The subhed on that Politico story above gets the election right in crediting “safety hawks, populists, and child-safety advocates” who united to oppose AI companies and their data centers in the midterms. But Politico got the main headline terribly wrong. These are not “AI doomers.” AI doomers are the AI cultists who, paradoxically and illogically, claim their own technology could doom humankind — and that’s why they should be given unfettered control over it.

The doomers are the bad guys. But Politico’s headline said the bad guys won because that’s how these bad guys skew the language around AI and corrupt discourse about it. The result is that the top AI technologists and investors talk at 180-degree cross-purposes to media, policymakers, and the public. When they say “safety” it’s not how the rest of us define “safety.” Same for “regulation,” “humanity,” “doom,” even “future.”

Their intent is to confuse public discourse, and it works, making us think that when we say “safety” we’re discussing the same idea. We’re not — witness that Politico headline and too much credulous media coverage of AI.

So it is time to provide a helpful glossary contrasting the AI boys’ language with ours.

Future vs. “future”

What we mean: Next month, next year, next election, maybe next generation — time reasonably understood to be under our influence.

What the AI cultists mean: Their faux philosophers are no slouches. They work at Oxford — or worked; one of them, Nick Bostrom, was ousted with his Future of Humanity Institute when racist emails in his past were exposed. His fellow traveler, William MacAskill, wrote What We Owe the Future, published by Hachette, a textbook for the ideology they call Longtermism: that the future that matters is whatever affects the 10-to-the-54th future human beings yet to come. Their implication is that what bedevils us in the present — whether injustice or inequity, plague or Holocaust — pales in comparison to anything that would hinder the happiness of all those future beings.

These technocrats are utilitarians who contend they can calculate and affect total happiness. That is what leads to such noxious thinking as this from one of their number: Here, a New York Times profile of Anthropic cofounder Dario Amodei perfectly illustrates the poison fruit of Utilitarianism.

In a blog post for GiveWell that year, Dr. Amodei discussed a decision to give away $10,000. He was choosing to donate to either the Stop TB Partnership, which focused on preventing adult tuberculosis, or VillageReach, which helped vaccinate children in African villages.

The Stop TB Partnership, Dr. Amodei wrote, was superior in “cost-effectiveness” because it served adults and “adults are capable of deeper and more meaningful experiences” than infants. “I think an adult death is perhaps 2 or 3 times worse than an infant’s death,” he added.

He thinks he can judge which humans are more valuable. That is the bridge that connects Utilitarianism and Longtermism to eugenics: the making of the Übermensch.

Human vs. “human”

What we mean: Us.

What the AI cultists mean: They mix the tenets of technology and philosophy, claiming they can use computers to build better humans — that indeed, human and machine will merge and become one in what they call the singularity. That is their doctrine of Singulatarianism.

Their quest begins with the chips that cultist extraordinaire Elon Musk wants to implant in heads, leads next to the humanoid robots Musk plans to sell (instead of his punchline-on-wheels, the Cybertruck), and ends with the belief that human psyche can be uploaded to machines and live forever and everywhere.

That encapsulates their belief in Extroprianism: that the mind can transcend the limits of the body. It also speaks to their version of a philosophy called Rationalism: when future humans think not like the base animals we are but instead rationally, like, well, algorithms. When the AI boys build what they call neural networks, some think they are building brains.

And that is how Bostrom gets to his magic number of 10-with-54-zeroes future human beings. They’re not like us. They’re not us. They are humans as machines, machines as humans, better than us: Übermaschinen.

Environment vs. “environment”

What we mean: Our dear Earth.

What the AI cultists mean: The universe, which they contend they can and will colonize with their human/machines. That is why Musk obsesses about Mars. This is called Cosmism.

Altruism vs “altruism:

What we mean: Unselfishly thinking and generously acting on behalf of others’ needs.

What the AI cultists mean: You’ve no doubt heard of “effective altruism” (EA), another of the AI cultists’ philosophies. This one was made infamous by Sam Bankman-Fried, convicted crypto fraudster and proponent of EA.

In the beginning, EA sounded reasonable enough, motivating the well-to-do to focus their charitable generosity on acts that will cause the most good. The example always used is buying mosquito nets to save lives. Who can nitpick that?

Ah, but when you follow this Utilitarian string — maximizing good — to its extreme, mixing in other of these zealous philosophies along the way, you throw out the mosquito nets and the African children saved by them in favor of investments that will benefit Bostrom’s Übermenschen: technologies like superintelligent AI. These effective altruists believe they know best how to invest society’s wealth and so they should have more of it. These altruists aren’t so altruistic after all; they are greedy money-grubbers and this is their wealth gospel.

Doom vs. “doom”

What we mean: ’Bye, all.

What the AI cultists mean: Their machines will become so intelligent, so powerful, so uncontrollable that they can destroy humankind. This is the thesis of Bostrom’s famous paperclip scenario, in which machines told to make nothing but paperclips will turn every resource on earth into paperclips, never mind humans’ needs for energy and oxygen: Clippy’s revenge.

There’s another variant on Doomerism from its primary prophet, Eliezer Yudkowsky, coauthor of the Doom bible, If Anyone Builds It, Everyone Dies: Why Superhuman AI would Kill Us All (also cynically published by Hachette). Cheery fellow. He loves the idea of superhuman AI but fears that if it is built badly and backfires, it could destroy humankind before it serves Bostrom’s future beings. Thus Yudkowsky says all AI should be stopped until we’re ready, else it should be destroyed with thermonuclear weapons so the remaining humans can learn their lesson and pick up work when they’re ready. This he calls safety.

Safety vs. “safety”

What we mean: Since the seminal Stochastic Parrots paper in 2021, AI safety has been clearly defined, focusing on harm to the environment (resources and climate), economy (labor and cost), public discourse (bias and disinformation). It is not complicated; so clear AI can grok it. I asked AI (Gemini) to summarize the paper’s definition [its emphasis]: “For the authors, ‘AI safety’ is not about preventing an autonomous AI takeover; it is about preventing real-world harm to human beings — especially marginalized populations — caused by irresponsible data practices, resource consumption, and the uncritical deployment of large-scale statistical models.” Right.

What the AI cultists mean: If we take all the related isms I’ve mentioned thus far — Transhumanism, Extroprianism, Singulatarianism, Cosmism, Rationalism, Effective Altruism, Longtermism — and put them together, it spells TESCREAL, an acronym coined by Stochastic Parrots coauthor Timnit Gebru with Émile Torres. Here is their paper that explains these faux philosophies and their roots in eugenics.

And that is what makes up the foundation of the AI cultists’ definition of safety: managing the all-powerful AI they are building so it does not, one way or another, destroy humankind. Safety to them has nothing to do with environmental damage, childhood safety, or disinformation. It’s all about doom.

This bit of dictionary disarray comes home to roost in media coverage of AI “safety,” as when The New York Times reports on a gathering hosted by the Future of Life Institute (FLI) that attracted odd bedfellows Bernie Sanders and Steve Bannon — without once mentioning that FLI is funded by known doomers and that “safety” went undefined. Through such coverage, the doomers — AI boys of one stripe or another — gain legitimacy.

The same problem arises when some employee leaves an AI company to supposedly blow the whistle on a lack of attention to safety there. We think they mean safety in our definition and reporters never ask them to define it. If they bothered, they’d find that often these departees are doomers.

Media and policymakers are blind to the cultists’ dangerous nuttiness because they successfully hide behind virtuous words — safety, altruism, and regulation — whose meanings they have hijacked and mangled.

Regulation vs. “regulation”

What we mean: Government intervention in an industry or activity to ensure a mandated level of transparency and accountability to the public good.

See, for example, Mallory McMorrow’s proposal to regulate AI, calling for transparency and testing, export controls, and humans in charge. We can and should debate the particulars, but that is a sane starting point.

What the AI cultists mean: The so-called frontier AI companies — Anthropic and OpenAI — say they favor regulation. But in their plan, this means they write the regulations to favor themselves and exclude start-up and open-source (open-weight) competitors. This is classic regulatory capture.

They also tout their self-regulation, with Anthropic putting forth its “constitution” for AI, asserting that they can make machines (which can’t count the Rs in “strawberry”) operate according to high principles. OpenAI has proposed frankly naive plans for world bodies to oversee AI.

Some AI boys, led by VC Marc Andreessen, are accelerationists. They believe any regulation hindering the progress of AI is evil. As Andreessen wrote in his breathless techno-optimist manifesto: “Technology is the glory of human ambition and achievement, the spearhead of progress, and the realization of our potential…. We can advance to a far superior way of living, and of being…. We believe intelligence is the ultimate engine of progress. Intelligence makes everything better…. We believe Artificial Intelligence is our alchemy, our Philosopher’s Stone — we are literally making sand think.”

The serious problem with all the definitional disconnects I’ve outlined here is that without agreement on what harm is to be mitigated, it is impossible to hold a meaningful debate over how to regulate it, how to hold its makers and users accountable while sharing the fruits of this impressive technology.

Intelligence vs. “intelligence”

What we mean: Don’t know. That is why the first book I commissioned for the Bloomsbury series I am editing, Intelligence: AI & Humanity, is by Dr. Rumman Chowdhury, who will examine this human construct in the context of history, where it has been used to exclude and has inspired a mania to measure what remains an abstract concept. To my mind, intelligence is that which defines humanity.

What the AI cultists mean: They think it is easy not only to define intelligence but to build it and set benchmarks for it. Not just that, they think they can build machines that will beat human intelligence by any measure. They call this Artificial General Intelligence (AGI)— general in the sense that it can do anything we can do — or Artificial Superintelligence (ASI) — super in the sense that it can do all that better than we can. The frontier companies headed for their trillion-dollar IPOs say they’re nearly there, that their generative AI chat machines will soon be so damned smart they can build and improve on themselves.

OpenAI’s Sam Altman and others in the field treat intelligence as a commodity their companies can make, own, and sell, as if from a vending machine. That is their utmost dehumanization of us all.

There are AI people who are not in the cult, thank goodness. One I admire is Yann LeCun, who believes that language-based generative models will take development of AI only so far. He favors real-world models that learn the laws of physics and are built for and limited to specific, controllable functions, rather than becoming the everything machine. He also is an advocate of open-source, open-weight AI to spur competition and innovation. Another proponent of world models is Fei-Fei Li.

I wish scientists and contrarian builders like LeCun would get more attention in media coverage of AI. I wish scholars like Gebru would be called upon to give audiences context on the outlandish claims of the AI boys. I wish journalists would press those AI boys on definitions inherent in those claims. I wish they would stop allowing the boys to anthropomorphize their machines — as if they have motives and morals — and stop doing so themselves. And when writing about AI, I wish they would discard the AI boys’ dictionary in favor of Webster’s.

This American election was indeed a repudiation of AI and its data centers. But I say data centers are merely the McGuffins of the drama — that is, tangible symbols of the actual objects of dislike and distrust: the AI oligarchs and billionaires who wield their wealth in our elections, who threaten to destroy humankind (and demand the power to do so), who are generally jerks, and who maim the language to obfuscate their own intent.

I think AI is an amazing and promising technology whose opportunities we have just begun to explore. I cohost two podcasts about AI (Intelligent Machines and AI Inside) and, as I said, I’m editing a book series to bring the humanities into the discussion about it. But I say the wrong people are in charge of this technology, and those people are conning the journalists and politicians who should see through them to stop them from ruining it for us all. Start with clear language.

As I finished writing this, I returned to Politico and found that the editors (or A/B testing or AI) thought better of the headline above. This is how a later version read:

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It is time to end government and politics built around this stubborn minority of old white men, a demographic that amounts to less than a quarter of the adult population across the country, about 10 percent if one adds the South as a factor. It is time to build government instead around the pluralistic majority that won this election.

Here, from my book The Gutenberg Parenthesis is sociologist William Kornhauser’s definition of a pluralistic society — apt guidance for us today:

It is also time for the left in power in states across the country to support and rebuild education. One might argue that the uneducated voted this way because they have harder employment and economic prospects and feel left behind. Maybe. I prefer to think that education itself has salutary effects on citizens, making them less vulnerable to attempts to sway them towIt is also time for the left in power in states across the country to support and rebuild education. One might argue that the uneducated voted this way because they have harder employment and economic prospects and feel left behind. Maybe. I prefer to think that education itself has salutary effects on citizens, making them less vulnerable to attempts to sway them toward fear, bigotry, and hate because of their ignorance. And so the education I support is not just vocational, it emphasizes the humanities and social sciences: education for education’s sake, widening the mind, ennobling the individual.

Here are the numbers from The Times’ analysis focusing just on voters with no more than a high school education. You will note that every category shifted left. But majorities in many categories of voters still stayed behind, in the red:

• men by 9 points,
• white voters by 26 points,
• white men by 34 points,
• white women by 17 points,
• men over age 45 by 7 to 10 points,
• white men over age 45 by 40 points.
• white Southerners by 46 points.

Yes, make gas and groceries cheaper. Get rid of Trump’s tariffs and war if possible. Root out corruption. Release the damned Epstein files. Get ready to expand the Supreme Court. Impeach half the executive branch. All that.

But first and foremost: Educate, educate, educate.

Even as I celebrate the emergence — the victory — of our pluralistic society in this election, The Times has twice in a week dismissed “identity politics,” arguing that if candidates don’t say “vote for me because I’m a ____”, it’s dead. This is willful blindness on the part of The Times, a profoundly conservative (not Republican) institution that defends status quo power and institutions such as itself. Still, The Times itself cannot stop covering its vision of identity politics, showing its priorities and worldview. Whom does the #BrokenTimes rush talk to after this great pluralistic election? The great variety of voters who won? No, old white men in the South:

Let’s be clear about one thing: Black voters saved Democracy’s ass. If the Democrats don’t use their power to assure voting rights and erase the Republicans’ racist policies, they will have every right to say, “Next time’s on you all.”

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Practically every day on the socials, under the hashtag #BrokenTimes, I bring receipts to my claim that The New York Times is failing us and democracy. I do not wish to join in the cacophony from the Trumpists about “fake news.” To the contrary, I do this hoping to hold The Times to account and make it better. As we approach the critical midterm elections, here are just a few examples of The Times’ failures so far on one day — October 30, 2026.

In the lamentable tradition of The Times and #ButHerEmails, the paper has been harping this week on its story about two Dan Sullivans in the Alaska senatorial election. Its primary source for the supposed investigation of perfectly legal acts retracted all that she told The Times, but it went ahead with the story anyway. On this day, the Democrat, Mary Peltola, responds to its accusations and says she knew nothing about “tricking voters.” Look at the home-page block above — with a magnifying glass — and you can see how The Times played that: hidden as an also-ran heading under its live blog. By midday, even that small note had fallen off the home page, where earlier in the week the original story was emblazoned all the day long. So determined is The Times to deliver its hatchet job.

The Times looks at the world through Republican-colored glasses. You can see that on the home page and above in its coverage of the South Carolina senatorial race, covering it from the perspective of Darline Graham rather than that of the opponent that could pull off this upset, Dr. Annie Andrews.

That is even more the case in The Times’ coverage of my congressional district, NJ-7, where the paper devotes a long puff piece about disappearing nepo-Rep. Tom Kean Jr., even though they could not get an interview — or returned email — from him. The Times calls him “press-shy.” He’s also constituent-shy. His opponent, Rebecca Bennett, is not mentioned until the very end, after much ink about the “esteemed” Kean family’s history starting the nation, about Kean’s “grasp of policy and an instinct to work back channels, if not a mic”, and his “mild, under-the-radar manner.”

And through whose lens is The Times covering California’s gubernatorial race this day? Through that of the Republican, Steve Hilton.

In Michigan — as my cohost on our Breaking the News podcast, Julie Roginsky, said today — The Times is setting the Democrats up for a fight or fall by portraying Abdul El-Sayed as the standard-bearer for “the left’s potency heading into the next presidential contest.” This critical race isn’t critical enough, it has to represent something bigger: a trend.

The big story after election day will be whether elections still stand: whether the Republicans will undermine or refuse to accept the vote. This is where The Times fails us most profoundly: by refusing to recognize the dire gravity of democracy’s fall. Here, it covers the merely “unusual” election-year activity of the Justice Department. It’s far more than unusual. It is election interference, voter disenfranchisement, authoritarianism. But if The Times refuses to call lies lies, it is even more adverse to calling fascism fascism and reporting on it.

Instead, The Times leaves it to the alien oligarch in our midst, Elon Musk, to declare the risk to democracy if … [checks notes] … Democrats win. Who the hell decided that The Times should give such serious, indeed even-handed coverage of Mr. Musk’s “extensive rationale for his involvement to date” in attempting to buy elections? Editors like to think that their super power is what we call “news judgment.” That is terrible judgment.

The Times loves polls and predictions. I contend that prediction is not journalism; it does nothing to inform the electorate but could influence elections. And as for polls, I often quote the late Columbia Prof. James Carey, who cautioned that opinion polls preempt the public discourse they are intended to measure. I wrote about that in The Gutenberg Parenthesis:

Now is prime season for polls. The day before, The Times had Nate Cohn putting forth four predictions for how the Congressional races could turn out, all signifying nothing. And today:

This would imply that the pollsters do not want to believe polls that do not show Trump winning.

The real issues that concern voters, the polls tell us, are corruption and prices. On this day, The Times acts as if it is representing the Little People by counting how many millionaires there are in the Senate. Well, if any of them own a home and are lucky enough to have a 401K these days, that might put them over the line to be called millionaires in an inflationary economy. I wonder how many editors at The Times are millionaires.

Let’s round out this day with The Times with another angle on the news: Melania Trump. It’s not enough that The Times has swallowed her propaganda whole, giving her credit over the Pope for a local cease fire in Ukraine. They wanted another excuse to repeat it over again, so they turned to the reliably cringe-inducing Vanessa Friedman to break the news that Melania’s new coat is not black and white but brown.

The republic may be teetering on the razor’s edge of fascism, but at least it’s comforting to know that she wasn’t wearing a tan suit.

And as I write this, The Times’ day is not yet done.

See also this very good video by journalist Jonathan Katz. We are singing in harmony, in a minor key.

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At least one New York Times journalist — columnist Michelle Goldberg — has at last begun covering the real AI story: not the technology but the technologists and their cult of faux philosophies that lead them to claim Promethean powers to destroy humanity. With their self-fulfilling prophesies of extinction, the AI boys grab the attention of unwary media and policymakers while distracting from the real costs and dangers — and benefits — of the machines they make.

The calls of doom have been coming from inside the AI house, though Goldberg notes that coverage of them — which I will critique here — is “incomplete, because it doesn’t account for tech leaders’ messianic dreams.” In recent columns, another Times columnist, Georgetown computer science Professor Cal Newport, has begun to explore the AI boys’ insane philosophies. “This exaggerated grimness,” Newport writes, “makes it easy to overlook the more immediate harms created by these technologies…. The time has come to push back.” He says their nihilistic doom trolling has to stop.

That’s a start. I wish their coverage would go deeper by citing the work of Timnit Gebru and Émile Torres, who catalog the AI cult’s full range of creeds under the acronym TESCREAL — for Transhumanism, Extroprianism, Singularitarianism, Cosmism, Rationalism, Effective Altruism, and Longtermism. Nevermind the specific doctrines. What is worthy of your — and media’s and policymakers’ — attention is that Gebru and Torres show how all these beliefs have their roots in eugenics.

Goldberg does note that some of their plutocratic adherents quote fascists and Nietzsche. Their goal is to select Übermenschen as they play God, building mythical, supposedly conscious “artificial general intelligence” and “superintelligence;” transforming themselves into man-machines with chips in their heads; using AI to help them live forever; populating Mars and the universe beyond with their progeny; and claiming responsibility for the future, never mind today’s trivial concerns. These überwealthy zealots have the resources — technology, capital, celebrity— and access to power to pursue their fevered, fascist dreams. 

That is scary shit. But that’s not the scary shit we see covered in news media.

Instead, news media lap up the AI overlords’ claims of suprahuman power. Right across The Times’ home page from Goldberg and Newport, editors regurgitate whole the doomsters’ pronouncements without bothering with basic reporting, finding other authorities who disagree. Where is bothsidesing when we need it?

Next, The Times gives unchallenged top-of-homepage prominence to Anthropic CEO Dario Amodei’s call to slow down AI development. 

What’s wrong with that? you ask. Much, I say. 

• First, journalists unquestioningly accept as gospel the doomers’ assertions that their creations are capable of such danger, while there are many who believe these claims are just a perverse form of macho marketing meant to demonstrate to investors how very powerful and valuable they are. 
• Second, this is classic regulatory capture: The “frontier” AI companies call for regulations that they will help lawmakers draft, which will raise the bar for entry into their market for the open and international startup competition we so badly need to challenge them. 
• Third, the doom scenarios seduce click-hungry media into giving them free publicity and that lures equally dupable politicians — Bernie Sanders and Ted Lieu leading the pack — to call for simplistic, instant solutions: namely unplug AI. Meanwhile, vestigial pro-business Republicans wait for Trump’s inscrutable instructions. See how The Times practically scolds pols for not panicking enough:

Out of all this arm-waving, either nothing will happen or Anthropic and OpenAI will succeed in blocking new competitors while getting ultrawealthy on their IPOs. And few pay attention to the real perils these technologies raise for the environment, labor, education, and culture. 

There’s another critical risk: that we all lose the opportunity to develop and put to use these promising, often impressive technologies in medicine, science, carefully considered educational applications, and daily life. Such is always the peril of moral panic. 

I am not an AI doomer, as you will surmise. Neither am I an AI accelerationist: “Damn the torpedoes, warp speed ahead.” Having studied the history of technologies related to media in my books, I recognize lessons from the past: that disruptive technologies, especially those related to speech, induce panic at first; that before long the public comes to harness new technologies; that the technologists and their power eventually fade into the background; and that, with fits and missteps, society figures out how to make good use of its machines. We did it with movable type, steam, electricity, and electronics, and I believe we’ll get there with the internet. We can figure out AI, too. 

AI in its many flavors — large language models are just one limited instance — are proving to be amazing. In some areas — analysis of proteins, possibly theoretical math, perhaps medicine discovery, and certainly coding — they are surpassing human ability. But that by no means is any indication of either general or super intelligence. To me, AGI is just another abbreviation for BS. I hold that artificial general intelligence is a wasteful goal fueled by the hubris of the AI boys. As the sane AI pioneer Yann LeCun instructs, machines programmed and trained to perform specific tasks will be faster and cheaper to build — and control — than some fabled, all-powerful überbrain of Oz.

I believe we should understand what these technologies can and cannot do and cover them accordingly. That is why I cohost two podcasts — AI Inside and Intelligent Machines — to keep up on the news. This is also why I am editing a series for Bloomsbury Academic — Intelligence: AI & Humanity — to invite scholars and writers from the humanities and social sciences to this critical conversation, for they are not heard enough.

Our first book in the series will be by Rumman Chowdhury, an expert in AI ethics and governance. She will examine our definitions of intelligence over time. What fascinates me about AI’s entry into public discourse and culture is that its presence forces us to reexamine our own ideas of intelligence, creativity, art, learning, trust, labor, the firm, and even — in the case of the AI cultists who claim deific powers — religion. (See this relevant interview with Inken Prohl in Die Zeit: “With AI, we have created a religion.”)

Coverage of AI in mainstream media is consistently appalling. It too often accepts the PR of the AI boys — whether utopian or dystopian, accelerationist or doomster — without challenge, skepticism, or balance. When the AI boys talk about “AI safety,” journalists rarely exhibit the sophistication to ask whether that is safety in the common sense (environmental, educational, cultural) or in the AI cultists’ overblown sense (doom and extinction). 

When we hear of episodes of supposed AI agent “swarms” going “rogue” and “hacking” into systems, journalists use scare words to pump up the drama by attributing malign motives to overgrown calculators. Worse, they give us incomplete reporting. They should be asking what the AI companies fail to tell us. In the case of the OpenAI/Hugging Face incident, we need to know what the company told its model to do before we can decide whether it disobeyed those instructions. We also deserve to know how OpenAI let its system go unmonitored for so long. Instead of just accepting the AI CEOs’ versions of the story, we need to demand greater transparency, and that will come only through tougher reporting. 

Media’s anthropomorphism badly clouds the discussion. Let’s be very clear: AI does not think. It calculates. AI is not conscious or sentient. AI has no sense of meaning. It has no motive and no sense of right or wrong, thus it is not lying or cheating. If it breaks laws or norms, we likely should hold responsible those who programmed or instructed it. 

We need journalists to do more rigorous and skeptical reporting, to study lessons from the history of technology, and to seek out scholars and experts rather than just taking the word of AI’s CEOs, VCs, and disaffected nerds. The end result is that policymakers and the public are ill-equipped to both use and judge these technologies. 

And we are using them. According to the Pew Research Center, more than half of Americans aged 18–49 say they interact with AI at least once a day — even as they express growing unease unto antipathy toward the technology and the data centers it runs on. The South Korean government will provide AI access to all citizens for free: universal AI as a right. Artificial intelligence is here to stay; there is no turning it off. We deserve the right to have a voice in how AI is developed, governed, and used. 

To do that, we require well-informed journalism. This is not that:

That story offers no credible scenario of extinction. It cites the fabled paper-clip hypothesis of the former Oxford philosopher of Effective Altruism, Nick Bostrom, who contended that a machine told to do nothing but make paper clips could monomaniacally make paper clips of us all. Oxford shut down Bostrom’s Elon-Musk-backed Future of Humanity Institute when old email of his was revealed to have said “Blacks are more stupid than whites” and used the N-word. This is why when discussing the doomster beliefs of AI cultists, the context of eugenics matters. But no mention of that by The Journal

In that article, while fueling the “freakout” it purports to report on, The Journal waits until ten paragraphs in before labeling extinction prognostication a “fringe opinon.” At least it does that. 

In this, The Times accepts AI companies’ excuses for why they can’t stop their AI from going rogue, while at the same time accepting their assertions that they can create AI that is “aligned” with human values.

Well, if you want to worry, here’s the real troubling news: This idea of AI alignment — of guardrails to prevent bad outcomes — is ultimately a fool’s errand, for there is no way for any AI company to predict and prevent every possible malign or accidentally harmful use of AI. That is the reality we need to be discussing. 

Instead, in that headline, The Washington Post anoints Dario Amodei, Sam Altman, and — gulp — Elon Musk as our “top AI leaders.” No, these are the profoundly self-interested CEOs of three companies selling AI, who are given free space to promote their own agendas without proper context. They share one interest: to pull the ladder up after them and make it more difficult for competition — especially Chinese AI companies and more importantly free and open models — to challenge them. Here, The Post is acting as their agent. 

Can AI be dangerous? Of course, it can. AI has been used by Russia to guide autonomous drones to kill Ukrainians. Perhaps our greatest fear is that AI could be used to craft bioweapons. But The Times concedes that even with instructions, it’s tough to actually make them. 

The more frightening truth — one that should be on our minds after this anniversary — is that in the wrong hands, any technology can be used as a weapon … even passenger jetliners. We have met the problem, and it is us. 

I do see the need for wise policy around AI, including:

• Demand for full transparency from AI companies. Congress would do well to sic expert staffers (not grandstanding pols) on the AI companies to dig into programmers’ and executives’ negligent behavior in cases such as the OpenAI/Hugging Face incident.
• Support for open-weight models (the closest AI gets to open-source) to provide competition to OpenAI, Anthropic, and SpaceX. These frontier companies want to frighten policymakers into banning these upstarts, especially those from China. Do not fall for it. 
• Support for fundamental, frontier AI research in universities to provide more competition to the IPO-mad frontier companies and to have this work done under the ethical, open, and peer-reviewed standards of the academy. We could also use a modern-day Bell Labs with a public mission to do AI research. 
• Support study of AI and its impact and implications by scholars in the humanities and social sciences. 

Are there alternatives sources for good coverage of AI? Not many. Here are a few: If you want to dig down into the rathole of the AI boys’ philosophies, there is no better place to start than Gebru and Torres’ TESCREAL work. If you want to follow the big, big money behind this movement and what it is building on college campuses and many acronymed institutes, follow the investigations of researcher Nirit Weiss-Blatt. And for clear — though not simple — explanations of the recent scares over AI, I recommend Newport’s latest podcast, particularly this episode and this. 

Perhaps journalism’s greatest folly is that it treats the self-serving heads of companies that make AI as experts and even intellectuals, though many of them left college early, which is why their frequent manifestos sound like the work of freeze-dried sophomores. News media need to seek out the expertise of historians, ethicists, anthropologists, sociologists, philosophers, legal scholars, economists, and community leaders to help inform all of us about the opportunities and risks of the age we are entering. 

The post They’re covering the wrong AI story appeared first on BuzzMachine.

I have written much about my memories of 9/11: My story of surviving the day; recording what I witnessed; a meditation on the Yahrzeit; then five years on; ten; and twenty years and what I recalled still.

Now twenty-five years after I must write of my regret. 

All this time, I had convinced myself of the common belief that the trauma of 9/11 brought us together as a nation and showed us a model of what we could be.

That was myth. I was wrong. 

After a decade of Trump, of American fascism, of my own profession’s — journalism’s — negligent failures in the face of it, how could I still believe that we are in any way better now than we were before? That the United States has twice elected an incompetent, ignorant, bigoted, dangerous, warmongering, authoritarian to the presidency is evidence that this nation has learned nothing and indeed fails to respect learning. That Germany — of all nations — can see one of its states grant an electoral landslide to right-wing extremists demonstrates that any lesson, no matter how profound, can be forgotten.

9/11 led to extremism in response to extremism. It elevated a fringe culture of conspiracy theorism to the core of right-wing politics and media. It enabled a security state built on constant suspicion and paranoia. It led to a sense of American victimhood and entitlement, muffling the empathy we should have for the suffering of other nations under attack. It made permissible an interchangeable American bigotry aimed at one group and then any group. 

I do not mean to sound cynical. But to deny the cynicism that has taken root and spread in this nation in the last twenty-five years would itself be an act of cynicism. 

If there is a way out of this, it is not through annual incantations of lost unity. It must be through fighting: fighting authoritarianism, ignorance, suspicion, bigotry, terrorism — domestic and foreign — and fascism. That requires that we — beginning with political leaders and journalists — first recognize these palls on the land so we may organize to oppose them. We must specify which institutions are under attack — democracy, education, equality, inclusion — before we can defend each.

My first emotion after surviving the attack on the World Trade Center was anger, not relief. In the flush of the moment, I at first titled the blog I started a few days after the attack “World War III;” before long, it was Buzzmachine. That was misplaced anger, anger that could be exploited. 

Anger properly channeled is a powerful force. We who defend democracy must direct our anger at those who threaten it, at those who have exploited 9/11 to seize power. I am angry at institutions — universities, media companies, law firms, civil service — that fail to defend themselves against unjust attack. I am angry at my fellow journalists for succumbing to their reflexive tropes of imagined unity, objectivity, normalcy. 

After 9/11, we asked when we would return to normal. In the midst of COVID, we asked the same question. But in truth, normalcy is nostalgic fraud: the belief that there is some better day to return to. If you are Black, Latino, an immigrant, disabled, LGBTQ, female, poor, or in any way disenfranchised, that day never existed. The past is nothing to fight for. What we must join together to fight for is a different and better future: progress. 

Looking back, I see that 9/11 robbed me of dreams. It allowed the forces of the past — of so-called conservatism — to set their agenda of protection, exclusion, and reversion, instead of progress.

On that beautiful, clear, September day that I shall remember for the rest of my days I witnessed and survived horror. The specific aftermaths in my life — a heart condition, two cancers, PTSD, and burdens on my family — are nothing next to the loss and trauma so many others have experienced, bearing scars still. On that day and to this day I know how fortunate I am. But I am also angry at the progress and potential we have lost. I am angry at myself for not fighting hard enough to regain them. 

That is how I feel, twenty-five years on.

The post 25 Years appeared first on BuzzMachine.

The story of labor and the Linotype is unexpected in many aspects. For this Labor Day, I’ll share a bit on the subject from my book Hot Type. (Links to buy the hardback and audiobook versions and signed copies are here).

Printers waged their first strike against publishers in occupied New York in the winter of 1776. They came together to form what would become the International Typographical Union (ITU) in 1850.

All through the nineteenth century, a few hundred inventors tried to build the machine that would automate typesetters’ work. One might think, then, that they would follow in the paths of the Luddites and Captain Swing and destroy the contraptions. But those earlier protests were against feudal factories more than technology; the workers were not yet not organized into unions like the typesetters; and Swing’s followers ended up swinging from gallows. Besides, typesetters watched the experience of pressmen; with the introduction of steam-powered presses, their ranks shrank but then grew as publishing did. 

More than the machine, typesetters feared the intrusion of women into composing rooms and forbade entry of black men — most notably Frederick Douglass’ son. (In Hot Type, I tell his story and that of Gussie Lewis Troup, who organized the first, regrettably short-lived women’s typographical union.) Typesetters were generally sanguine about the machine because so many of the 300 attempts at building one had failed.

Until the Linotype, the machine at the center of my book. On July 3, 1886, the first working Linotype invented by Ottmar Mergenthaler was hoisted up into the nonunion composing room of the New York Tribune, under the eye of its publisher, the villain of my tale, Whitelaw Reid. From Hot Type:

At the start of July 1886, a decade after he first met [his muse, James O.] Clephane, Mergenthaler supervised the installation of a Linotype in the New York Tribune composing room. “Through the Frankfort Street end of the composing room ran a huge flagpole,” that machine’s first operator, John T. Miller, recalled fifty years later, in a commemorative issue of the company newspaper, The Linotype News. “To that pole, that memorable afternoon in 1886, a block and tackle was attached. Nine stories below, in the street, was the first Linotype. It was completely boxed, and on top of it stood a man to guide it up through the network of telegraph wires. . . . As the man who made the dangerous ascent (I’m sorry I can’t remember his name, if I never knew it) threw one leg over the large window sill, he gave loud expression to his relief.” The composing room foreman gave that man thirty-five dollars for his perilous duty. “And soon Ottmar Mergenthaler and Charlie Letsch” — a nineteen-year-old assistant who had accompanied the machine from Baltimore — “had the Linotype in working order.”

The Tribune composing room was lined with hundreds of compositors’ typecases, which ran from one side of the building to the other. There were also three Burr machines, an unwieldy typesetting device that had survived multiple inventors, owners, bankruptcies, and names (it was later called the Empire). The Burrs composed and distributed type as [the machine Mark Twain backed] Paige’s Compositor did, a letter at a time. “The middle one of our three Burr machines had been shunted aside to make way for the new device,” Miller recounted. “Naturally, the arrival of the new and improved contraption made a big stir. All of us who could manage to, crowded about for a good look at it. Most of the hand men didn’t think much of it, and many said so. Even we Burr operators were a little skeptical.” The Burrs would soon be sold and four more Linotypes ordered.

The New York local of the ITU — known as Big Six — had a spy in Reid’s scab composing room. “‘The experiments were carried on in a partitioned-off end of the composing room floor, doors locked: entrance, except to pass-holders, forbidden,” J. W. Sullivan of Big Six recalled years later. “But one of № 6’s half dozen card men under cover on the then non-union Tribune got me a sketch of the machine with some of its type-faced slugs, explained its principles. . . . I could not rid myself of the conclusion that Gutenberg’s epoch-making invention of movable types had had its day.”

Here’s the surprising bit: The ITU did not forbid the machine. It embraced the machine, but under one condition.

The next year, the ITU dispatched “some of its most thoughtful and conservative members” to witness an “improved Linotype first-hand and report back. “It was found that this machine was capable of some excellent work, considered from a mechanical stand-point, and produced lines perfect in spacing and with a clear face, from which plates were made as readily as from type,” their report said. The delegation gathered data from twelve days’ work in one composing room in Brooklyn and another in Manhattan, where an experienced compositor was pitted against an expert typist. (The typist was a tad faster.)

The committee came away with a recommendation impressive for its foresight: “It is concluded that printers ought to stand ready to operate the machines, and that unions should in no way discourage their use, but should insist that their members be employed” to operate them. “It is not thought that there is anything apprehensive in the situation or that there is need of a panic in typographical circles.” They advised against “the foolish effort to stand in the way of mechanical improvement.”

And so, the typographers’ union made a bold and strategic decision not to reject the Linotype but to control it. On March 3, 1889, a newspaper publisher asked the union whether it would object to his introduction of a machine. “It is the sense of this union,” №6 resolved in reply, “where an employer desires to introduce typesetting machines the union should merely insist payment of the scale of the union and the employment of its members to do the work.” The national union followed suit, directing that “where typesetting machines are used, practical printers shall be employed to run them and also that subordinate unions shall regulate the scale of wages on such machines.” . . . .

The ITU came to recognize the inevitability of technology invading its sphere. “This is the day of the machine,” said a report to the union’s 1893 convention. “The machine is with us, and it behooves us as craftsmen to get closer together, en masse, and take care of it in a manner to show our appreciation of so important an invention and reap whatever benefits it may be possible for labor to derive from labor and dollar-saving machines. The web press is with the pressmen as the typesetting machine is with the compositor.”

It was a risk. By one accounting, the ITU lost 36,000 positions in short order, including older members who felt incapable of learning a new way to work. But with the new technology, media industries exploded.

“After 5 years the trade has about adjusted itself to normal conditions, and the membership of the printers’ union is to-day greater than its membership of compositors ever was,” the ITU’s Donnelly testified in 1900. “The policy adopted by the typographical union was not to oppose the machine, but to admit its success and make the best of it; to try and master it,” he explained. “The spirit that was manifested by the members was something of this kind: ‘Here is something that will take my bread and butter away from me and I must try and become its master.’ They endeavored to learn the machine as quickly as possible.”

One key to printers’ survival and success was that publishers chose not to pocket their machine dividends — a 66-percent saving in the cost of typesetting, with half the errors to boot. Instead, proprietors invested in more, bigger, and more competitive publications.

In my research, I was impressed to see federal commissions convened at the turn of the century to study the impact of new technologies on work and the economy. If only our current government were capable of such sane and sober study and analysis of AI’s entry into the workplace and culture; we need it.

There seems to be a lesson in the ITU’s actions: Rather than fighting and trying to forestall the inevitable arrival of new technology, it is better to take control of it. That worked well for the ITU for three-quarters of a century as it lobbied successfully for the eight-hour work day and drastically improved the working conditions — and health — of its members. The ITU — and particularly New York’s Big Six — became immensely powerful. 

Until they weren’t. In the 1960s and ’70s, new technologies threatened: punched paper tape that could run a Linotype without an operator, like the robot it appeared to be; cold type (shining light through letters onto photographic paper to set text); computerized hyphenation and justification of text; computers in newsrooms, allowing publishers to “save keystrokes” and eliminate typesetting in composing rooms; and finally PostScript, which turned letters into shapes to be described to and displayed by computers and printers. 

This time, the ITU tried fighting the technologies. A series of strikes over these issues killed six of nine New York newspapers — and eventually the union along with them. 

The lessons the ITU and its leadership faced with these new technologies was different from the lessons learned with the Linotype. For all these fascinating stories, you’ll need to buy the book. 

Happy Labor Day.

The post Labor and the Linotype appeared first on BuzzMachine.

With the publication of my new book, Hot Type, I’m sharing brief excerpts to give you a sense of the stories in it. Mark Twain is the Zelig of the tale, reentering often, as if a tour guide. Here, he comes on stage as Samuel Clemens, a young printer’s devil working in his brother’s Hannibal newspaper before hitting the road as a tramp printer. This is my way to explain the job, the craft — the art, some would say — of setting type. Following this in the book is an account of the tremendous technological innovations in publishing — steam-powered presses, stereotyping, the telegraph — that Sam saw in this period, all of which will lead the way to the Linotype. But you won’t find that here. You’ll have to buy the book .

In 1847, at age eleven, a fatherless Samuel Clemens begged his mother to let him leave school to work. Two years later, after Sam’s teacher decamped Missouri to join the California Gold Rush, Jane Clemens relented and allowed her son to undertake an apprenticeship at Joseph Ament’s Missouri Courier in Hannibal. He worked as a printer’s devil — composing room dogsbody — for no pay, only food, board, education in the trade, and the promise of two suits. Sam slept on the floor of the office above Brittingham’s Drugstore and received just one suit, a too-large hand￾me-down from the too-large publisher, which “gave me the uncomfortable sense of living in a circus-tent.”

After serving two years, Sam went to work in the Hannibal Journal, a paper bought and run by his brother Orion. It was a dreadful weekly blatt filled with endless transcripts of boring speeches, treacly serialized fiction, and random, useless items passing for news: an inch of snow in St. Louis the week before, a robbery a state away in Illinois, how many brooms orphans manufactured daily in Cincinnati (twenty dozen). In Sam Wheeler, Detective, Sam the author described a village paper that might as well have been his brother’s.

It was a wretchedly printed little sheet, being very vague and pale in spots, and in other spots so caked with ink as to be hardly decipherable. The first column was occupied by “Original Poetry” of the sappiest description. The next four were occupied by a selected story which was as sappy as the poetry. The remaining column of this first page was made up of short paragraphs of vapid, heart-breaking, infuriating rot entitled “Wit and Humor.” The other outside page was built wholly of advertisements: three columns consisted mainly of glorified quack-poisons . . . headed with blurred portraits of the assassins who invented the nostrums, and tailed with lying testimonials from people who had never existed; the two remaining columns were thrown into one, which sang the praises of “Bagley’s Celebrated One-Price Emporium” in riotous display-lines of forty-line pica shot full of shouting exclamation points.

The Clemenses were not noted for their business acumen. The boys’ father, John Marshall Clemens, failed at running multiple general stores. As will become clear in these pages, Sam would prove to be a disaster at business, saved from poverty and obscurity only by his talent as a writer and speaker. Brother Orion was the least proficient of the clan. Stumbling into the newspaper business when he worked as a printer in St. Louis, Orion returned to Hannibal to buy the Journal for $500 on credit, and he promptly cut the price of a subscription from $2 to $1 a year and reduced the price for advertising. “Thus,” said Sam, “he created one absolute and unassailable certainty — to wit: that the business would never pay him a single cent of profit. The paper was a dead failure. It had to be that from the start.”

In the Hannibal Journal, Sam began to write in his rascally voice under the noms de plomb of Rambler and Epaminondas Adrastos Blab, not yet Twain. Once, when Orion was away, young Sam took the opportunity to write and print a news item, illustrated with a childish woodcut, mocking the editor of a rival newspaper, who had purportedly gone to the river to put an end to his lovesick misery. “The satirized editor at first swore that he would thrash the whole Journal office, then he left town and did not come back any more,” reported Twain’s biographer, Albert Bigelow Paine. Said Sam: “My literature attracted the town’s attention, but not its admiration.”

Mostly, Sam set type, fitting it in page forms, inking it, pressing dampened paper atop it. He was, according to Orion, good at the job, “as swift and as clean as a good journeyman.” Sam stood at the typecase with the text to publish in front of him and a composing stick in his left hand. With the practiced sixth sense compositors acquire, his right hand reached for the correct box from which to pluck the next letter, capitals in the upper case, the rest organized by frequency of use in the lower case — the biggest box for e. Light was supplied by windows in the day, at night by a candle stuck in the d box, dripping its tallow on the k box next to it.

This was not a task for the fumble-fingered. Each metal letter was small, less than an inch long and no thicker than a half-dollar. Sam’s finger felt for a notch molded into one side of a letter’s shaft to make sure it was positioned correctly. Then he added it to his composing stick with a clink. The letters were mirror images of how they would appear in print. As the line filled up, he needed to think ahead and decide whether to split the next word — compositors had to know rules of spelling, hyphenation, punctuation, and grammar. Once that was done, he calculated the spaces, thin or thick, needed between each word to evenly fill out — to justify — the line.

Typesetting, justifying, and correcting all the words in just the paragraph above could have taken an hour of Sam’s labor. Once the type was set, the compositor’s job was still not done, for after the sorts were used in the press and cleaned (in the stench of long-ago composing rooms, that was accomplished with lye and often urine), they had to be redistributed back into their proper nooks in the typecase for reuse. That was not so simple as it sounds, for one had to read each piece of type in mirror image, making sure not to confuse the d and b — minding, as they say, one’s p’s and q’s. At a big-city paper, that paragraph above might have earned Sam twenty-three cents. Orion promised to pay his brother $3.50 a week but “he never was able to pay me a penny as long as I was with him.”

On the press, Sam worked with a colleague. One of them inked the type laid out in a form on the bed of the press. The other placed a dampened sheet of paper in a holder called the tympan, folding down a protective frame called the frisket. He turned a winch called the rounce to move the form and paper under the press’ flat, horizontal platen. Pulling the press’ handle brought the platen down onto the paper and type, transferring ink and text. He then winched the bed back out. The paper came off the type with a kiss, a sticky smack, and they did it all again, as often as 250 times in an hour. The speed of that process determined the natural limit of a newspaper’s circulation: how often the pressmen could pull that lever in the time between the news being set in type and it becoming too stale to sell. The Society for the Diffusion of Knowledge’s Penny Magazine figured in 1833 that the maximum press run for a daily newspaper was 5,000; for a weekly magazine, 20,000. That ceiling on the scale and reach of media was about to explode. And all the skills Sam learned as a journeyman printer would eventually be rendered obsolete by a succession of new inventions….

More excerpts:

• Back to the prior excerpt: Introducing Hot Type
• Forward to a LitHub excerpt about Twain finding a business model for books at scale. 

The post Sam Clemens, compositor appeared first on BuzzMachine.

With the release my new book, Hot Type, this week, I will post some good bits in hopes of enticing you into reading it. Here, from the introduction, is a preview of the many delightful rabbit holes I explored building the story of the invention of the first successful typesetting machine, the Linotype, and with it, the birth of mass media. You can order the book here. Please.

The story of the Linotype is many stories in one.

This is, first in my mind, the story of the advent of mass media and its consequences: speed and scale, attention and reach, capital and control. In the early nineteenth century, before the mechanization and industrialization of print, the average circulation of a daily newspaper in the United States was only 4,000, limited as it was by the speed and power of human muscle to set its type and pull its press. By the end of the Civil War, steam-powered presses began to speed up production of print at a scale never imagined. Cheap paper manufactured from wood pulp made books, magazines, and newspapers cheaper than ever to publish and buy. Railroads carried these publications and their influence ever farther, while also providing a new time and place to read. The telegraph brought news from around the world as fast as lightning. Literacy was rising fast.

One man (and it was almost always a man) stood in the way of media’s explosive progress and potential: the typesetter at his typecase, adding letters to his composing stick a click at a time. To hand-set the type in just one page of this book would have taken the average compositor as long as two hours. That is why the growing media industry eagerly awaited the invention of a machine to automate the job. “It is discreditable to the inventive genius of this country that the one great mechanical want of our time is still unsupplied,” New York’s World cried in 1869. In an Industrial Revolution rendition of “if we can fly to the Moon why can’t we . . .?”, The World pleaded: “We want the means of supplying the demand for reading matter. The inventive talent of the country produced the steamboat, the cotton-gin, and the electric telegraph.” Why not yet a typesetting machine?

This is the story of that invention. Hundreds of failed typesetting
machines littered the nineteenth century, as did scores of abandoned attempts to build its mechanical precursor, the typewriter and the keyboard. Here I will recount the work of inventors who failed and the few who finally succeeded in revolutionizing print and publishing: Christopher Latham Sholes with the typewriter; Ottmar Mergenthaler with the Linotype; and finally, Steve Jobs with his Mac and John Warnock and Charles Geschke with PostScript, the inventions that wiped out all textual technologies that came before. Their histories are seeded with insight and inspiration, frustration and failure, collaboration and the rare eureka!

This is the story of Mark Twain. He is the Zelig and zeitgeist of our tale, for he will return often. Young Sam Clemens was a typesetter on his brother’s newspaper in Hannibal, Missouri. He was a tramp printer wandering from composing room to composing room across the country, witnessing technological progress in the trade. He wrote for newspapers. As Mark Twain, he was perhaps the first beneficiary of media made mass — and his celebrity helped make it. But the Linotype was his bête noire, for Twain invested his fortune in a would-be competitor, the Paige Compositor. Its inventor, James W. Paige, was a pathological perfectionist, equal parts brilliance and flim-flam, and it was because of him — and other failed business judgments — that Twain’s publishing house folded, sentencing him to bankruptcy and bitterness. Some say it robbed the great man of his sense of humor.

This is a story of technology and our adjustments to it. In the midst of his struggles with the Paige Compositor, Twain wrote A Connecticut Yankee in King Arthur’s Court. It reflects Twain’s — and society’s — enamored affair with the technological and new, as the Yankee introduces electricity, steam, telegraph, telephone, and newspapers to Camelot. At its end, the book exposes Twain’s disillusionment with dark modern arts, culminating in a technological Armageddon that foretold the hell of the First World War. Reexamining the technological disruption of the time could not be more relevant to us today as we grapple with the consequences of a connected world and artificial intelligence.

This is the story of labor and technology’s costs and benefits. One might assume that typesetters — the people — wished to destroy typesetters — the machines — as the Luddites smashed looms and Captain Swing rioted against threshers. But no. The International Typographical Union (ITU) recognized the inevitability of the Linotype’s success and made one consequent demand: that its members should be the ones to learn and operate it. After short-term job losses, that strategic foresight led to tremendous growth in employment and in union power — until the trade faced superseding technologies. Inside this labor history is an examination of gender and race. The typewriter was gendered female, bringing women into the new workplace of the office. Typesetting and the Linotype were gendered male, as women were excluded from composing rooms. So was Frederick Douglass’ son, refused membership in the ITU — even while he and his father published their newspapers — because he was Black.

This is the story of capital and early-stage capitalism in the era Twain named the Gilded Age. Because publishing required investment in complex and expensive machines — presses and Linotypes — writing and public discourse became the domain of corporations. Here enters a villain in this opera named Whitelaw Reid, who stole the New York Tribune out from under its founder, Horace Greeley; who forced Ottmar Mergenthaler out of the company he made; who used Mergenthaler’s machine to keep union printers out of his composing room; and who peeved Mark Twain on multiple occasions.

And this is the story of the culture’s relationship with text in a grand arc from the goose quill (and its eventual industrialization with the steel-nibbed pen); to Gutenberg and his material, movable type; to the typewriter, allowing anyone to produce a printed page; to the Linotype and its profound impact on all publishing. The arc of this saga ends with the technology that replaced all that: the computer program called PostScript, which describes letters as shapes alongside other images, opening the way for desktop publishing and the democratization of print — and ultimately the internet and all things digital.

In the end, this is less a story of machines than of human beings: the triumph and tragedy of Ottmar Mergenthaler; the grand friendship and loyalty of his muse and supporter, a presidential stenographer named James O. Clephane; the sad sack inventor of the first successful typewriter, Sholes, with James Densmore, the dogged booster who made it successful; the young woman named Gussie Lewis Troup, who founded a typographical union for women; the 1960s union boss, Bert Powers, whose strikes killed six of nine newspapers in New York while he saved the livelihoods of his members; and the unsung publishing consultant Jonathan Seybold, who connected the dots needed to make writing and publishing on screens possible. You will be introduced to these and other leading players in the Typothetae Personae that follows, and will hear their voices, often in florid and charming Victorian speech, throughout the book.

“The history of the invention of the typesetting machine is a novel or a drama in all its ups and downs,” wrote Karl d’Ester, a German scholar of newspapers and communication. This is that drama. In the first chapter, you will meet Sam Clemens as a printer’s devil, learning to set type. As a tramp printer, he traveled the nation and witnessed disruptions that threatened print’s old ways. As Mark Twain, he threatened staid Eastern culture as he chronicled and named the age and its upheavals. Everything about printing was changing — everything except typesetting. The industry awaited the machine that would finally automate even that slow, complicated, and expensive job.

In the following three chapters, you will see the experiments and failures that preceded both the typewriter and typesetter — most notably Twain’s folly. Then you will meet the inventors who won, learning their bittersweet life stories and, in Chapter Four, witnessing the eureka! that made the Linotype possible. The following two chapters track the success of the Mergenthaler Linotype Company as it ushered in the age of mass media, and as media moguls — and Twain as a wannabe publishing mogul — searched for business models to sustain their new industry.

Next comes the rich tale of labor’s relationship with the machine, from the founding of America’s oldest trade union to the antics of the Swifts, the speedy typesetters who, odd but true, turned their craft into a spectator sport; to the union leaders who led their members to safety in the Linotype age; and finally to their denouement at the hands of media mogul Rupert Murdoch. Next comes the end of all that and the beginning of what replaced it: the computer and desktop publishing. Then I return once more to Twain and his disillusionment with technology, celebrity, and humankind.

After it all, I offer my typographical autobiography, for I had the good fortune to live and work in the transition from hot type to cold, material to digital. There I will reflect on how these changes affected my relationship with writing and publishing as a journalist.

More excerpts:

• Forward to Sam Clemens, compositor: How to set type since Gutenberg.
• Forward to a LitHub excerpt about Twain finding a business model for books at scale. 

The post Introducing my book ‘Hot Type’ appeared first on BuzzMachine.

On this week’s Intelligent Machines, we cohosts had a spirited disagreement about Anthropic’s watermarking of text, as required by EU regulation. The company just released more detail about how it will work, and now I’m upset for a different reason than I first thought.

I’m angry as a writer.

Anthropic’s method will alter its models’ word choices in a pattern based on a key only it knows, allowing it to detect writing (or editing or translation) by its machine — to an uncertain degree of certainty. The company contends there is no difference in meaning between the otherwise random choices “grey” or “overcast” in, for example, the context of weather. So what’s the issue?

Thus Anthropic declares words fungible, language random, choice meaningless. Not to me. I try to select my words as carefully as I can for a number of considerations: style, tone, rhythm, avoiding repetition, but most of all meaning. You may quibble with my choices, but they are mine, not yours; that’s what makes my writing mine, to communicate what I wish to communicate. “Gray” and “overcast” are not the same, damnit. That’s the reason we have both of them.

So I resent Anthropic et al dismissing the value of a writer’s selection of one word over another for the impact that decision has on expression, on impression — occasionally on art.

We humans might not be able to detect whether the machine or the key is being used. That’s not the point. The selections/changes/alterations made in accordance with the key will affect sense and style on an ever-larger proportion of text entering discourse, and the fact that Anthropic (and the EU) consider this acceptable, unimportant, even trivial has cultural impact on the worth of words. They devalue writing. At the very moment when LLMs commodify writing and writers, this is just another kick to the kidneys for a challenged craft.

And why is this forensic breadcrumb trail being required? Because of prejudice against the technology: fear unto moral panic. But technological solutions to perceived technological problems have just as many unintended consequences as the problems themselves, often more. The irony is that in a zealous effort to protect the distinctiveness — the sanctity — of human text, the authorities and the technologists deprecate what makes text human.

In my new book Hot Type, I quote critics such as Friedrich Kittler insisting that typewriters changed how Nietzsche, Hemingway, or Hesse wrote and thought. At the end my book, in what I call a typographical autobiography, I recount how technologies, from typewriter to computer to PostScript, affected my composition and cognition. These technologies affected my methods, but that makes my prose no less human. We should debate what the impact of this next technology, AI, might be on creativity and perception, but we should give that process time. Rushing to regulatory and technological solutions to a problem not yet fully understood is foolish.

So I’m pissed.

Here is a sentence from the first page of Hot Type, one I chipped away at innumerable times. These are the choices I made:

Unlike what we now call machines — computer chips veiled inside sleek and sealed grey boxes with no moving parts, save fans to cool their brains— the Linotype’s innards were left exposed, as if to show off the genius of its works: its troop of idiosyncratically shaped cams, gears, belts, arms, and wheels marching to instructions foreseen more than a century before by their inventor, German-born watchmaker Ottmar Mergenthaler.

Now let us recast it with perfectly acceptable synonyms, as Anthropic’s detection key might, in composition, editing, or translation. In fact, I asked Claude to do just that. Here is what it delivered as “a synonym-substituted version, keeping the structure and meaning intact.”

Contrary to what we presently term machines — microprocessors concealed within polished and enclosed grey containers with no moving components, except fans to cool their circuitry — the Linotype’s mechanisms were left visible, as if to display the ingenuity of its craftsmanship: its brigade of distinctively shaped cams, gears, belts, arms, and wheels progressing to directives anticipated more than a century earlier by their creator, German-born horologist Ottmar Mergenthaler.

You may find Claude’s just fine. I find that it misses the wonder, cadence, and anachronism I tried to convey. Anthropic’s engineers and the EU’s regulators may ask, what’s the prob? Much, I say.

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In response to the spectre of Chinese open-weight AI models haunting America, Dean Ball, OpenAI’s director of strategic futures [are there directors of strategic pasts?], issued a warning more shrill even than the New York Post’s alerts about Mamdani’s bus-and-grocery socialism. 

One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a “public good” which will ultimately be provided by the state as a kind of “digital public infrastructure.” This future strikes me as a dystopian hellscape, but I’ve never met an open-weight models advocate who doesn’t ultimately concede this is where things end.

As Jason Howell and I discussed this on our podcast, AI Inside, we found ourselves asking, What would be so wrong with AI communism? What if there were AI for all? Eh, comrades?

Imagine all that could be created, often for free, on top of open AI models: how many universities and researchers, startups and entrepreneurs, artists and students could better afford the technology. Imagine the greater control that comes from locally hosted models. Imagine the greater transparency and security that comes with openness. And imagine the power — pricing and political — that could be wrested from the new AI giants as they barrel toward their IPOs…which, of course, is precisely what frightens them. But you need not imagine all this, for open-weight models are affording these opportunities now. 

By championing open AI, we could atone for past sins (including mine) of insufficiently supporting openness in the first phase of the internet, leading to the fencing of the commons. Open AI may be our best and only defense against its oligarchic domination. As the wise John Palfrey, head of the MacArthur Foundation, just said, “This is a design moment — for the technologies, for the way we relate to one another across geographic and political boundaries, and for what the future looks like.”

A week after Ball’s cri de code, Nvidia founder and CEO Jensen Huang posted an open letter supporting open-weight models, now signed (as I write this) by fifty AI giants — pretty much everybody who matters … except Anthropic. Even Ball’s bosses signed. It is a remarkable endorsement of open computing and a message to governments. I recommend reading it in full:

The Washington Post puzzled over why Nvidia et al would “take a stand that helps their Chinese rivals.” (Note that Post owner Bezos’ Amazon has not signed this letter.)

But of course, open-weight AI is in the business interests of Nvidia and AI chip companies: the more AI is used, the more chips are needed. Locally run, open AI is also in the interests of countless companies. I hate to find myself agreeing with Palantir’s Alex Karp, but he tells his corporate clients they should run open-weight, locally hosted models so they don’t give over the souls of their business to the frontier AI companies; this is his business model.

Openness is also in the interests of an enlightened AI industry, as it creates competition and that yields greater innovation. This is why an AI pioneer I greatly respect, Yann LeCun, doggedly supports open-source AI and why he founded Project Tapestry, “a new open-source platform for globally federated development of frontier AI models — preserving local control and long-term independence.”

Now just as sanity was emerging in the discussion about AI, moral panic reared its sweaty head again when credulous media reported that an OpenAI model had gone rogue and “hacked” into Hugging Face. This turns out to be another instance of the doom-as-marketing strategy engaged in by both OpenAI and Anthropic. It is their way to attract publicity and venture funding and control the conversation about regulation of AI. In truth, OpenAI’s model was engaged in a security test; it only did was it was instructed; it has no sense of right or wrong or “hacking;” it isn’t a rogue threat to society, no matter how much the AI boys would like to believe they hold such power.

The chef’s-kiss irony of the Hugging Face affair was that the platform found American models useless in its defense against the “hack” because they were all hampered by guardrails forbidding them from undertaking tasks regarding security risks. Hugging Face had to rely instead on an open-weight Chinese model.

Such panics, predictably, lead to threats of government control of AI, and that worries the hell out of me, especially and obviously given the IQ of the current administration. In Congress, Reps. Ted Lieu (D-California) and Nathaniel Moran (R-Texas) have proposed the AI Kill Switch Act, which would require major AI companies to install the means for their models to be shut off in the event of a “credible risk.” And who will have the power to decide to pull the plug? The secretary of Homeland Security.

No, no no. 

When I attended a World Economic Forum (Davos) AI event in San Francisco sometime ago, one faction of worrywarts urged the banning of open-weight, open-source AI because users could turn off guardrails, and then who knows what chaos would ensue. But as I often argue, guardrails are fools’ comfort, for there is no way for any model maker to anticipate and thus prevent every possible malign or accidentally harmful use to which their tools could be put. That doesn’t mean that AI companies should not be expected to try to prevent against known malicious or dangerous acts. But AI is a general machine, like the printing press. There was no way to tell Gutenberg to design his movable type such that no future Martin Luther could ever make mischief with it.

Open-weight models are our best defense against hegemonic control of the technology by either governments or huge AI corporations. They are also the best way to put AI into the hands of more people, not just those who can afford to spend fortunes on hosted tokens. That throws a wrench into Sam Altman’s plans to sell back to us our collective intelligence as if it were a commodity. “We see a feature where intelligence is a utility, like electricity or water,” Altman says, “and people buy it from us on a meter.” Thereby, Altman concedes that AI is, if not a public good at least a public utility. 

Now I will object to the idea that what AI offers is “intelligence.” That is a gross anthropomorphism that, by its very conception, competes with and excludes humanity. But for the sake of this discussion, for the moment, let’s use it.

If intelligence is an asset that can be created and shared, flowing as from a spigot, shouldn’t we all have access to it for the greater benefit of society? Isn’t that all the more reason to endorse open-weight, open-source AI that we can run and train and adapt and control and benefit from on our own? 

Yes, free, open-weight models will always be two steps (read: six months) behind the so-called frontier models. But open models will be able to do 99 percent of what 99 percent of people want to do with AI. Still, there will be business opportunities aplenty for AI companies to build specialized models, trained on specialized information, for specialized tasks of high value. In fact, it would be much more productive if the companies would concentrate on that instead of pursuing their bullshit goal of building “artificial general intelligence.” 

Now I’d like to take this discussion one step more: If “intelligence” is a public good, should not the data needed to train models be? For if we all can benefit from open models, who would want them to be less intelligent? And does it not follow them that data, civic information, and by extension journalism should be open? 

Oh, I can hear the howls of protest, for I’ve heard them for years: How will the gathering of that data and information be paid for? One answer is universities, where research is subsidized. Or it was, until America’s right-wing extremists opened war against the institutions of education and science. 

As for journalism, it is not a forever thing. Before the economics of mass media and the attention economy overtook news and civic discourse, society operated differently. Limited by the technologies of the time, before steam-powered presses and Linotypes, publications were small, often both created and shared socially. Now that mass media and its attention economy are the walking dead, we will need to reconsider every model of gathering, sharing, and utilizing public information. My point is that the discussion about open-weight, open-source AI forces us to ask similar questions about what open journalism would look like. Eh, comrades?

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California is about to hand out $20 million — half from Google, half from the state — to news organizations, and it is wasting a golden opportunity.

Instead of building a new and more competitive landscape of news, instead of creating services to benefit the entire news ecosystem, instead of investing in innovation, instead of embracing new news partners such as libraries and community organizations, instead of imagining a new future for journalism, the California Civic Media Program is going to end up sending too many checks to the hedge funds that have ruined news in the state.

I am sorely disappointed and rather angry. For imagine what $20 million in one year could do to set an example of innovation for the nation.

There’s much history here. Lobbyists for the old, hedge-fund-controlled newspaper industry — the rebranded American Newspaper Publishers Association of 1887 — have been flogging protectionist legislation from Washington to Springfield, Illinois, to Sacramento, arguing that lawmakers should tax tech companies, which they say took ad revenue away from the media moguls (as if God had granted it to them).

In Sacramento, this took the form of the California Journalism Preservation Act (CJPA). It was terrible legislation. I was commissioned by the California Chamber of Commerce to write a white paper on it and I went to Sacramento to testify against it. I argued that policymakers should look instead to the New Jersey model of private-public support for journalism based not on payrolls in dying, legacy newsrooms but through open grants to anyone applying with innovative plans to serve communities’ needs.

Meta said if CJPA passed, it would pull news off Facebook and Instagram, as it did in Canada when it passed similar legislation. Apple apparently called in favors and was excluded from the bill. This pretty much left Google holding the bag. Negotiations ensued that resulted in plans for a promising public-private partnership, without legislation.

At first, much of the funds were to be administered by the state librarian, a former journalist, who understood the scope of opportunity. I offered suggestions on how the money could support real community-based innovation. I introduced the state to true innovators who are working with libraries as hubs of community information, with community members trained to cover their own governments, with public media building support for the larger ecosystem. Many folks were excited about what could be done.

Then the state pulled the program away from the library in favor of the Governor’s Office of Business and Economic Development (GO-Biz). Working with deputized agents and an advisory board, the resulting program will give money to the owners of news organizations based on present headcount of journalists: $20K for each of up to five full-time journalists, $10K each for up to 15 more, up to $250K per news organization.

There are conditions. The news organization must be at least three years old. That is blatantly anticompetitive, excluding the startups that are the fresh blood journalism so badly needs. Broadcasters are also excluded.

But there are efforts to serve under-served communities. Applicants will be prioritized based on answers to “three short narrative questions on their coverage of disinvested audiences, ongoing viability, and planned use of funds.” And 13 percent of the funds are to be set aside to support smaller newsrooms in communities with greater information needs.

Still, most of the money will likely end up in the pockets of out-of-state hedge funds, just as their lobbyists intended.

When I’ve spoken with legislators in multiple states, I’ve tried to remind them that they need no longer fear publishers who now buy ink by the thimbleful, not the barrel. Mass media are the the walking dead. They cry poverty. But they still invest in lobbyists.

Some advocates for the future of news are essentially saying this program is better than nothing. I disagree. It is a wasted opportunity and a dangerous precedent.

This is the first year of the program. If this is all it does, it should die. If it continues, I’d hope that wiser heads would prevail to create a program that supports growth in the ecosystem (with startups), services that help the entire ecosystem (e.g., ad networks, training, shared technology), inclusion of new participants (e.g., schools, libraries), and innovation (don’t preserve the news that was, invent the news that can be). Note well that alongside various philanthropies, Google does just this with its News Initiative. 

For the record, Google is not at fault for how this has turned out. The company made clear from the start that it would not influence the use of funds. Responsibility falls to the state government and its agents. I hope they go back to the drawing board. (In disclosure: I have raised funds for the universities I work with from tech companies, including Google and Meta.)

For the sake of historical context, I look to the 1947 Hutchins Commission report on a crisis in American news, which even then saw a crying need for greater competition and diversity in news. “Monopolistic practices, together with the cost of machinery and the momentum of big, going concerns, have made it hard for new ventures to enter the field of mass communications…. Can the press in the present crisis rise to its responsibility as an essential instrument for carrying on the political and social life of a nation and a world of nations seeking understanding? If not, will its irresponsibility deprive it of its freedom?” There is less machinery needed today, thanks to the internet, but the monopolistic, protectionist, and exclusionary reflex of old publishers has not changed a bit.

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In an urgent and provocative essay in Die Zeit, journalist Georg Diez calls for a redefinition of progress in the time of AI. Taking lessons from the genesis of progressivism — a response to the Industrial Revolution and the (first) Gilded Age — we cannot now surrender the power to decide society’s future to present technologists.

“A notion of progress that inspires society and supplies it with new energy, both intellectually and emotionally, must therefore be comprehensive, systemically conceived, and grand,” Diez writes (with apologies for my translation). “It must be formulated collaboratively by politics, business, science, and civil society, and it must answer the question of what technology we want — and under what terms.”

I write this just as the ultimate profanity of capitalism’s coupling with technology — Elon Musk’s SpaceX — comes to the market at the absurd and obscene valuation of $2.11 trillion. Thus he, the world’s richest man, is funded and empowered to define progress according to his insanities: colonizing Mars and beyond with the seed of his loins and fevered dreams.

We cannot let this stand.

Diez asserts that “the situation is schizophrenic. On the one side, large swathes of Western societies seem to have lost faith that the future will be better. On the other side, a techno-optimist progress cult has established itself in Silicon Valley, promising incredible prosperity and undreamed-of convenience for all, because artificial intelligence will enable a giant leap in productivity.”

These extreme worldviews preempt reasoned public discourse over progress’ direction. “What does it mean,” Diez asks, “especially for a society that is experiencing the end of its old certainties, without having yet found new ones?” He says that in the past, progress equaled “technology plus values” and society was able to negotiate “how the advantages and gains of technological progress could and should be distributed.” I’m not so sure we’ve done such a good job of it of late. Still, he is right to add that today, we must recognize changed circumstances: the decline of the West in the face of advances by China, India, and Indonesia. “This makes it all the more urgent to formulate a concept of progress for the 21st Century.”

For this, Diez turns to the 19th Century, to the Industrial Revolution and the impact of the era’s coal, steel, and railway barons. “Driven by the first Industrial Revolution, a technological and economic transformation produced both mass proletarian misery and stark wealth.” Resistance to both gave birth to the politics of progress.

I write about a slice of this history in my upcoming book Hot Type, tracking the response of America’s oldest national labor organization, the International Typographical Union (ITU), as it was faced with the imminent arrival of the typesetting machine, the Linotype, in 1886. Having learned from the failures of the Luddites and Captain Swift against mechanical feudalism, as against the eventual perseverance of pressmen at the advent of steam, the union did not fight technology but instead insisted on controlling it and benefiting from its efficiencies, while leading the national movement for the eight-hour day and safer working conditions. The ITU flourished in pay and power until faced with a next technology it could not control (for that story, you’ll have to order the book).

Such was a spirit of “militant optimism,” in Diez’ words. “Progress, as was clear then and should be clear now, can only be achieved with technology, not against it.” The task is to balance certainly legitimate criticism of technology with a clear vision for how its fruits might benefit society.

The difference today, Diez says, citing VC Vinod Khosla, is that AI will shift the distribution of power and wealth to capital, away from labor. In response, Khosla proposes exempting the lowest-paid workers from income tax, making up the difference taxing capital gains; various AI boys have touted a universal guaranteed income. But note well that in his encyclical, Pope Leo XIV rejected the latter, for “work is not simply an instrument; it expresses and enhances the dignity of our lives.” Redistribution of wealth is imperative — see: the trillionaire — and should occur through taxation to support social programs.

A new concept of progress, Diez argues, must be conceived from the perspective of humanity. Amen. This is why I work on new educational programs that emphasize the humanities in the time of AI. And this is what inspired me to edit a new book series called Intelligence: AI & Humanity, to open the discussion to writers from the humanities and social sciences.

“Artificial intelligence challenges us to redefine who we want to be, both as individuals and as a community,” Diez observes. “It provokes questions such as: What constitutes quality of life for us?… A new concept of progress should be shaped neither by technophobia and austerity nor by the promise of exponential growth.”

Today, it has been left to the technologists — to the wrong sorts of technologists, often sophomoric dropouts: the Musks, Altmans, Thiels, Karps, Zuckerbergs, Bezoses— to impose their ideas of progress on the rest of us. There is no better example lately than Anthropic positioning itself as savior of humankind, touting its AI “constitution,” while building what it deemed to be AI so dangerous it could not be revealed to mere citizens — prompting Trump to ban it to foreigners, resulting in turning it off for all. This is not progress. 

No, progress must be the result of open public discourse and political discernment and negotiation. In the 19th Century, trade unions fought for their share of newly created wealth while social movements fought for justice: abolition and suffrage. Today, the debate over the limits and fruits of technology must be driven by new leaders representing the rest of the world outside Silicon Valley.

This is not to say that technologists should not be parties to the discussion. They should take part in the conversation based on the merit of their work and ideas, not their market caps. But as I have learned in researching and writing my histories of technology and media — of print, magazines, the mechanization and industrialization of mass media, and even the internet — one clear lesson I have taken away is that once a technology becomes commonplace and is put to use by others, the technologists inevitably fade into the background. They hold their power of as priests only temporarily, so long as their mysteries may prevail. This fall from the heights, I predict, will be their fate much faster in the case of AI, because it is the tool made so simple anyone can use it, and because so many of its masters are so deservedly disliked.

And that is why I share Diez’ arguments with you, for I agree that it is vital that we — workers, students, academics, creators, citizens — take charge of this new technology and of the discussion about its effects. We must define progress not in terms of the AI boys’ bullshit — AGI (artificial general intelligence), ASI (artificial superintelligence), the end of labor, the colonization of unlivable Mars, a world post-humans — but in human terms: dignified work; shared wealth; the benefits of science, art, and creativity; education for all; equity and justice; and community. It is our future we need to map, a task far too vital to leave to programmers and capitalists.

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I am delighted that Montclair State University (MSU) has won its bid to take over New Jersey public television, for in this moment I see an opening to reimagine and reinvent public media in a new image — as the public’s media. 

And nowhere better for that to happen than in New Jersey, where threads have been coming together over years — most running through MSU — to support and grow the broader news ecosystem in the state. This support has come from private-public partnerships working with the university in what we have come to call the New Jersey Model. 

Adding public television adds one more piece. Montclair State has first-rate television facilities and the chance to involve students and faculty in producing content for the channels. But to me, television is the least of it. 

What really excites me is that Montclair has the opportunity to build on the strong foundation of its NJ News Commons and Center for Cooperative Media, which now serve more than 300 independent, community-based news providers, new and old, small and large.

Here I want to tell you the story of how this has evolved from what I have seen. I don’t mean to paint myself as a Zelig of the tale, as most often, I merely witnessed and cheered what has been happening. But I have been proud to have had the opportunity to watch as a new vision for local news, media, and community has been built here — a vision I’ve long believed in. I am also proud to say that I am a fellow at MSU’s Center for Cooperative Media, where I hope to help work toward that vision. 

For me, this saga goes back three decades, when I began beating the drum for thinking of news through the lenses of ecosystems and communities over newsrooms and corporations. I was doing that while working as president and creative director of Advance.net, where we started NJ.com while developing hyperlocal news, and then in my research on news ecosystems and innovation at CUNY. 

In New Jersey, this history stretches back at least as far a 2011, when then-Governor Christie sold off the state’s public media — and bandwidth in an FCC spectrum auction — to plug a budget hole. It was a short-sighted decision that robbed the state of its only broadcast outlets. The president of Montclair State at the time, Susan Cole, very much wanted to take over NJ’s public media. The state instead gave the TV and radio stations to WNET and WNYC in New York and WHYY in Philadelphia.

When that happened, an emergency meeting was convened in Newark with journalists and political leaders brought together to consider what to do about our state and news. Some wanted to start a newsroom. I instead beat my ecosystem drum, arguing that we had the chance to support the growth of news outlets in communities across the state, now made possible by the internet. 

Soon, the Dodge Foundation — where I was an advisor and would serve for a time on the board — convinced Montclair State that it had the chance to support and grow the state’s independent and open news ecosystem with the creation of the NJ News Commons, headed at first by hyperlocal blogger Debbie Galant. At Advance, I had tried to persuade Debbie to start a Montclair blog on our site. “Good idea, Jeff,” she said. “But why the hell would I do that for you?” She was right. Instead, she founded Baristanet, a pioneering, independent hyperlocal blog that lives on in a merger that is now Montclair Local.

Debbie had the trust of the ragtag bunch of very independent local bloggers who were trying to make a go of it covering their towns online — and who frankly did not trust big, old news media. The Commons’ mission was to support those local news outlets with training, mentorship, and collaboration — not to compete with them by making a newsroom and content with it. 

The Commons led, in turn to the founding of the Center for Cooperative Media, which under the leadership and vision of Stefanie Murray has been doing pathbreaking work. The Center has just launched a news-sharing network across the state’s ecosystem, funded by the Google News Initiative. It conducts research on communities’ information needs. It helps local news sites with their business and technology and it brings them together for collaborative projects. This is the foundation on which the real public media of New Jersey — the public’s media — is already being built. 

After Christie denuded New Jersey’s media, the legislature was lobbied (read: guilted) to fund support for New Jersey news with the creation of the NJ Civic Information Consortium, which gives grants to applicants from across the state that meet its criteria for supporting the information needs of under-served communities and developing new models for sustainable news. 

Together Montclair State’s Center and the Consortium — working with the hundreds of outlets in the state — have demonstrated what could be done when private and public, journalistic and academic entities work together for the good of communities. Back then, Tom Glaisyer of the Democracy Fund, dubbed what was happening here the New Jersey Model, and he vowed to spread it to other states in the nation.

I’ve testified about the New Jersey Model before legislators in California, Oregon, and Illinois as I’ve tried to dissuade them from passing legislation written by lobbyists for the old, hedge-fund-controlled newspaper industry as it seeks handouts via protectionist, retributive taxes aimed at tech companies. Instead, I say, look at what Jersey has done to build something bigger and better, more open, inclusive, and innovative, by offering support to folks who want to cover and serve their communities.

To be clear, I am not suggesting that old media should be left out of this future. I just joined the board of the not-for-profit that acquired NJ Hills Media, a chain of local weekly papers and sites. Through the Montclair State connection, NJ Hills is reaping benefits from the connection.

Enter MSU’s Professor Carrie Brown. We worked together at CUNY to build a new program in engagement journalism that she directed, centering communities and their priorities in students’ work. Both of us left CUNY and came to Montclair, where Carrie is bringing the values of the movement she has pioneered to classes and to the ecosystem.

In the latest term, Carrie had her engagement students go to listen to residents of Parsippany, where NJ Hills just started a new, online-only and free news site. A few weeks ago, the students presented the reporter covering the town, Nicole Flanagan, and her boss, NJ Hills CEO and publisher Joe Territo, with their findings and recommendations for coverage. Halfway through the presentations, Joe turned to me, saying he wanted help like that in every one of the towns the company covers. 

Meanwhile, at Montclair, we are looking at other new programs, including potentially working with libraries in towns across the state as information hubs for their communities. That, too, is part of New Jersey’s news ecosystem. 

This is the environment into which the new New Jersey public media fits. Stefanie Murray, alongside Keith Strudler, dean of MSU’s College of Communication and Media, and the university’s president, Jonathan Koppell, created the winning bid to convince the state to bring our stations back to our air after WNET decided to drop its franchise. I had no role in the process, other than getting to read and comment on the proposal in progress. I am confident that MSU’s team will use this opportunity to bring imagination, innovation, and inclusion to the task. 

Here is Strudler illustrating how this all comes together around MSU’s vision of the public’s media:

We’ll have staff reporters — North, Central and South Jersey coverage to start, with a full-time Trenton reporter as an aspiration. But the bigger story is what’s already out there. There are hundreds of content creators across New Jersey — people doing serious storytelling on YouTube, TikTok, Instagram, local news sites — who already have audiences and are already doing good work. Our goal, working with the Center for Cooperative Media, is to figure out how we partner with those people. How we give them a bigger platform. How we extend our reach without pretending we can do everything ourselves….

The Center for Cooperative Media has been better than almost anyone in the country at building networks of storytellers across platforms. That’s going to be a real asset. And the best approach is to go to those communities and ask what they need — not come in from the top down and say we know what New Jersey wants.

Amen.

This is also a chance to rethink television. In the long-ago, I was TV critic for People and TV Guide, and so I have opinions. That is why, in the mid-1990s, my frequent boss and mentor Jim Willse — former editor and publisher of the NY Daily News, later to be the editor of Advance’s Star-Ledger — brought me in to consult on a project to launch a 24-hour news channel in NJ. I devised an eccentric content plan that proposed building the studio in New Jersey’s real main street — a mall. And so we could hear the voice of the people, I borrowed an idea from Canadian TV pioneer Moses Znaimer, whose CityTV built a “speakers’ corner” on a Toronto street, so anyone could record a message that might be included in a TV show. What became News12 New Jersey did build a kiosk to capture vox pop and parked it in a mall, for a little while, until Advance left the project. 

Of course, today, we have the ultimate speakers’ corner in the internet, where even with its problems, communities can come together to share knowledge and need. Journalism should begin by listening to them. This is where and this is when the public’s media can be built, here in my home state, Jersey. 

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Artificial Intelligence, though more than a half-century old as a technology, has occupied front-of-mind cultural consciousness for only a few years, since ChatGPT. Yet AI is already profoundly disliked and distrusted in both media meme and apparently in public opinion.

The techlash against the internet and then social media took at least two decades to ferment, while the AI backlash feels more like an instant reflex. Fifty-seven percent of Americans say AI’s risks outweigh its benefits, making it less popular even than ICE! Half fret about its ill effects on creativity, meaningful relationships, news, and elections. In rare consensus, Republicans and Democrats alike are NIMBYing data centers across the nation. A German digital conference offers a workshop in poisoning AI data. The FT declares “a new Luddite movement.” And commencement speakers daring to utter the letters A and I are sure to be booed.

It is, however, difficult to discern true public opinion from performative public opinion polls, as polls reflect media’s self-fulfilled prophesies. In reality, even as views of AI sour, the public’s use of the tools soars: more than half now employ it to, for example, research topics of interest, a thirty-eight percent increase in a year.

Who or what is to blame for AI’s bad rep? In The Web We Weave, I assert that the problem is less the AI than certain AI boys who make up the newest oligopoly. Look no farther than the now-finished OpenAI trial: technology’s Godzilla v. Mothra, unlikeable Musk v. unreliable Altman. Now add the creepy dramatis potens of West Coast billionaires (before they all dodge taxes and move to Miami) — Thiel, Andreessen, Karp, Zuck, Ellison, Bezos — plus the moral entrepreneurs trying to pump and exploit technofear (Tristan Harris, Eliezer Yudkowsky, Nick Bostrom, William MacAskill, Dustin Moskovitz) — and it’s no wonder people profess dislike for their algorithmic progeny. And it doesn’t help relations when they dismiss us humans as “meat computers.”

Yet AI is amazing, constantly wowing even the skeptical with its feats and tricks. Every week on the two (yes, two) AI podcasts I co-host — AI Inside and Intelligent Machines — I both both marvel at and fault the capabilities and implications of this new and powerful technology. Because I am also editing a new Bloomsbury book series about AI and humanity, I am constantly trying to get my head around how AI works, what it can and cannot do, what its benefits and perils might be, and what its creation, use, and product says about us as humans.

To learn more about AI, I do not turn to the boys above. I turn to critics, yes; there are many. But to understand AI’s innards I find it best to look to a few of the field’s master communicators and teachers, notably Jensen Huang, founder and CEO of Nvidia, and Yann LeCun, NYU professor and founder of the new AMI Labs. Unlike AI’s blind proselytizers, they do not market superheated claims of superintelligence a day away, nor in the doomsters’ dire warnings of AI-combusted human extinction.

Below are videos of each; dip in and you will learn more about AI.

Each man has clear economic interest in the success of AI; Huang leads the world’s largest corporation by market valuation and LeCun has raised $1 billion to envision a next generation of AI, past LLMs. Each tries to present realistic and credible perspectives on the present and near-future state of the art and technic of AI. Each calls bullshit on others when warranted. The most important reason I watch these two is because in their public appearances, each educates, addressing multilayered constituencies: customers, partners, investors, employees, policymakers, journalists, students, and the public.

I am fascinated by their presentation skills because, as a journalist, we’re supposed to be communicators. They also interest me because I am a visiting professor at Stony Brook University, where I work with the Alan Alda Center for Communicating Science (see this Wall Street Journal report explaining their work). I am trying to dissect these technologists’ skills at communication to see how others might communicate technology more effectively and honestly for more informed and necessary public discourse.

All this is why I became a loyal connoisseur of Huang’s keynotes. They are bravura solo performances: two hours or longer on stage before appreciative industry audiences, presenting new product announcements while holding up and showing off chips and boards that are, in truth, as enigmatic in their appearance and ways as an obelisk to a 2001 ape. All the while, he explains Nvidia’s accomplishments and position in the field and the market. It shouldn’t be mesmerizing, but to me, it is.

As a student of Huang’s addresses, I soon learned that in each, he has a new lesson to impart, in addition to promoting a new chip or software or deal. The first talk that really hooked me was his Nvidia developers’ conference keynote of March, 2024. In it, he helped me begin to grasp the scale of AI technology.

For a next book project on the birth and death of mass media, I’ve been reading up on the invention of the the triode vacuum tube and amplifier in 1906, which enabled radio as well as the loudspeaker. Four decades later, the tube was superseded by the transistor and eventually, in 1958, the chip. (BTW, if you’re interested in that history, I recommend Conquering the Electron: The Geniuses, Visionaries, Egomaniacs, and Scoundrels Who Built Our Electronic Age by Derek Cheung and Eric Brach.)

On stage in 2024, Huang announces a new, bigger chip — a GPU or graphics processing unit named Blackwell — that holds 208 *billion* transistors shunting electrons and with them logic and knowledge. Then AI-generated animation on the giant screen behind him multiplies those chips in racks and in turn multiplies racks—each component clicking into place with satisfying, synthetic clunks — to add up to an entire data center populated with 32,000 GPUs — thus six quadrillion transistors. Mind blown. Here is that moment, beginning at minute 26:

Huang’s lesson in that keynote is the value of scale, for the wonders of generative AI have been made possible not only by Google’s theoretical breakthrough in 2017 but by the massive computing power (“compute” in their abbreviated argot) powered by Nvidia’s processors (and megawatts).

In that and subsequent keynotes, Huang imparts more lessons. He lectures on the economy of tokens — generative AI’s numerical abstractions of words, for instance, which LLMs create to calculate their predictions. He explains the need to manufacture tokens at ever-high speed and ever-lower cost in the data centers he characterizes as factories (of tokens). He declares the end of Moore’s Law, which since the 1960s predicted the rate of growth of the number of transistors on a chip: a 100x increase in computing power every ten years. Huang touts instead what he calls accelerated computing, boasting that Nvidia’s chips and its CUDA software platform have multiplied computing power 1,000x in just eight years.

I am transfixed as he animates the idea of digital twins: how AI, trained on a massive number of possible scenarios, computes every alternative that could next face a factory robot or an autonomous car. (I am so taken with the idea of the digital twin that I keep imaging there’s a novel in it: the machine that predicts the consequences of every choice we face.) It is clear from what he shows off that Huang believes robotics represents the next industrial explosion.

Last fall, Huang gave a keynote to Nvidia’s Washington conference, in which he deftly thanks the Trump administration and Department of Energy for helping his industry’s cause, without sacrificing a gold bar or too much dignity. Here he wants to teach policymakers about the needs of the industry that is holding up our economy even with tariffs and war.

It turns out Huang is not just a presenter but also an effective debater. See him here making his case for allowing sales to China as a benefit to American industry, in this podcast with Dwarkesh Patel.

Huang took a company that began making chips to power computer — and particularly game — graphics and positioned it to be at the heart of the AI explosion, its market valuation exceeding $5 trillion. If anything would give a CEO license to make outlandish claims and predictions, that would. But Huang doesn’t talk about flying to Mars. Instead, he tries to explain the value of what is being built. To his DC audience, he asserts that “AI is not a tool. AI is work. AI is work that can use tools.” I think that is new.

If you’re hooked now like me, watch his latest California keynote, in which he talks about the agentic age suddenly upon us.

Yann LeCun is a different kind of communicator. He is first and foremost a researcher and educator, secondarily now an entrepreneur. I have tried to read and watch his presentations to NYU students and I must confess that not too long in I regret my success at dodging higher mathematics courses … in high school. Yet LeCun is also an effective communicator even to humanities dolts like me. Here he is a year ago patiently explaining his perspective on AI to Jason Howell and me on our podcast, AI Inside:

Getting to speak with LeCun is a privilege, for he is one of AI’s godfathers (though, as he says, living in New Jersey, he’d prefer a different honorific). Among his many accomplishments and recognitions, he has received— alongside Yoshua Bengio and Geoffrey Hinton — the 2018 Turing Award for work on deep learning.

What I value most about listening to LeCun is that he does not suffer bullshit, whether that is claims of imminent superintelligence or prognostication of inevitable disaster for jobs or humankind itself. As a clear-eyed academic, he never shies away from debate or disagreement rooted in research.

Lately, LeCun has developed a reputation as a contrarian regarding LLMs, though his is a view he has long held. While the putative Wunderkinder of the infant industry — the leaders of OpenAI, Anthropic, et al — insist that all they need is ever-more compute to reach their Everest of so-called artificial superintelligence (any day now), LeCun argues persuasively — to me — that LLMs, though impressive and useful, are essentially a dead-end, for they traffic in text, which represents a finite sphere of representation of life.

LeCun has argued instead for devising world models to teach the machine the sort of experiential constraints a toddler or a kitten can learn: about gravity acting upon a ball falling off a table, where it persists, though now unseen. If one wants to build AI for the real world, one must conquer Moravec’s paradox: that “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” This from LeCun’s presentation:

For an effective starter course in LeCun’s worldview, I highly recommend watching him debate LLMs vs. world models with Google DeepMind’s Adam Brown, in this Scientific Controversies discussion moderated by Janna Levin at Brooklyn’s Pioneer Works.

In 2022, LeCun published a paper proposing a “path towards autonomous machine intelligence… enabling them to reason, predict, and plan at multiple time horizons… [as] intelligent agents.” Or as he sums up the goal: to work with common sense. Here, too, is a 117-slide presentation he made to NYU students explaining his ideas. I’ll admit I am soon lost in the formulae, though the lecture isn’t meant for the likes of me. This is how he instructs students, fellow computer scientists, competitors — and now funders, as LeCun has founded AMI Labs to build advanced machine intelligence on his model for the future, which he calls Joint-Embedding Predictive Architecture (JEPA).

I will do a bad job summarizing his proposal; that’s why I offer the videos below, for they are far more effective at communicating the ideas than I am. But in short, LeCun describes using photos and videos from real life to train models — or to train them to train themselves — so they understand representations of the world and consequences of actions, rather than trying to predict every pixel or merely ape human teachers. That is, his method can discern, say, a ball as a ball and predict the result of action on it. JEPA does this by encoding an original image alongside a corrupted version so the system can, in LeCun’s words, “predict the representation of the original image from the representation of the corrupted one.”

The implications are many. LeCun says JEPA will lead to models that can undertake a wider variety of tasks with less training, for they do not need to be taught every possible permutation of a situation. These models are also more efficient, for they concentrate attention on particular change — a ball thrown — rather than every change — countless leaves rustling in the scene — and need not predict the progress of every pixel.

He says these systems will be capable of thinking. Unlike LLMs, they won’t — at first — listen or talk, which might make them less flashy than ChatGPT or Claude: fewer neat parlor tricks to convince journalists that they’re in love. But LeCun convinces me that being able to understand the world and its constraints and to operate in it is table stakes for the next paradigm of AI. This is what it will take for AI to deliver value to industry, including in robotics, industrial control, and health care. He also is persuasive when he argues that his framework will be safer than LLMs, for rather than producing the general machines that their creators claim can do everything better than all of us — as the AI boys insist — JEPA will produce specialized agents with bounded tasks, each built to “anticipate the consequences of its own actions.” JEPA won’t take over the world. LLMs, LeCun says, can be dangerous; haven’t we learned that?

He says he is building “AI for the real world” — that is, world models — for as it turns out, “reality is way more complicated than language.”

If you want to dig into LeCun’s view of AI’s future (and understand why, on my podcasts, I regularly declare myself on Team Yann), here is a series of videos, stepping up in complexity. The first is a casual conversation with Jacob Effron:

Next is a more technical and deeper explanation of JEPA from Welch Labs. I had to watch a few times to understand some (not all) of it. It is an excellent primer (and here is part 2.

And here is a video in which LeCun does not speak. It is a victory lap for his vision of building reasoning: building a system that can solve any problem given a set of constraints rather than just generating a next token (or writing a brute-force, old-fashioned program). The host, Ksenia Se of Turing Post, extols JEPA (but notes that it is “quite a tragic name for a beautiful idea”).

Note the title of the video: “Yann was right.” To which Yann added when he shared it on his socials, “But of course I was.” (That’s another reason I like both these men; they have a sense of humor that is not evident in the other AI boys.)

What I most appreciate about LeCun is the humility inherent in a scientist’s worldview. The generative AI companies display the hubris of believing they are almost done building the general machine that can take over every human task, or destroy us in the process. LeCun is, instead, on a scientific journey of discovery and iteration. He knows there is yet much work to be done.

I also greatly respect his support for open source. When he was at Meta, heading a lab and then advising on AI, he fought for it to release its Llama models openly. This is how academics and scholars work: inviting challenges, teaching others, and collaborating and learning together.

AI is here to stay. There is no wishing or protesting or regulating or boycotting it away. We must not surrender its future and ours to a few oligarchic billionaires. The only way we can have a voice in its direction is to understand it better. And the only way we can understand it is by listening critically to the people actually building it. That is why I want to see technologists better able to communicate about technology — so we can debate it and its effects. That’s why I’m studying these two masters of communication.

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Eddie Glaude, Jr., holds a mirror up to America. Look, he tells us, look! How often I have heard him on television, invited to the camera by Nicolle Wallace to lament another American tragedy and sin: racist murders, the shooting deaths of mere babies, the abuse of immigrant children, the bigotry of the president. Do not say that this is not us, he demands. This is us. This is America. The italics are his. Unless and until we, we white Americans, acknowledge and absorb that truth, he tells us, we cannot and never will move past it. 

Glaude’s new book, America, U.S.A.: How Race Shadows the Nation’s Anniversaries, is that mirror, reflecting the worst of our reality in sharp detail. He uses the moment of the nation’s already spoiled 250th anniversary to look back on earlier birthdays, on earlier assertions of an American ideal that were always in fact claims to a white America. Those claims have met their lowest ebb in Donald Trump and his klan’s brazen denials of the nation’s racism and any remedies. Diversity is as much as illegal. Racism is now the de facto law of the land. 

His book is a stunning, damning indictment and conviction of our nation. I cannot recommend it more highly. Best yet, I commend you to listen to the audiobook, read by Glaude. More than once over the years, at the beginning of a Princeton term, I have wandered through the downstairs stacks in my favorite bookstore, Labyrinth, to see what texts are being assigned in the classrooms across the street. I always stop at the shelves filled with those selected by Prof. Glaude, wishing I could sit in his class and learn. To hear him read this book is to witness his teaching. 

While I was listening to the book, I joined Julie Roginsky and Michelle Kinney for our every-Friday lament about the state of news and media in the podcast we call Breaking the News. What was most broken last week was, of course, CBS. As we were cursing the murder of 60 Minutes at the hands of Bari Weiss and the Ellisons, Michelle said something most wise: that sometimes, rather than wishing to recapture what is lost, we must simply mourn it. 

Yes, 60 Minutes is the dead show walking. CBS News is already dead. CNN is likely doomed. The Washington Post might as well be buried. The New York Times fails us constantly in the face of fascism. Sinclair is brainwashing towns across the nation, where hedge funds have ruined most every newspaper. Ultimately, I contend, it is mass media that is dead and doesn’t know it. I no longer think it is worthwhile to wonder how to fix it. Instead, I mourn it and ask what will replace it. 

In this context, I brought up Glaude’s book and said that he forces me to mourn not an America that was but an America that never was: a fantasy of the nation. 

My grandparents were, frankly racist. And so I was proud of my parents for raising my sister and me to recognize and reject their way of thinking. But what my parents wanted to replace it with in my mind was the American myth of the melting pot. It was too many years later that I saw the inherent falacy in the contention that harmony would come at the expense of identity and history, as if we in power, we white Americans, would ever admit others into our pot of privilege. To be colorblind, as was the aspiration of the time, was to be blind to history, to the effects of racism and the benefits of our own birth. 

Just as I see that in my own field, to which I have devoted fifty years of my life, it is fruitless and ultimately delusional to think there ever was something better to return to, so I understand that an America of principles can only be built anew, following the full realization of what it was and still is. Each must be replaced.

What Glaude forces his readers to do is to face the reality of racist America, the crusade to declare the U.S.A. a white nation and to exclude all others. He calls us to a radical new birth. It is brilliantly written, forceful in its poetry, unflinching in its honesty, demanding in its teaching. 

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