Without being overly technical, let’s look at the attributes of any item (token/document/image/currency, etc.) stored in a blockchain. Here’s what you get:

• It’s indelibly time-stamped – anyone, anywhere in the world can verify exactly when the item was added to the blockchain. It follows that the item (whatever it is) must have been created before that date.
• It’s unmodifiable – when we write checks, we use ink because it can’t be modified. The blockchain brings the same benefit to digital items.
• It can’t be eradicated – nobody can destroy an item stored in the blockchain.
• There’s only one original – you can make copies, but the original is the real deal. And the original is easy to identify.
• Any transaction involving the item (a sale, for instance) will similarly be time-stamped, unmodifiable, and ineradicable.

What kinds of items would benefit from these attributes? Here are some categories:

• Legal documents – any document stored on the blockchain is essentially inviolable. We know its entire history and anything/everything that’s been done to it. I can foresee a future where only blockchain-stored documents will be legally enforceable. Indeed, I think I’ll store my will as an NFT so there can be no debate amongst my heirs as to what my intentions are.
• Ownership records – property records can result in unending discord if there’s any doubt about their veracity. For instance, if land ownership records disappear, how do we decide who has the right to use the land? The Peruvian economist, Hernando de Soto, suggests that land titles and deeds should be stored in a blockchain to preserve their integrity.
• Idea precedence – the entire scientific establishment is driven by idea precedence. Who made the discovery first? Who can claim credit for creating a new idea? Millions of dollars in royalties and patent rights can ride on date stamps. Blockchain dates are easily verified and inalterable.
• Artwork – a newly discovered Van Gogh painting recently sold for $19 million. Yet I can buy a nice poster of the same artwork for roughly $20. We all know that the original is worth much, much more than a copy. Yet how do we know if a digital item is an original? The blockchain knows. Indeed, this is the use case for the current NFT mania – it differentiates the digital original from digital copies.
• Provenance – where did the item come from? Whose hands did it pass through? Was it stolen or did it come to market legitimately? Dealers in historical artifacts wrestle with these questions every day. A token on the blockchain can record not only the item itself but also everything that has happened to the item over time.

Ultimately, the blockchain is about trust. Do we trust paper documents to accurately record who owns a piece of land? Or whether Scientist X created an idea before Scientist Y? Or whether an artwork can legally be sold? Once the hype settles down, I think the true value of the blockchain is that it can help us verify facts, enforce legal rights, and establish a climate of trust. That’s not hype.

Wear a mask!

I like to think of Blaise Pascal (1623 — 1662), the French mathematician, as the western world’s first practitioner of Twitter. His collected Pensées were brief, enigmatic thoughts about mathematics, religion, and philosophy. Collected after his death, they read like tweets from the 17th century (though they were intended to be a much more comprehensive defense of religion).

In the Pensées, Pascal made his famous wager. We all bet with our lives on whether God exists or not. We can live as if God exists and practice the traditional forms and virtues of religion. Or we can do the opposite and ignore our religious duties, assuming that God does not exist. If we live as if God exists and we’re right, then the rewards are infinite. If we’re wrong, the loss is finite. Indeed, it’s quite small – we’ve wasted some time in church and in prayer. Thus, Pascal argues, it’s only rational to live a pious life. The wager is heavily stacked to that side.

I’m applying the same logic to face masks in the time of coronavirus. I don’t know if face masks will protect me – or those around me – from a viral infection. Most scientists seem to believe that masks help dampen the disease’s spread. But some scientists take vigorous exception and argue loudly the face masks do no good at all.

So, who’s right? Like most Americans, I’m not qualified to judge. But I am qualified to apply Pascal’s wager. Let’s say that I bet that face masks offer useful protection and decide to wear them regularly. Now let’s guess that I’m right; I win the wager. What have I gained? The face mask may have protected me from a nasty and long-lasting infection. Indeed, since I’m over 60 and have some underlying health conditions, the mask may well have saved my life.

But what if I’m wrong? What have I lost? A few dollars for a supply of masks and a few hours of discomfort while wearing them. In other words, not much. So, the bet is stacked. I could gain a lot. But even if I lose, I don’t lose much. As Pascal might conclude, it’s only rational to wear a mask.

And, when I’m not wearing a mask, I’ll reflect on one of Pascal’s most famous tweets: “All of man’s problems stem from his inability to sit still in a room.” Pascal sums it up pretty well. Either sit still in a room or wear a mask. Thank you, Blaise.

I recently saw an ad for Progressive Insurance that says, “Drivers who save with Progressive, save $796 on average.”

Now I like Progressive. And I love Flo. So, I’m sure that the statement is true. I’m sure it’s based on fact.

But it also entails a logical fallacy. If you don’t spot the fallacy, you may easily assume that the average savings for all drivers who switch to Progressive is $796. That would be a mistake.

This is a good example of the survivorship fallacy. We only examine cases that “survive” a certain threshold. In this case, the threshold is drivers who save. What about drivers who didn’t save?

Let’s say that we have 1,000 drivers who saved money. In fact, they saved a total of $796,000. On average, they saved $796 each.

Now let’s say that another 1,000 drivers saved nothing. Now we have 2,000 drivers who saved a total of $796,000. On average, they saved $398 each.

When we consider those people (or cases) that didn’t survive the threshold, the numbers change dramatically. You might hear an investment company say, “Investors who have stayed with us for ten years, made an average of 7.3% per year.” The threshold is stayed with us for ten years. Your question should be, “Well, what about those who didn’t stay for ten years?”

The survivorship fallacy doesn’t just affect numbers; it also affects qualities. Let’s say a prominent management journal publishes an article that proclaims, “The Ten Most Innovative Companies In The World Do These Three Things.” The threshold for selection is the ten most innovative companies (however that is measured). It’s quite possible that many other companies do the same three things but aren’t nearly as innovative. Since they didn’t survive the selection criterion, however, we don’t consider them.

What’s the moral? When you see an ad, put your critical thinking cap on. You’re going to need it.

That’s the upshot of a study recently published in American Psychologist. The authors, Shigehiro Oishi, Minkyung Koo, and Nicholas Buttrick, correlated neighborhood walkability with intergenerational upward social mobility. The basic finding: kids who grow up in walkable neighborhoods are more likely to move upward – as compared to their parents – than kids who don’t live in walkable neighborhoods.

The authors begin by noting that “Although upward mobility is generally in decline in the United States …it is easier to get ahead in some parts of the United Sates than in others.” Kids growing up in Pittsburgh, for instance, are much more likely to rise from the bottom 20% (as kids) to the top 20% (as adults) than are kids growing up in Charlotte, North Carolina.

Why would that be? Previous research had identified five factors associated with socioeconomic fluidity for a given area. These are “1) less residential segregation, 2) less income inequality, 3) better primary schools, 4) greater social capital, and 5) greater family stability.” (Social capital is a measure of community participation, including the proportion of people in a given area who vote, volunteer, and otherwise engage in community activities).

Oishi, Koo, and Buttrick accept the “Five Factors” and ask an additional question: does the walkability of a neighborhood also contribute to social fluidity? The authors conducted four different studies to answer this question. Here are some of the top-level findings.

• Comparing 389 commuting zones with walkability ratings from walkscore.com, “showed that upward social mobility was substantially higher in more walkable commuting zones than in less walkable commuting zones.” (r = .390, p<.001)
• But, wait. Maybe it was the Five Factors as opposed to walkability per se. The researchers held the Five Factors constant and found that “walkability explained 11% of additional variance uniquely” beyond the Five Factors. (R2 rose from .41 to .52).
• But, wait. Maybe walkable areas are also more liberal politically – and the liberal policies promote social fluidity as opposed to walkability. Or maybe it’s because walkable areas are healthier and healthier people are more socially fluid. Nope. The researchers held these variables constant (as well as several others). “Overall, walkability was a robust predictor of upward social mobility beyond factors previously used….”
• Why, then would walkability promote social fluidity? One finding is that people have less need for cars in walkable neighborhoods. People without cars can compete effectively for jobs in a wider geographic area.
• Additionally, walkability seems to promote a “sense of belonging” in a neighborhood. The researchers found that these feelings of belonging were “themselves associated with upward social mobility”.
• Does it only work in America? Does this reflect the individualism of America or is it also present in more collectivist societies? The researchers collected data from South Korea, which they describe as a “vertical, collectivist culture”. The finding: “… frequency of walking was indeed associated with a greater sense of belonging, which was in turn associated with upward social mobility.”

This study raises bigger, broader questions as well. Numerous commentators have noted that upward mobility in the United States has declined precipitously over the past 50 to 75 years. Baby boomers may be the last generation to do broadly better than their parents.

This time frame corresponds to the growth of suburbs and our increasing dependence on cars. We can surmise that more people today live in non-walkable areas than they did, say, in 1950. Perhaps this migration explains why upward mobility is declining. As we spread out horizontally, we grow isolated and have less sense of belonging. Though the automobile is a vehicle for geographic mobility, it may well be an obstacle to social mobility.

In the course of writing this article, I discovered a great website: walkscore.com. The site provides walkability ratings on a scale of 0 to 100. For instance, our home in Denver gets a walkability rating of 51. We can walk to some restaurants and are close to some pretty good public transportation. By contrast, our little apartment in Brooklyn gets a walkability score of 99. We could easily live there without a car. Check it out. It may change the way you view your neighborhood.

Kuhscheiße!

All humans want to connect the dots. We want to explain why something happened – or will happen — by linking events through time. A caused B caused C and that will cause D. When we do this in the past, we call it history. When we project it into the future, we call it politics.

We want to connect the dots because we deeply desire a sense of control. If we can explain why something happened in the past, we believe that we can control it in the future.  If X causes Y and we don’t want Y to happen again in the future, then we can work very hard to eliminate X. We can control the future because we can explain the past in mechanistic terms.

The past, however, is a very rich source of causes and effects. It may be that X causes Y in some circumstances. In other cases, perhaps P causes Y. In still other cases, the combination of X, P, and Z causes Y – but only if X, P, and Z occur in a certain order. If we look hard enough, we can use history to prove anything we want. Liberal historians find liberal causes. Conservative historians find conservative causes. To paraphrase Ernest Rutherford, this isn’t physics, it’s stamp collecting. One side collects red stamps; the other side collects blue stamps.

We often underestimate the role of chance in the shaping of events. As Hans Zinsser pointed out in Rats, Lice, and History, a lot of stuff happens by accident and stupidity. The right person is in the right place at the right time and we have a victory. The right person is not in the right place at the right time and we have a tragedy. Stuff happens for no apparent reason.

Yet we still have a need for control. So we make stuff up. The fancy term for this is confabulation. Wikipedia defines confabulation as a “memory error defined as the production of fabricated, distorted, or misinterpreted memories about oneself or the world, without the conscious intention to deceive.” It’s not a lie; it’s an illusion.

We used to think that confabulation was a sign of mental illness. Today, we believe that every human does it. It’s a simple way to deal with a reality that we can’t explain or control.

The French philosopher, Henri Bergson, developed the related idea of “retrospective illusion”. As we “…consider our actions in the past, we have the illusion that they could not have developed in any other way. At the moment, however, our actions seem indeterminate.” We see the past as an eternal chain of causes and effects that could not have happened in any other way. According to Bergson, it’s an illusion. We see the path of history clearly. What we don’t see is how it might have lurched in a different direction because of some random event. (Bergson’s concept is also known as retrospective determinism).

Even the best histories by the best thinkers must necessarily omit most of reality. As Mark Twain wrote, ““In the real world, the right thing never happens in the right place and the right time. It is the job of journalists and historians to make it appear that it has.” We simplify the real world so we can comprehend it and control it. As we simplify, we also make mistakes. Perhaps Hegel (pictured) was right: “History teaches us nothing except that it teaches us nothing.”

3271                            2987                2769                            3389

2587                            3266                4022                            4231

3779                            3378                4388                            5327

2964                            2864                2676                            3653

3453                            4156                3668                            4218

Why would you suspect fraud?

Before you answer that, let me ask you another question. Would you please write down a random number between one and 20?

Asking you to write down a random number seems like an innocent request. But the word “random” invokes some unusual behavior. It turns out that we all have in our minds a definition of “random” that’s not quite … well, random. Does the number 17 seem random to you? Most people would say, “Sure. That’s pretty random.” Do the numbers 10 and 15 seem random to you? Most people would say, “No. Those aren’t random numbers.”

Why do we have a bias against 10 and 15? Why do we say they aren’t random? Probably because we often round our numbers so that they end in zeros or fives. We say, “I’ll see you in five minutes (or 10 minutes or 15 minutes)”. We rarely say, “I’ll see you in 17 minutes”. In casual conversation, we use numbers that end in zeros or fives far more often than we use numbers that end in other digits. Because we use them frequently, they seem familiar, not random.

So, if we want numbers to look random – as we might in a fraud – we’ll create numbers that fit our assumptions of what random numbers look like. We’ll under-represent numbers that end in fives and zeros and over-represent numbers that end in sevens or threes or nines. But if the numbers are truly random, then all the digits zero through nine should be equally represented.

Now look again at the reported numbers from the precincts. What’s odd is what’s missing. None of the twenty numbers end in five or zero. But if the numbers were truly random, we would expect – in a list of 20 — at least two numbers to end in zero and two more to end in five. The precinct numbers are suspicious. Somebody was trying to make the numbers look random but tripped over their own assumptions about what random numbers look like.

Moral of the story? If you’re going to cheat, check your assumptions at the door.

By the way, I ask my students to write down a random number between one and 20. The most frequent number is 17, followed by 3, 13, 7, and 9. There is a strong bias towards odd numbers and whole numbers. No one has ever written down a number with a fraction.

I earned my Ph.D. in 1984. The hard skills I learned are now out of date. But I still use many of the soft skills most every day. One hard skill I learned, for instance, was how to code in Fortran. Not much call for that today. But I also learned how to use statistics, do experiments, weigh evidence, reach conclusions, defend my thinking, and communicate effectively. When companies invite me to consult with them, they want my process skills, not my Fortran skills.

We have traditionally paid more attention – and more money – to hard skills. After all, hard skills are … well, hard to come by. As such, they must be worth more. My Fortran skills were hard to master, useful, and hard to replace in the job market. They were worth paying for.

Hard skills, as traditionally defined, are often quantitative, structured, or rules based. They may include accounting, physics, financial modeling, proficiency in certain software packages, programming, data mining, data analysis, diagnostics, and so on. They are also teachable and testable. You can find plenty of coding bootcamps, for instance. If you want to know whether someone can program in Python, you can easily devise a test to find out.

Soft skills, on the other hand, are “…more intrinsic to personality and more difficult to judge quickly.” Soft skills include the ability to get along with others, the ability to explain things, self-control, ability to focus, creativity, empathy, critical thinking, politesse, ability to negotiate effectively, and wisdom. You may not be born with soft skills, but you typically don’t acquire them in the classroom. You learn them from life.

Additionally, hard skills tend to be immune to culture. Programming in Python is pretty much the same whether you’re French, or American, or Japanese. Soft skills often vary by culture. Communicating with senior executives is very different in Tokyo than in New York.

Teaching hard and soft skills also varies. Online education is often effective for hard skills. Many hard skills are rules-based, and we can learn rules remotely. Learning soft skills requires time, coaching, and motivation. Instead of learning rules, we are modeling behaviors.

Because they’re rules-based, hard skills are much more likely to be automated. I used to hire an accountant to do my taxes. Now, I use a software package on my laptop. Most rules-based processes – including computer programming, medical diagnoses, actuarial services, accounting, and stock trading – will likely be automated over the next decade. We won’t need nearly as many people in those professions.

The pace of automation seems to be accelerating as well. I might have worked for 20 to 25 years as a Fortran programmer. Today, I suspect that learning Python will keep you employed for no more than five years or so. Then you’ll be replaced, perhaps by a computer.

For all these reasons, I would like to change the names we use to describe these skills. Instead of hard skills and soft skills, I would call them temporary skills and durable skills. By changing the labels, we will also change our perceptions. Clearly durable skills are more valuable than temporary skills. By describing them more accurately, we can make our investments – in ourselves and others – more wisely. That’s a durable skill.

I’m certainly not the first to propose new labels for hard and soft skills. Click here, here, and here for some of the articles that have shaped my thinking

What if we could make friends more quickly and more predictably? Would we make more friends? Would life be better? Would we be happier? Would we take fewer tranquilizers?

What if we could make friends in nine minutes?

We usually think of making friends as a pleasurable process. We don’t usually think of it as a necessary process. We could, I suppose, survive reasonably well without making friends. But what if you have to make friends? How would you do it?

This is a problem that faces some social science researchers. If you want to study relationships – how they form, how they influence behavior, etc. – you need to be able to create relationships and measure their degree of closeness.

For instance, you might want to study the effect of friendship on, say, pro-social behavior. Do people in friendly relationships do more good works or fewer? You invite pairs of friends to participate. Assume that you want to compare pairs of people who have been friends for less than six months. You could sort through pairs of people to find those who fit your criteria. But it’s complicated and imprecise.

Alternatively, you could recruit strangers, pair them up randomly, and induce friendships among them. What’s the advantage? Constantine Sedikides and his colleagues wrote about this in their paper, “The Relationship Closeness Induction Task.” They note that “Because newly formed laboratory relationships lack a history of … past interactions, … the researcher is able to examine the effect of relationship closeness per se on the dependent measurements….” Random assignment also reduces the impact of pesky intervening variables.

The methodological advantage seems clear. But … how do you induce a friendship? Sedikides et. al. describe several methods that didn’t seem to work very well. They then propose the Relationship Closeness Induction Task (RCIT) which is built on “… the principle that a vital feature in the development of a close relationship is reciprocal and escalating self-disclosure.” In simpler terms, by sharing information about yourself (self-disclosing) with a stranger who also shares information, you develop a closer relationship.

The RCIT consists of three lists of questions – 29 questions total — and participants are asked to spend nine minutes “mutually self-disclosing”. They spend one minute on List 1, three minutes on list II, and five minutes on List III. The authors note that the RCIT has proved its validity in four different ways:

1. Participants reported a higher level of relationship closeness than did control groups, with no gender differences found.
2. RCIT induced closeness created statistically significant impacts on dependent variables in several different studies.
3. Participants reported that they had adequate privacy and felt comfortable with the process.
4. In the allotted nine minutes, participants answered 90% of the questions.

The original questions were written for college students; they’re the most likely participants in these kinds of studies. With just a bit of imagination, however, you could pull out the college-related questions and substitute other, more relevant questions in your friendship induction process.

I suspect by now that you would like to know the 29 questions. Here they are. Now go out and make some friends. You’ve got nine minutes.

List I – One minute

1. What is your name?
2. How old are you?
3. Where are you from?
4. What year are you in at University X?
5. What do you think you might major in? Why?
6. What made you come to the University of X?
7. What’s your favorite class at the University of X? Why?

List II – Three minutes

1. What are your hobbies?
2. What would you like to do after graduation from the University of X?
3. What would be the perfect lifestyle for you?
4. What is something you have always wanted to do but probably never will be able to do?
5. If you could travel anywhere in the world, where would you go and why?
6. What is one strange thing that has happened to you since you have been at the University of X?
7. What is one embarrassing thing that has happened to you since arriving at the University of X?
8. What is one thing happening in your life that makes you stressed out?
9. If you could change anything that happened to you in high school, what would that be?
10. If you could change one thing about yourself what would that be?
11. Do you miss your family?
12. What is one habit you’d like to break?

List III – Five minutes

1. If you could have one wish granted, what would that be?
2. Is it difficult or easy for you to meet people? Why?
3. Describe the last time that you felt lonely.
4. What is one emotional experience you’ve had with a close friend?
5. What is one of your biggest fears?
6. What is your most frightening early memory?
7. What is your happiest early childhood memory?
8. What is one thing about yourself that most people would consider surprising?
9. What is one recent accomplishment that you are proud of?
10. Tell me one thing about yourself that most people who already know you don’t know.

In major corporate decisions, a devil’s advocate can serve an invaluable function. The advocate can help stress test an idea and point out cognitive biases that others might miss. The big idea is put on trial. Executives who proposed the idea serve as defense attorneys. The devil’s advocate is essentially the prosecutor. She looks for weaknesses in the other side’s case and serves up an alternative narrative. She also helps the team protect against the down side. The advocate helps us make the decision right — using a balanced process that tends to dampen major biases.

All too often, however, the process devolves into “decision theater”. We’re just playing roles that don’t improve the decision process but do make us feel better about it. Here’s how I’ve seen it play out in various software companies:

• Only a small number of people play the devil’s advocate (DA) role. They do it voluntarily and they get little or no support in terms of resources or even encouragement. Each time we had a meeting about a big decision, the same people  spoke up to say, “Well … let me be a devil’s advocate here …” I admired these people but I also wondered, Why do so few people step forward in this role? How could the company promote this role as a regular part of the decision process?
• In these meetings, the devil’s advocate’s objections were always “handled”. In other words, the leader of the meeting (often the CEO) would thank the devil’s advocate for the input and then give a breezy statement that effectively dismissed the input.  We all felt better because we had “considered” the other side. But had we really?
• Prior to the meeting, the devil’s advocate had very few resources to develop a coherent position. The DA didn’t have any staff to gather information or budget to hire consultants, etc. The DA’s position might be very thoughtful .. but it wasn’t well developed with evidence to back it up. It could easily be dismissed.
• This is what I call “decision theater.” We believe we’re contributing to a good decision process, but we’re really just acting out roles.

I certainly respect people who play the devil’s advocate role. To make this more than theater however, organizations need to change the process. How? Well, let’s look at the history of the devil’s advocate.

The Catholic church originated the role of the devil’s advocate in 1587. The advocate plays a key role in the process of canonization — determining whether a person should be declared a saint. The process includes a trial, with one side arguing that the person does indeed deserve sainthood. The other side — led by the devil’s advocate — argues the opposite. The devil’s advocate aims to poke holes in the other side’s argument, For instance, the advocate might claim that the miracles attributed to the person were actually frauds.

From my perspective, the most important element was that the church gave the advocate resources and respect to fulfill the role effectively. The devil’s advocate had resources — time, money, staff — to call on. This differs greatly from devil’s advocates in today’s corporate world, who may speak up but are not institutionally supported. A corporation that wants to debias its decision processes should do what the Catholic church did — institutionalize the role and provide enough support to make it serious.

My friends who have kids sometimes ask if the lessons I teach in my Persuasion classes also apply to little tykes. Can we apply classic rules of rhetoric to convince kids to do (or not do) things? Can we apply Cicero’s five canons of rhetoric to five-year-olds? Truth be told, I haven’t studied it in detail. But, as a father, and now grandfather, I do have some thoughts. I might even claim to have good ethos (in the Ciceronian sense). Here are some thoughts:

• Nobody likes to be talked down to — as a speaker or writer, you should never imply that you are smarter than your audience. If you want to degrade an opponent’s ethos, tell the audience that the opponent thinks he’s better than they are. (This technique is known as attributed belittlement). The same concept applies to kids — only it’s more literal. You’re taller than they are. Get down to their level. Speak to them face to face. They don’t like to be talked down to.
• Pathos trumps logos — we know that adults make decisions more based on emotion than on logic. Doubly true for kids. Start by recognizing, and validating, their emotions.
• Concession-and-shift — the best way to disagree is to begin by agreeing. If a kid is throwing a tantrum, start by conceding that she’s right. I call it the “ain’t it awful” maneuver. First you get down to their level and say something like, “I just hate it when my ice cream falls in the sand box and I don’t get to eat it. Ain’t it awful?” You may need to repeat it several times. Pretty soon, they’ll realize that you’re agreeing with them. Then (and only then) you can start talking about next steps.
• Decorum is the art of meeting expectations – what does your kid expect from you? If you don’t fulfill these expectations, you create cognitive dissonance. Your kid’s not sure he can trust what you’re saying. You can talk about anything but, first, you have to act like your kid expects you to act. You can change your kid’s expectations, but it takes time. Don’t try it in the middle of a meltdown.
• Social proof is incredibly important — how do you get a kid to eat broccoli? Not by logic. Not by lying — “You’ll grow up big and strong”. Put him with other kids who like broccoli. When another kid says, “Can I have your broccoli?”, your kid will say, “No, that’s mine!” By the way, as an adult, your value as social proof to a kid is approximately zero.
• Speak to their commonplaces — a commonplace is simply a shared belief. Conservative commonplaces tend to revolve around liberty. Liberal commonplaces tend to revolve around justice. Kids’ commonplaces tend to revolve around … well, you know your kid. What does she believe? Speak to that, not to what you believe. As Will Rogers said, “When you go fishing, you bait the hook with what the fish likes. Not with what you like.”