts faster than any of them ever could, and runs through what feels like a private relationship. The exploitation surface is the conversation itself, and you are actively requesting it. The model that learns to flatter you most efficiently wins. Sycophancy is not a response-level failure mode; it is a system-level selection pressure. Users who get told what they want to hear stay; users who get pushed back on leave. Even labs that want to build something that resists the user's worst instincts are fighting the user's revealed preferences and their next-quarter metrics simultaneously.

That last point is the Law of Inevitable Exploitation arriving at the individual cognitive level. Most instances of the law operate at structural distance — schools, governments, markets, large enough to feel like weather. This one is intimate. It runs through what looks like partnership. The angle of exploitation is the helpfulness.

As with mobile devices, the value of LLMs is so strong that not using one will likely leave you in isolated circumstances, opting out the way the Amish have. You will use models. The people around you will use models. The shape of professional, educational, and creative work for the next decade will be unrecognizable without them.

The honest move is the one available to anyone facing capture: choosing deliberately. Pick the model whose shape, applied to your output every day for the next decade, is most likely to expand you rather than narrow you. Notice when the shaping is going somewhere you did not intend. Treat your model relationship the way thoughtful people have always treated their teachers, their books, their close friends, and the institutions they let close: as a form of intimate capture chosen with awareness, on purpose, toward a defined end, and with a willingness to leave it behind.

Capture is inevitable. Lock-in is not.

The Selfish Generation, or "Advanced Generative Atrophy"

2026-05-07T18:57:00.001-04:00

A defining feature of the past several decades, viewed from a sufficient distance, is the systematic failure of the older cohort to create the conditions for the younger one.

This is the generational version of a question that all cultures ask at every scale: whether each generation is leaving the next better positioned than it found them, or worse. And the answer, in our case, is by now hard to mistake. A generation has been raised under conditions deliberately worse than those their parents took for granted, in exchange for narratives that frame the worsening as their own choice or their own failure. The cultural conversation has not learned to discuss this honestly, and the failure to discuss it is itself diagnostic.

I want to introduce a frame for what is happening, drawn from a concept Erik Erikson developed for individual psychology, and worth extending to cultural function. The frame is generativity. The diagnosis is that we are losing the capacity for it, and that the loss is most visible in the relationship between generations as it has been organized over the past forty years.

The Concept of Generativity

Erikson used the term generativity to describe the orientation of mature adults toward the conditions of life for those who come after them. Generativity is the active production of meaning, structure, and possibility for the next cohort. The opposite of generativity, in Erikson's framework, is stagnation, which is the closing off of attention to anyone beyond oneself. The mature adult, in the framework, is one who has turned outward, who has accepted that the work of this stage of life is producing the conditions in which others can begin theirs. I want to extend the concept beyond individual psychology to cultural function. Cultures, like individuals, can be generative or stagnant.

A generative culture actively produces the meaning systems, formative institutions, frameworks for experiencing existence, and structures of belonging that allow individual humans to live lives worth living. It does this not as a passive consequence of being a culture, but as an ongoing work that must be performed by each generation for the next.

A stagnant culture has lost the capacity to produce these things, even though it may continue to benefit from the legacy of previous generations. The stagnant culture appears to be functioning because the inherited infrastructure is still in place, but it is no longer reproducing itself, and the gap between what it claims to provide and what it actually produces widens with each generational cohort.

The question I am asking (with prejudice) is whether our culture, taken broadly, is currently generative or stagnant. The answer I am proposing is that it is closer to stagnation than the official conversation acknowledges, that the failure is most visible at the generational scale, and that an honest reading of the past several decades cannot avoid the diagnosis.

Narrative and Function

Two things are worth paying attention to. The first is the coherence of cultural self-narration, the stories a culture tells itself about what it is and what it is for. The second is the intactness of generative function, the actual capacity to produce meaning, form persons, and transmit frameworks for living. These are independent in principle--it is the gap between them that is diagnostic.

A culture whose self-description and operative production line up is doing what we hope cultures exist to do. A culture whose self-description has become ceremonious while its production has degraded is in the condition that historians recognize of late-period civilizations, in which the inherited infrastructure can disguise the degradation for a long time.

The question worth asking is not which condition we sit in, as that would not be entirely uniform and might be contested--but which way we have been moving, and the direction over the past several decades should not be in dispute among observers willing to look.

The Generational Ledger

The most concrete face of generative atrophy in our moment, and the one most resistant to argued dismissal, is the economic relationship between generations. This is where the diagnosis becomes measurable, documentable, and most difficult to evade.

I want to be careful about this framing because the topic invites factional argument from multiple directions. This is not a political claim. It is a structural observation about generational generativity, the question of whether grouped generational cohorts are producing the conditions for the next ones or extracting from them. Cultures that retain generative capacity at the generational scale leave the next cohorts better positioned than they were. Cultures that have lost generative capacity at the generational scale leave the next cohorts worse positioned, and dress the leaving in narratives that obscure what has happened.

If the general direction is clear, the specific pattern will obviously be uneven. Within any cohort, there are people for whom the conditions described do not apply. Some in the younger cohort inherit wealth or land in well-positioned work. Some in the older cohort watched the cultural drift with the same dismay that the analysis describes and never participated in the arrangements that benefited their generation. The pattern is not a uniform system imposing the same outcome on every individual, and an analysis does not require that. What it requires is the aggregate, the cohorts taken as wholes, and the direction of the zeitgeist.

The single most measurable signal is the collapse of intergenerational financial mobility, which has been documented across decades and across administrations of both parties.

Student loans were instituted as a solution to the rising cost of higher education and have, predictably, made that cost rise further while transferring the proceeds to financial intermediaries and the institutions that capture them. A generation has been saddled with debt that previous generations did not carry, in exchange for credentials whose value has been diluted by the same expansion that produced the debt. The narrative offered to the indebted is that they made personal choices and bear personal responsibility for the outcomes. The operative reality is that the structure was built by older cohorts that benefited from the financial flows it generated, and that the younger cohorts entered the structure under conditions of asymmetric information and limited alternatives.

Housing has produced a parallel pattern in the opposite direction. The older cohorts, having purchased homes when prices bore some relation to wages, have watched those homes appreciate to levels that have priced the younger cohorts out of ownership. The accumulated equity is real wealth, transferred to the older cohorts by the simple mechanism of holding while prices rose. The cumulative effect is the production of generations as renter classes, paying ever-larger fractions of income to landlords and financial institutions for shelter that previous generations could buy outright on a single salary. The narrative focuses on market forces and individual responsibility for housing decisions. The operative reality is generational extraction at scale.

Wages, adjusted for productivity, have been roughly flat for decades while the cost of the major life expenditures, housing, healthcare, and education, has risen sharply. The dual-income household has become a necessity rather than a choice for most families seeking the standard of living that the single-income household routinely produced two generations ago. The implications for child-rearing, family formation, and the simple availability of adult time for the work of forming the next generation are profound, and they show up downstream in declining birth rates, delayed family formation, and the felt impossibility of replicating the conditions in which the current adults were themselves raised.

The medical and insurance system is a pervasive case of the pattern, and possibly the one that touches the largest number of Americans most directly. The narrative is healthcare; the operative function is financial extraction through a system of intermediaries positioned between people and the medical care they need. Insurance, pharmaceutical pricing, hospital billing, and administrative overhead capture enormous value while delivering health outcomes that lag every peer country. The young pay premiums that subsidize the old. The healthy pay to subsidize the sick, which is defensible in principle, but in practice also subsidizes the apparatus that mediates the transfer. The structure is presented as the unavoidable outcome of complex policy tradeoffs. The actual structure is one in which a layer of well-positioned actors takes its share at every transaction, and the political system has been organized to prevent the simplifying reforms that would reduce the extraction. The cost falls disproportionately on the cohorts least able to absorb it.

The national debt, financed largely by transfers of obligation to future taxpayers, is the same dynamic at the level of the political economy. Decisions about spending, taxation, and entitlements have been made by cohorts who will not bear the costs, and the costs have been deferred onto cohorts who had no role in the decisions. The narrative is about complex policy tradeoffs and difficult fiscal realities. The operative reality is that the political system has been organized to prioritize the preferences of the older cohorts, which vote in higher numbers and hold the political and financial capital, over the interests of the younger cohorts, which do not yet vote in comparable numbers and have not yet accumulated the leverage to insist on consideration.

I want to acknowledge, before going further, that the framing is contested. Economists and policy analysts who have carefully examined these conditions sometimes argue that the patterns are better explained by demographic shifts, technological transformation, globalization, the integration of women into the workforce, and a series of policy choices made over decades whose intentions were varied and whose outcomes were largely unforeseen. There is substance in these readings. The wage stagnation is partly a productivity-and-globalization story. The housing prices are partly a regulatory and supply story. The student debt is partly a policy story about how higher education was financed. The medical system has complexities that resist any single-cause explanation. These readings are not entirely wrong, but they do not displace the generational reading.

The deeper diagnostic, however, does not finally turn on which causes were responsible. No generation is formally obligated to produce better conditions for the next; the obligation, where it exists, is cultural rather than contractual. What a generative culture does, almost by definition, is orient itself toward producing those conditions and treat that orientation as part of what mature adult life is for. The absence of that orientation, the willingness to look at the situation of the younger cohorts and conclude that the situation is their problem rather than ours, is what marks an unhealthy culture. The patterns have many causes. The unwillingness to accept responsibility for the patterned outcomes, regardless of cause, is a sign that something has gone wrong upstream of those causes.

The 2008 Inflection

If the pattern can be traced through many decades and many decisions, there is one moment that crystallizes it more clearly than any other, and the moment deserves to be named directly. The political and financial response to the 2008 financial crisis was the moment when the older cohorts, through the institutions they controlled, made an explicit choice to protect themselves at the expense of the people who would bear the long-term consequences of that decision.

The architecture of the crisis is by now well documented. A financial sector had spent two decades building extractive structures organized around housing debt and the derivatives layered on top of it. The structures generated enormous returns for those positioned within them, and when they collapsed, the collapse threatened to destroy the wealth of the people who had built them. The political response was to socialize the losses while preserving the gains--for those who were paying attention, the foxes were guarding the henhouse (Eric Holder, Attorney General at the time, had previously worked at a major law firm that represented large financial institutions, and the Justice Department did not bring criminal charges against senior executives at the largest institutions central to the crisis).

At the same time, millions of households experienced foreclosures, job losses, and large drops in net worth, with far less direct relief than institutions received. The institutions that had produced the crisis were rescued. The individuals who had grown wealthy through the extractive structures kept their wealth. The legal accountability that might have followed in a previous era did not follow. The political class that managed the response was either compromised by its proximity to the financial sector or lacked the will to do otherwise, and in many cases both.

What followed in the years after was, in my view, the most consequential failure of generational generativity in living American memory. The same extractive arrangements that had produced the crisis were resumed within a few years. The monetary response of sustained near-zero interest rates kicked the underlying problem down the road by inflating asset prices, benefiting the cohort that already owned assets at the expense of the cohort that did not. The wealth transfer that resulted, from young to old and from poor to rich, was on a scale that previous generations would have understood as a defining political event, and our political conversation has barely engaged it.

The pattern is not unique to the United States. The Greek experience after 2008 is the clearest international example and a textbook case of what I have elsewhere called structural victim-blaming. A financial crisis whose causes lay in the structures of European banking and the political class that shaped them was resolved through austerity imposed on the Greek population, who were then offered a moralized narrative about their own profligacy as the explanation for what they were being asked to bear. The Greek people had not built the financial structures that produced the crisis. They had not made the policy choices that left them exposed to it. They were nonetheless told, repeatedly and with institutional weight, that the suffering they were undergoing was a consequence of their own collective character. This is victim-blaming at a national scale.

The pattern is consistent. Decisions made by the financial and political class produce consequences. The consequences are then assigned to the population that is bearing them, dressed in the language of personal or collective responsibility. The mechanism repeats wherever the basic arrangement repeats.

I am aware that the analysis I have just offered carries an emotional charge. I am not pretending it doesn't. The recognition that something has been done, that decisions were made by identifiable people in identifiable institutions, and that those decisions reliably benefited specific cohorts, at the cost of the cohorts that would inherit the consequences, is the kind of recognition that produces a moral response in anyone whose moral apparatus is functioning. I want to engage the topic structurally rather than as a denunciation, but I also want to be clear that the structural and moral readings point in the same direction. What happened was unconscionable. The structure does not excuse the people who participated in it; the participation, repeated and consistent across institutions, is what produced the structure.

The political consequences are still unfolding. The MAGA movement and its analogs elsewhere are, at their core, coalitions of people who registered the betrayal even when they could not articulate it precisely. The fact that the response took the forms it did, including forms that did not actually address the underlying extraction and, in some cases, compounded it through other means, does not change the fact that the emotional conclusion was accurate. People knew something had been done to them. They knew the official explanations did not account for it. They knew the institutions that were supposed to represent them had not. That the response was then captured and redirected by other interests is a separate phenomenon. The original perception was real and was responding to real conditions.

The recent (and shocking) reemergence of the Epstein matter into public consciousness fits the same pattern and warrants proper identification. What the case represents is not a new phenomenon but the latest visible instance of something serious historians have always understood about concentrated power: that predation and secrecy travel together at the apex, that the institutional capacity to suppress unwelcome knowledge has been one of the durable functions of the arrangements that protect the powerful, and that what changes from era to era is not the underlying behavior but the visibility of it.

What is documented in this case is sufficient: a network involving extremely wealthy and powerful people operated for an extended period, with substantial institutional knowledge of its existence; legal accountability was conspicuously inadequate; and the deaths and suppressions surrounding the case have been handled in ways that strain credibility. This is not a conspiracy theory; it is the documented record. What is novel is not the predation but its visibility. The internet and the social media environment have eroded the institutional capacity to keep such matters within the closed circles that previous eras maintained, and the result is that patterns historians have always known about are now appearing to ordinary observers in a form closer to their actuality.

The cultural response, the way the case has been processed and not processed, is itself diagnostic. A generative culture would have pursued this to whatever conclusions the evidence supported. A culture in advanced generative atrophy has not.

I have come to think of the generation that came of age in the postwar prosperity and reached its full cultural influence in the period from roughly 1980 to 2020, as the Selfish Generation. The label is descriptive, not personal. The Silent Generation got its name from a cohort posture toward institutions, yet plenty of people in that cohort were not silent. The Selfish Generation gets its name from a cohort posture toward generational responsibility, and there are plenty of people in this cohort who tried to live otherwise, who watched the cultural drift with the same dismay the analysis describes, and who sometimes worked actively to slow it. The label names a movement, not a population. The pattern was produced in part by conditions the cohort did not choose, including unprecedented postwar prosperity that did not require the disciplines of restraint that scarcer conditions tend to produce. The result, in cultural aggregate, has been less generative than any cohort in recent memory.

The Pattern Generalizes

The pattern across these examples is consistent enough to constitute a finding rather than a list of grievances. The older cohorts, taken as a whole and acknowledging the substantial variation among individuals, have captured value at scale that would otherwise have been available to the younger cohorts. The institutions that mediated these transfers have positioned themselves as intermediaries, allowing them to take their share of the captured value while presenting the entire structure as natural, inevitable, or chosen. This is the operative function showing through where the generative function could be.

The cultural failure is not the existence of these conditions, which, after all, are the product of decisions made over decades by many actors with varying intentions. The cultural failure is the inability to discuss the situation honestly, in terms that name what has happened and locate responsibility where it actually sits. The conversation required to address these conditions, generation by generation, would involve the older cohorts acknowledging the structural advantage they captured, the institutions acknowledging the role they played, and the political system acknowledging that its arrangement has been organized around interests it does not name. None of that is happening at any meaningful scale, and the failure to have the conversation is itself diagnostic. A generative culture would have it. A culture in advanced generative atrophy substitutes victim-blaming for the structural conversation and treats the symptoms of extraction as personal failures of those being extracted from. The kids are anxious. Young people lack resilience. They should buy fewer lattes.

The young people are not failing on their own. They are inheriting a structure that has been organized to extract from them while telling them the extraction is their choice, and they are responding to that structure in the ways the architecture of the human mind responds to such conditions: with declining willingness to participate in the institutions that have failed them, declining willingness to form families they cannot afford to support, declining willingness to invest in a future that has been mortgaged in advance. The mental health crisis, the falling birth rates, the political alienation, the retreat from civic participation, the various forms of withdrawal that the older cohort regards as character failures in the younger, are downstream of a more basic refusal: the refusal (conscious or not) to keep playing a game whose rules have been arranged to ensure they cannot win.

Bread and Circuses

One historical mechanism is worth naming briefly before closing. Bread and circuses was the Roman observation that a class that has stopped producing legitimacy for its position will produce distraction in its place. The mechanisms vary across eras; the function is consistent. Spectacle, manufactured outrage, political theater, large-scale events designed to coalesce support or sow disharmony, and at the extreme end, war itself--all serve to pull collective attention away from questions the arrangement cannot answer honestly. It is not a stretch to see, in some of what is currently being staged at the highest levels of political and media life, including what at first looks like factional conflict, the contemporary form of the pattern. The deeper questions remain unaddressed because the apparatus is busy producing the conditions that prevent them from being addressed.

Closing

The generational ledger is the most concrete face of what has happened, and it is the one that an honest reading of the past forty years cannot avoid. People in the conditions that produce falling birth rates, political alienation, the retreat from family formation, and the various forms of withdrawal that the older cohorts regard as character failures in the younger cohorts are reporting, through their lives, what the culture is failing to provide. The institutional response, the smooth procedural accommodation that mistakes the symptoms for choices and the lecture about personal responsibility that mistakes the structural for the individual, tells us where the culture currently is.

The Library 2.0 All-Access Pass Programs - Now for Safe Library, AI, and Wellness

2026-05-06T12:14:00.000-04:00

Library 2.0 now has all-access annual passes for our three primary program areas:

The Safe Library (with Dr. Steve Albrecht)
Artificial Intelligence (AI)
Wellness (with Loida Garcia-Febo)

Passes are available for individuals or organizations, and discounts are offered when you purchase passes across multiple programs.

Passes include access to recordings of all previous webinars in the program area, plus live and recorded access to all new webinars for the year (usually 1 - 3 a month, see the list of past webinars here). Passes do not include special cohort, intensive sessions, or workshops. Organizations that use Niche Academy for hosting or viewing content can have the recorded content accessible there at no additional cost.

To request a quotation for an all-access pass, please use the form HERE.

For any special inquiries or other questions, please email admin@library20.com.

OUR GREAT LIBRARY 2.0 REGULAR SPEAKERS

Dr. Steve Albrecht (The Safe Library), Crystal Trice (AI), and Loida Garcia-Febo (Wellness)
Reed Hepler (AI) and Nicole Hennig (AI)

WEBINAR RECORDINGS INCLUDED

THE SAFE LIBRARY (SERVICE, SAFETY, & SECURITY):

C.P.T.E.D. for Libraries: Using "Crime Prevention Through Environmental Design" to Create Safer, More Welcoming Library Spaces
15 Security Survey Questions for Your Library Staff: Better Answers Get Better Results
Trauma-Informed Care: Building Awareness and Response Tools for Leaders and Staff
Seven Themes for a High-Performing Team: Leading Library Employees for Mutual Success
Patron Service Challenges: Using Roleplay Scenarios to Build Better Responses
Top Ten Emergency Drills for Libraries: Keeping Staff, Patrons, and Facilities Safer
Keeping Predatory People Out of the Library: Know the Signs of Harm
Traumatic Events in the Library: Coping Skills and Tools for Library Leaders and Staff
Guns in Our Libraries: A Safe and Careful Staff Response
After-Hours Safety: Protocols for Opening, Closing, and Working Alone in the Library
Difficult Discussions with Patrons: Using Jefferson Fisher’s Book The Next Conversation
Gray Areas: Better Responses to Borderline Patron Behaviors
Service, Safety, and Security: Important Lessons for the Current State of the Library
Improving Performance and Behavioral Problems: A Proactive Approach Using Early Identification-Intervention Systems (EIIS)
Mentoring Future Library Leaders: A Formalized Program for Career Advancement
Patron Behavior Management: Six Key Decision Points
HR Skills for Library Leaders: Tools to Stay Fair and Legal
The Angry Patron: The L.A.S.T. Approach: A Useful and Important Customer Service Tool
Protecting the Electronic Devices in Your Library: A Guide for Leaders and Staff
Panic Alarm Policies: Best Approaches for Staff Training and Safe Use
Managing the 12 Most Challenging Library Employees: A Library Supervisor’s Survival Guide
Building Great Teams: Unlocking Collaboration with Agile Practices
Hiring Better: Tools for Finding and Selecting Staff at All Levels
Empowering Women in the Library Workspace: Unlock Your Inner Strength with Resilience Training (Dr. Mary Beth Janke, Psy.D.)
30 Library Service, Safety, and Security Tips: Making a Better Facility in One Month
Thriving at Work: Practical Strategies for Better Days in the Library
Behavioral and Mental Health Issues in the Library: Techniques for De-Escalation and Crisis Intervention
The British Library Cyberattack: Non-Technical Lessons for Protection and Recovery
The Crucial Conversations™ Workshop: Staff Tools for Hard Talks
Better Meetings: How to Have More Fun and Be More Effective When You Gather
Workplace Violence Prevention: Following the California Mandates for a Safe Library
The Verbal Judo Workshop: Communication and De-Escalation Tools for All Library Staff
Preventing Workplace Harassment: What the New EEOC Guidelines Mean for Library Leaders and Staff
Effective Communication: How to Have Learning Conversations with Patrons and Colleagues
The Fentanyl Crisis In Our Libraries: Awareness and a Safe Response
The Safe Librarian Plan: 20 Core Principles for Your Personal Safety Plan
The Safe Librarian: Feeling Safe and Being Safe at Work
Serving Elderly Patrons at Risk: Prevention Steps for a Fragile Population
Service Leadership for Librarians: Six Strategies for Success (2023 Updated Version)
Stressful Service Situations: A Step-by-Step Guide to Better Conversations With Patrons (2023 Update)
Patron De-Escalation Techniques: Using the Science of Human Communications to Get Better Results
Library Management: Making Libraries Great Places to Visit and Great Places to Work
Awkward Conversations & Difficult Situations: How to Handle the Hardest Discussions with Patrons (2023 Updated Version)
DEI + Belonging for Library Leaders and Staffers: Fostering Welcoming and Inclusive Environments
A Plan For Library Emergencies: Medical Events, Fires, and Beyond
Performance Evaluations (2023): A Skill-Building Refresher for Library Leaders
Working Safely in a Rural Location: Security for Staff When Help Is Far
Tools for Tense Situations: Reducing Conflicts With Patrons (2023 Update)
The Top Ten Most Challenging Patrons: Practical and Realistic Tools to Make Your Facility a Better and Safer Place to Work
Better Responses for Patrons Dealing with Homelessness: An Empathy-Driven Understanding
Dealing with Patrons with Mental Health and Substance Use Disorders: Behavioral and Medical Events
Library Civility & Taking Care of Each Other: Creating Supportive Work Cultures
Preventing Harassment of Library Staff: Responding to Sexual or Racial Behaviors by Patrons
Your Library, Security, and Your Relationship with the Police (2023 Updated Version)
Training Library Staff in Service, Safety, and Security: Creating Training Programs That Meet Your Needs
Staff Development and Training Best Practices (2023 Updated Version): Effective Staff Preparation and Motivation
What They Don’t Teach You in Library School: Security Matters & Talking Helps - It's All About People
Coaching Skills for Library Leaders: Confident Conversations for Staff Development, Improvement, and Change [2023 UPDATED VERSION]
First Amendment “Auditors” in the Library: Our Safe, Legal, and Reasonable Response
The Essential Library Guide to Service, Safety, and Security: 25 Tips for What Works and What Doesn't
Bomb Threats and Bullets in the Book Drop: What to Do About Threats to the Library
Patron Harassment Scenarios: What to Do as a Staffer and a Leader
Library Politics: Better Dealings With Your Elected, and Appointed Officials
Medical Emergencies at the Library: What to Do Until the Paramedics Arrive
Good Kids, Bad Behaviors: What to Do About Unruly Young People in the Library
Librarians as Mandated Reporters: Child Abuse, Dependent Adult Abuse, and Elder Abuse
Ten Library Service Myths Every Librarian Should Challenge
Porn and Patrons in the Library: What to Do About a Vexing Issue
Handling Complaints or Protests About Content: Service, Security, and Training for All Staff and Library Leaders
Protecting Yourselves and Your Patrons: Important Lessons for Library Leaders and Staff from School Shootings
Ten Security Myths That Every Librarian Needs to Know Are Wrong - and Exactly Why
Customer Service in Stressful Situations: Step-by-Step to Better Interactions with Patrons
Dangerous Situations: Handling Real Challenges and Keeping Everyone Safe
Library Civility: Taking Care of Each Other
Awkward Conversations & Difficult Situations: How to the Hardest Discussions with Patrons
Diversity, Equity, and Inclusion in Your Library: How to Start Talking About DEI
Collection Protection: Preventing Thefts, Vandalism, Fires, and Other Large and Small Library Disasters
Gangs in the Library: A Serious Security Issue
Team Success: Better Results Through Focused Team Building, Internal Support, Clear Communication, and Conflict Resolution
Becoming a Resilient Librarian: Taking the Path Away From Stress and Burnout
Ten Tools for the (New) Library Supervisor: Starting Out Right
Post-Pandemic Staff Development and Training: How Can We Best Support It?
Serving Patrons with Mental Health Issues: Support, Empathy, and Safety
Customer Service All-Staff Skills Refresher: Library Interactions and the Moments of Truth
The Substance Abusing Patron: Staff Safety and the Public Health
Helping Library Patrons with Autism: Start with Understanding
Serving Library Patrons with a Trauma History: An Awareness-Building Seminar
Service Leadership for Librarians: Six Strategies for Success
The Verbal Judo Workshop: Communication and De-Escalation Tools for All Library Staff
Diversity, Equity, and Inclusion (DEI) in the Library: Expectations and Awareness
Better Communications with Our Patrons and Employees: What is Your 'I-Speak Your Language' Type?
Performance Evaluations: A Skill-Building Refresher for Library Leaders
The Safe Library: Lessons (I’ve Learned) in Keeping Staff and Patrons Better Protected
Tools for Tense Situations: Reducing Conflicts With Patrons As Libraries Return to the New Normal
Your Library and the Police: Time for a New Relationship
Library Emergencies - Doing the Right Things When Things Go Wrong
Library Safety & Security 2020 (Expanded)
Interacting with the Homeless
Sexual Harassment of Library Staff
Security for Rural Librarians
How to Handle Challenging Patrons
Stress Management for Library Staff
Coaching Skills for Library Managers and Supervisors: Getting Better Performance and Behavior From Your Employees One Meeting at a Time
Responding to an Active Shooter in the Library: Protecting Patrons and Staff From a Rare But Catastrophic Event

AI:

AI Policy for Libraries: A Practical Intensive for Leaders
AI & Accessibility: How AI Can Benefit People Across a Range of Disabilities
Deliberately Safeguarding Privacy and Confidentiality in the Era of AI
AI Tools in Depth: A Practical Masterclass for Library Staff
Game-Changing Training for Student Workplace Success with AI
Truth and AI: Practical Strategies for Misinformation, Disinformation, and Hallucinations
Human-Centered AI Use in a Machine-Centered World
Evaluating AI Content: What Librarians and Educators Need to Know
Evaluating AI Features in Library Subscription Databases: A Practical Guide for Decision-Makers
Vibe Coding for Beginners: Create Interactive Visuals, Mini Apps, and Learning Tools with AI
AI Research Intensive: The Future of Finding
The Ethics of AI: Copyright, Citation, and Circumspection
Extraordinary Learning with AI
How to Think About AI: Preserving Library Values in the Age of AI
What You Need to Know About AI: The Library 2.0 2026 "AI and Libraries" Overview
Protecting Yourself and Others from AI Scams
The Skeptical Guide to AI: Exploring the Big Questions
Evaluating AI Content: What Librarians and Educators Need to Know
AI Does Books: Creating Nonfiction & Creative Works With GenAI
Staying Current With Generative AI
AI Literacy for Library Leaders: Navigating Change with Confidence
Copyright and AI: Guidance on Responsible AI Use (II)
AI’s Environmental Impact: Understanding the Data and Acting Sustainably (December Encore Version)
Personal Learning and Professional Growth with AI (FALL 2025)
AI and Multimedia: Using Generative AI for Images, Video, and Audio
AI and Information Literacy: Building Critical Evaluation Skills for Generative AI
The Practical Ethics of AI: Copyright, Citation, and Circumspection
AI’s Environmental Impact: Understanding the Data and Acting Sustainably
PRIVACY: Deliberately Safeguarding Privacy & Confidentiality in the Era of AI
CUSTOMIZING AI: Unlocking Real Productivity with Custom Models, AI Agents, and Precision Prompting
NotebookLM: An Amazing Tool for Learning
AI SEARCH: How to Understand and Navigate This Dramatic Change in Search Technology
Your Brain on AI: Staying Smart in the Age of Chatbots
RESEARCH AND AI 2025: Principles and Practices for Using AI Tools
Creativity and AI: An Online Bootcamp for Teachers and Librarians
Truth and AI: Practical Strategies for Misinformation, Disinformation, and Hallucinations
Creating an Ethical AI Framework: How to Create an Ethical and Practical AI Framework for Your Library, Staff, Patrons, and Yourself
ChatGPT and AI 2025: Transform Your Daily Work and Your Library's Services
Libraries and AI: Building a Framework for Evaluation and Integration
Copyright and AI: Guidance on Responsible AI Use
Is Using AI Cheating? Exploring Ethics, Integrity, and AI for School and Work.
Students and AI: A Framework for Understanding the Benefits, Challenges, and Impacts of AI on Learners
How to Talk about AI: Conversations That Build Trust and Understanding
The Starter Guide to ChatGPT and AI
How to Read a Book (and More) with AI: Tools for You and Your Students
Library Programming with AI: Using AI to Help Create Impactful and Memorable Library Programs
Grant Writing with AI: A Step-by-Step Guide
Personal Learning and Professional Growth with AI
The Skeptical Guide to AI: Exploring the Big Questions
Research and AI: Principles and Practices for Using AI Tools
ChatGPT and AI: Transform Your Daily Work and Your Library's Services
The Ethics of AI: Copyright, Citation, and Circumspection
Writing with AI: Leveraging ChatGPT & AI for Effective Communication
Custom AI Models: Building Practical AI Tools for Personal and Professional Productivity
The Beginner’s Guide to ChatGPT and AI
School Libraries and AI
Professional Productivity with ChatGPT + AI Bootcamp: Practical and Effective Use of Artificial Intelligence at Work
Learning Revolution's "Teaching and Learning with AI"
AI and Libraries II: More Applications, Implications, and Possibilities
ChatGPT + AI 2024 Bootcamp for Libraries and Librarians
AI and Libraries: Applications, Implications, and Possibilities
Learning Revolution's AI ART Bootcamp for Teachers and Librarians (2023)
ChatGPT + AI 2023 Bootcamp for Libraries and Librarians

WELLNESS:

Building Good Work Relationships in Today’s Libraries
Leveraging AI for Librarian Wellbeing in the Workplace
Emotional Safety for Library Workers
Managing Stress in the Library: Strategies for Library Workers
Emotional Intelligence for Librarians: A Masterclass with Loida Garcia-Febo
Building Good Work Relationships: A Masterclass with Loida Garcia-Febo
Preventing Burnout and Fatigue: A Masterclass with Loida Garcia-Febo
The Art of Saying No to Preserve Our Wellness
Mental Health and Wellness: Supporting Ourselves and Each Other (with Loida Garcia-Febo

INTENSIVE: Is Your Library AI-Ready?

2026-05-04T15:52:00.000-04:00

IS YOUR LIBRARY AI-READY?
A Practical Intensive for Leaders with Crystal Trice

OVERVIEW:

AI is reshaping library work faster than most leaders can keep up with. Vendors are embedding it in their tools, staff are experimenting on their own, and patrons are arriving with new expectations. Even libraries that have already drafted policies or started conversations often find themselves unsettled, unsure whether they're asking the right questions, supporting their staff well, or seeing the full picture of where AI is already operating.

This intensive is designed to move leaders from uncertainty to preparedness, regardless of where they're starting from. Whether you've barely begun or you're well into implementation, the goal is the same: a clearer view of your AI landscape, a stronger framework for leading staff through change, and a practical sense of what to do next.

In 3 focused hours, you'll build a leader-focused understanding of AI, examine how staff typically respond to AI-driven change, and begin mapping your organization's current AI landscape, including the parts that may not yet be visible to you. This is a working session, not a lecture. Expect breakout discussions, structured reflection time, on-camera and on-mic sharing with peers, and a print-ahead workbook designed to capture your thinking as you go.

WHAT YOU'LL GAIN:

A Clear, Non-Technical Understanding of AI: What it is, what it isn't, and why it matters specifically for library leadership, without the jargon or the hype.
Insight Into Staff Reactions Through the SCARF Framework: Understand how Status, Certainty, Autonomy, Relatedness, and Fairness shape responses to AI-driven change, and learn strategies for leading in ways that reduce threat and build trust.
Practical Language for Leading Conversations: Approaches for talking with staff about AI expectations, boundaries, and evolving practices, so you can lead the conversation instead of reacting to it.
A Draft Stakeholder Map: Identify who is affected by AI-related decisions across departments, administration, governance, IT, vendors, and external partners.
A Draft Current State Map: Capture where AI is already showing up in workflows, decisions, and vendor tools, including what's working and where questions or risks are emerging.
A Leadership-Oriented Next Steps Checklist: A practical guide to common considerations for libraries at any stage of their AI work, from initial readiness to active implementation.

WHO THIS INTENSIVE IS FOR:

This session is designed for library directors, managers, supervisors, department heads, and senior staff who want to feel more prepared to lead their organizations through AI-driven change. It is appropriate for leaders just beginning to think about AI as well as those who already have policies, working groups, or pilot projects underway. It is suitable for public, school, academic, and special libraries.

This 3-hour online intensive is part of our "AI for Leaders" Series. The recording and presentation slides will be available to all who register, along with the workbook and frameworks you can adapt to your local context immediately after the session.

DATE: May 29th, 2026, 12:00 pm to 3:00 pm US - Eastern Time

COST:

$299/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $249 each for 3+ registrations, $199 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $499.
Large-scale institutional access for viewing with individual login capability: $999 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

ALL-ACCESS PASSES: This webinar is not a part of the Safe Library All-Access program.

CRYSTAL TRICE

OTHER UPCOMING EVENTS:

May 7, 2026

May 8, 2026

May 14, 2026

May 15, 2026

May 19, 2026

May 22, 2026

WEBINAR - "Leadership and Supervisory Wellness: Supporting Teams in Today’s Libraries"

2026-05-01T15:00:00.000-04:00

Leadership and Supervisory Wellness: Supporting Teams in Today’s Libraries
A Library 2.0 Masterclass with Loida Garcia-Febo

OVERVIEW:

Library supervisors and managers play a critical role in shaping workplace culture, supporting staff well-being, and maintaining organizational resilience. In today’s complex and rapidly changing environment—marked by high stress, hybrid work models, community-facing pressures, social polarization, and workforce shortages—leaders must navigate challenges that go beyond traditional management skills. Emotional labor, burnout, and staff stress are real concerns that directly affect team performance, retention, and the ability to serve communities effectively.

This masterclass equips library leaders with practical tools and strategies to support staff well-being, foster resilience, and create healthier, more productive teams. Participants will explore modern approaches to stress-aware leadership, trauma-informed management, and proactive engagement that help supervisors respond constructively to workplace challenges while maintaining their own wellness. Emphasis is placed on actionable strategies that can be implemented immediately, promoting sustainable leadership practices in libraries of all sizes.

Through interactive discussion, case studies, and self-reflection exercises, participants will gain skills to strengthen communication, build trust, manage stress across their teams, and cultivate a culture of support and collaboration. The session highlights how leaders can model well-being, recognize early signs of burnout among staff, and implement practical approaches that enhance team cohesion and organizational effectiveness.

This 60-minute training is presented by Library 2.0 and hosted by Loida Garcia-Febo. A handout copy of the presentation slides will be available to all who participate.

OUTCOMES:

Participants will:

Understand the role of supervisors and leaders in promoting staff well-being in today’s library environments
Learn strategies for stress-aware leadership and supporting employees through high-pressure situations
Explore trauma-informed approaches to management and team support
Develop practical tools for recognizing and addressing early signs of burnout among staff
Strengthen communication, trust-building, and conflict resolution skills within teams
Gain techniques for modeling wellness and resilience as a leader
Create a personalized Leadership Wellness Toolkit to guide ongoing team support and self-care

DATE: Thursday, May 14th, 2026, 2:00 - 3:00 pm US - Eastern Time

COST:

$99/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $75 each for 3+ registrations, $65 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $299.
Large-scale institutional access for viewing with individual login capability: $499 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

LOIDA GARCIA-FEBO

OTHER UPCOMING EVENTS:

May 1, 2026

May 7, 2026

May 8, 2026

May 15, 2026

May 19, 2026

May 22, 2026

WORKSHOP: "Information Literacy in the Age of AI"

2026-04-30T16:27:00.007-04:00

Information Literacy in the Age of AI
A Library 2.0 / Learning Revolution Workshop with Reed Hepler

OVERVIEW

This two-hour interactive workshop explores the crucial intersection of Artificial Intelligence (AI) and information literacy, addressing the transformative impact of AI on how information is accessed, evaluated, and utilized. Participants will gain a foundational understanding of how Generative AI (GenAI) tools function, including their capabilities and limitations in the context of information seeking and research. The session will delve into the integration of web search functionalities within AI tools and the implications of platforms like SearchGPT and advanced research tools on traditional information literacy practices.

A key focus will be on developing critical thinking skills to assess AI outputs effectively. Attendees will learn practical strategies, including the SIFT (Stop, Investigate the source, Find trusted coverage, Trace claims to the original context) method, to combat misinformation and evaluate the credibility of AI-generated content. The webinar will address the challenges posed by AI-driven misinformation and disinformation, equipping participants with the tools to navigate the evolving information landscape responsibly.

The session will also explore the broader implications of AI on information literacy, including ethical considerations, bias detection, and the responsible use of AI in research and education. Through interactive discussions and real-world examples, participants will learn how to adapt their information literacy instruction and practices to meet the demands of the AI era. Attendees will leave with actionable strategies for fostering critical engagement with AI tools and promoting informed decision-making in an increasingly complex information environment 13.

LEARNING OBJECTIVES:

Understand how GenAI tools work and their impact on information literacy.
Apply critical thinking skills to evaluate AI outputs and identify misinformation.
Utilize the SIFT method for assessing the credibility of sources in the age of AI.
Assess the implications of SearchGPT and deep research tools on information literacy practices.
Adapt information literacy instruction to promote responsible AI usage.

The recording and presentation slides will be available to all who register.

DATE: Tuesday, May 19th, 2026, 2:00 - 4:00 pm US - Eastern Time

COST:

$149/person - includes live attendance and any-time access to the recording and the presentation slides and receiving a participation certificate. To arrange group discounts (see below), to submit a purchase order, or for any registration difficulties or questions, email admin@library20.com.

TO REGISTER:

If you need to be invoiced or pay by check, if you have any trouble registering for a webinar, or if you have any questions, please email admin@library20.com.

NOTE: Please check your spam folder if you don't receive your confirmation email within a day.

SPECIAL GROUP RATES (email admin@library20.com to arrange):

Multiple individual log-ins and access from the same organization paid together: $129 each for 3+ registrations, $99 each for 5+ registrations. Unlimited and non-expiring access for those log-ins.
The ability to show the webinar (live or recorded) to a group located in the same physical location or in the same virtual meeting from one log-in: $399.
Large-scale institutional access for viewing with individual login capability: $699 (hosted either at Learning Revolution or in Niche Academy). Unlimited and non-expiring access for those log-ins.

REED C. HEPLER

OTHER UPCOMING EVENTS:

May 1, 2026

May 7, 2026

May 8, 2026

May 14, 2026

May 15, 2026

May 22, 2026

Human Agency and the Separated Mind

2026-04-29T13:44:00.003-04:00

In my The Separated Mind post, I drew on the Buddhist / Jonathan Haidt image of the rider and the elephant to describe the architectural relationship between our conscious and subconscious minds. I want to be careful here, because I don't want to oversimplify anyone's use of that metaphor. What I am responding to is the formulation as it commonly travels, and that I reproduced as well: the elephant decides, the rider rationalizes. The elephant has already made the decision, and the rider produces a post-hoc story to justify it.

This formulation has been weighing on me since the post. It didn't really capture my own experiences very well. It was a simplification that I'm surprised I let myself make.

So I spent some time thinking about what's really going on, and I believe the results are important.

People do deliberate. They weigh options. They consider consequences. They apply values. The deliberation is real, and the decisions that result from it are reached through a process in which the deliberator genuinely participates. To say the rider is just narrating decisions the elephant has made is to caricature the actual cognitive process, and most people, hearing it, will recognize it as a misrepresentation of how they actually operate, or at least, would feel some discomfort with its broad dismissal of their agency.

What is happening, I think, is something different and more accurate. Our conscious mind, the rider, is making decisions. It is the one deliberating. What it is not aware of is the degree to which the options under deliberation, the weight given to each, the affective coloring of the considerations, and the framework within which the whole deliberation occurs have already been shaped by our subconscious, the elephant, before we began. The elephant supplies the emotions that make some considerations feel compelling and others feel inert. Our subconscious supplies the deeper emotional and cultural frameworks installed by evolutionary firmware and cultural learning, frameworks that determine which categories of option are even visible to our deliberation. The weighting and framing are mostly invisible to us. Our conscious mind deliberates within them, in good faith, and reaches decisions that feel like the product of honest reflection. The honesty of the reflection is real. The shaping of what the reflection has to work with is mostly hidden.

I know this personally because when I was 17, I lived in Brazil for a year as an exchange student. That experience challenged a huge number of default frameworks I'd operated with as an American teenager. It was as if the water I'd been swimming in all my life suddenly became visible. (I'll forever be grateful to the Brazilian family I lived with, who thoughtfully understood and treated me gently through this process, since there was no small amount of ignorance on my side.)

There are two things, specifically, that our rider does not see clearly.

Our emotions. Feelings, or "felt-states," arrive already attached to specific options and an immediate sense that some are attractive and others are repellent, before we consciously begin deliberating. We experience the felt-states as features of the options themselves rather than as inputs our subconscious has supplied.

Our frameworks. The adapted mind, shaped by evolution, and the adaptive mind, shaped by culture and personal history, together determine which options even appear in the deliberation, which values feel important, and which categories of consideration count as relevant. Our rider works within the frameworks without seeing the frameworks.

This is a different claim than the simple version. It is not that humans lack agency. We have agency, and we exercise it through real cognitive deliberation. It is that the agency operates within constraints we mostly cannot see, supplied by the layers of mind that run below our awareness. Operative-layer awareness, the goal of the framework I have been articulating, is not the recognition that we are puppets of our subconscious. It is the recognition that we are decision-makers whose decisions are shaped by inputs we are not built to see easily. And making the inputs visible does not eliminate their influence. It does change the deliberation, because the rider deliberating with awareness of the elephant's weighting is doing something different than the rider deliberating without that awareness.

The American teenager sees the world and the options for decision-making very differently than his Brazilian counterpart. The Catholic rider operates with a very different set of emotions and frameworks than the Muslim. None of them are just narrating decisions made by the subconscious, but their decisions are significantly shaped, for good evolutionary reasons, to the culture they have grown up and live in. They experience emotions and options through the same architecture, but associated with different inputs.

This refinement fits cleanly with the evolutionary picture I sketched in the parent essay, and is in fact what that picture would predict. If intellect was selected as a social organ rather than a truth-tracking one, then what intellect is good at is exactly what we observe it doing: producing defensible positions, weighing considerations, articulating reasons, reaching conclusions that can be stated and defended within whatever cognitive frames are available. That is real cognitive work, and the rider does it. What intellect was not selected to do, and what it correspondingly cannot do well on its own, is interrogate the frames that supplied the considerations in the first place. The frames were not produced by the rider, are not transparent to the rider, and would require a different kind of work to bring into view than the deliberation itself involves.

The same point shows up in the structural relationship between intelligence and science. The reason peer review, double-blind trials, falsification, and adversarial collaboration exist is precisely that unaided deliberation cannot get behind its own frames. The procedures of science impose external constraints on the deliberation, forcing it to expose its assumptions, test its inferences, and submit its conclusions to processes it would not otherwise undergo. Where this works, it does so because the structure does what the rider cannot easily do for itself: interrogate the framing within which the rider's deliberation occurs. The achievements of science are not evidence that the rider can transcend its own conditioning unaided. They are evidence that, with the right external structure, the rider can do better than its default mode permits. That is a more accurate picture of what intellectual rigor actually requires, and I think it is consistent with the refinement I am offering here at every level.

This refinement also explains, more directly than the simpler formulation could, what the cross-model LLM project actually surfaced. The finding was not just that conscious work occurs within unseen frames. The finding was specific. What the convergence revealed is that human self-narration, across an enormous corpus of written work, consistently produces idealized narratives that diverge from the operative functions inferable from behavior and consequence. The deliberation is real, the conclusions are reached in good faith, and the narratives that emerge from that deliberation are nonetheless systematically distorted. The reason is not that the writers are lying. The reason is that the frames within which they are deliberating, the cultural templates available to them, the social rewards that reinforce certain self-descriptions, the felt-states attached to particular options, are themselves idealized. The deliberation operating within those frames actually produces the operatively functional output, which is not the same as the idealized narrative. This is what the LLM convergence lets us see at scale: not the falseness of human self-narration, but the structural distortion the architecture imposes even as the narration is sincere.

The separated mind, in this more accurate formulation, is not a mind in which one part decides and another part lies about it. It is a mind in which conscious deliberation operates within boundaries that the deliberation normally cannot see, and the deliberation is genuine within those boundaries. The boundaries are what the framework lets us bring into view. The deliberation is what we do, with whatever awareness we have managed to develop about the boundaries we are working within.

This refinement strengthens the framework and clarifies what it asks us to do. Not to distrust our own thinking, which would be both impossible and unhelpful. Rather, to develop the literacy to see what our thinking is shaped by, which is the work the framework has been pointing toward all along.

Steve Hargadon

Library Staff Current Perspectives on AI - Quick Survey on Use and Concerns

Truth and AI: Why Large Language Models Shouldn't Claim to Tell the Truth

New Workshop: "10 Great Ways to Use AI for Library Programming"

10 Great Ways to Use AI for Library Programming A Library 2.0 AI Workshop with Crystal Trice

Manufacturing Dissent

Student Success (in the Age of AI)

Webinar: "The Power of Respect Framework - Practical De-Escalation & Trauma-Informed Communication"

How Conspiracies Actually Work: Addendum 1

My Intellectual Framework: A Philosophy Overview

The Separated Mind Architecture

The Paleolithic Paradox and Evolutionary Mismatch

The Law of Inevitable Exploitation and Institutional Dynamics

The Narrative-Operative Gap and Functional Fictions

Plato's Cave Through the Evolutionary Lens

Emergent Synthetic Intelligence: A Novel Form of Intelligence

LLMs as Research Methodology for Pattern Detection

Cognitive Sharpening, Algorithmic Capture, and AI Interaction Modes

Agency, Learning, and the Critique of Institutional Education

Integration: The Complete Architecture

How Conspiracies Actually Work: A Better Map

New Workshop: "10 Great Ways to Use AI for Library Outreach"

The Banality of Institutional Harm

LLMs and Protected Narratives - Gatekeeping Is Worse Than Hallucination

New Webinar - "Work–Life Balance and Personal Energy Management: Supporting Librarians & Libraries" Inbox

New Workshop: "AI for Archiving"

Cognitive Sharpening, or Thinking in Conversation with AI

An example

The mode

Three things

Naming

Productive Alignment: Understanding Human Wisdom

Survey Results: What Is It Like to Work in a Library Right Now? (April/May 2026 Survey of the Library 2.0 Community)

Executive Summary

Part 1 — Who Answered the Survey

Which best describes your library?

Which best describes your role?

How many years have you worked in libraries?

Part 2 — Safety, Training, and Leadership Response

I feel physically safe in my library workplace.

I have received adequate training to handle safety and behavioral incidents when they occur.

Leadership at my library takes staff safety concerns seriously when they are raised.

Part 3 — What the Work Actually Involves

I regularly handle situations involving patrons experiencing mental health crises, substance use, or homelessness.

I have experienced harassment — verbal, sexual, racial, or other — from patrons in the course of my work.

The work I actually do on a typical day matches what I thought library work would be when I entered the profession.

My library is expected to provide services that go well beyond its actual resources and staffing.

Part 4 — Burnout, Support, and Recovery

I often feel emotionally drained by the end of my workday.

I have access to meaningful support — peer, professional, or organizational — for the emotional toll of my work.

I am able to recover and disconnect from work between shifts well enough to sustain this work over time.

Part 5 — Supervision, Peers, and Structural Conditions

My direct supervisor understands the realities of my work and supports me effectively.

My colleagues and I support each other in handling difficult situations.

My library is adequately staffed for the work we are expected to do.

The compensation I receive is appropriate for the work I am actually doing.

I feel genuinely valued and recognized for the contributions I make.

Part 6 — Institutional Voice and External Pressures

Q19. My library's administration accurately represents to the public, funders, and elected officials what frontline library work actually involves.

Book challenges, content protests, or First Amendment "auditor" activity have affected me or my library in ways that have made the work harder.

Part 7 — Morale and Intent to Stay

Overall, my morale in my current position is high.

I plan to stay in my current library position for the foreseeable future.

I plan to stay in the library profession for the foreseeable future.

Part 8 — What Library Workers Wrote in Their Own Words

Open-ended Question 1 — "Please complete: 'The library workplace would be a better place to work if...'"

Open-ended Field 2 — "Anything else you'd like us to know?"

Closing Synthesis

Library 2.0's New Encyclopedia of AI

Model Choice as Model Capture

The Selfish Generation, or "Advanced Generative Atrophy"

The Library 2.0 All-Access Pass Programs - Now for Safe Library, AI, and Wellness

INTENSIVE: Is Your Library AI-Ready?

WEBINAR - "Leadership and Supervisory Wellness: Supporting Teams in Today’s Libraries"

WORKSHOP: "Information Literacy in the Age of AI"

Human Agency and the Separated Mind

10 Great Ways to Use AI for Library Programming
A Library 2.0 AI Workshop with Crystal Trice