Tag: Antifragile

Mental Models For a Pandemic

Mental models help us understand the world better, something which is especially valuable during times of confusion, like a pandemic. Here’s how to apply mental models to gain a more accurate picture of reality and keep a cool head.

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It feels overwhelming when the world changes rapidly, abruptly, and extensively. The changes come so fast it can be hard to keep up—and the future, which a few months ago seemed reliable, now has so many unknown dimensions. In the face of such uncertainty, mental models are valuable tools for helping you think through significant disruptions such as a pandemic.

A mental model is simply a representation of how something works. They are how we simplify complexity, why we consider some things more relevant than others, and how we reason. Using them increases your clarity of understanding, providing direction for the choices you need to make and the options you want to keep open.

Models for ourselves

During a pandemic, a useful model is “the map is not the territory.” In rapidly changing situations like a global health crisis, any reporting is an incomplete snapshot in time. Our maps are going to be inaccurate for many reasons: limited testing availability, poor reporting, ineffective information sharing, lack of expertise in analyzing the available information. The list goes on.

If past reporting hasn’t been completely accurate, then why would you assume current reporting is? You have to be careful when interpreting the information you receive, using it as a marker to scope out a range of what is happening in the territory.

In our current pandemic, we can easily spot our map issues. There aren’t enough tests available in most countries. Because COVID-19 isn’t fatal for the majority of people who contract it, there are likely many people who get it but don’t meet the testing criteria. Therefore, we don’t know how many people have it.

When we look at country-level reporting, we can also see not all countries are reporting to the same standard. Sometimes this isn’t a matter of “better” or “worse”; there are just different ways of collating the numbers. Some countries don’t have the infrastructure for widespread data collection and sharing. Different countries also have different standards for what counts as a death caused by COVID-19.

In other nations, incentives affect reporting. Some countries downplay their infection rate so as to not create panic. Some governments avoid reporting because it undermines their political interests. Others are more worried about the information on the economic map than the health one.

Although it is important to be realistic about our maps, it doesn’t mean we shouldn’t seek to improve their quality. Paying attention to information from experts and ignoring unverified soundbites is one step to increasing the accuracy of our maps. The more accurate we can get them, the more likely it is that we’ll be able to unlock new possibilities that help us deal with the crisis and plan for the future.

There are two models that we can use to improve the effectiveness of the maps we do have: “compounding” and “probabilistic thinking.”

Compounding is exponential growth, something a lot of us tend to have a poor intuitive grasp on. We see the immediate linear relationships in the situation, like how one test diagnoses one person, while not understanding the compounding effects of that relationship. Increased testing can lead to an exponential decrease in virus transmission because each infected person usually passes the virus onto more than just one other person.

One of the clearest stories to illustrate exponential growth is the story of the man who asked to be paid in rice. In this story, a servant is to be rewarded for his service. When asked how he wanted to be paid, he asks to be paid in rice, using a chessboard to determine the final amount. Starting with one grain, the amount of rice is to be doubled for each square. One grain on the first square looks pathetic. But halfway through the chessboard, the servant is making a good yearly living. And after doubling the rice sixty-four times, the servant is owed more rice than the whole world can produce.

Improving our ability to think exponentially helps us understand how more testing can lead to both an exponential decrease in testing prices and an exponential increase in the production of those tests. It also makes clear just how far-reaching the impact of our actions can be if we don’t take precautions with the assumption that we could be infected.

Probabilistic thinking is also invaluable in helping us make decisions based on the incomplete information we have. In the absence of enough testing, for example, we need to use probabilistic thinking to make decisions on what actions to pursue. We ask ourselves questions like: Do I have COVID-19? If there’s a 1% chance I have it, is it worth visiting my grandparents?

Being able to evaluate reasonable probability has huge impacts on how we approach physical distancing. Combining the models of probabilistic thinking and map is not the territory suggests our actions need to be guided by infection numbers much higher than the ones we have. We are likely to make significantly different social decisions if we estimate the probability of infection as being three people out of ten instead of one person out of one thousand.

Bayesian updating can also help clarify the physical distancing actions you should take. There’s a small probability of being part of a horrendous chain of events that might not just have poor direct consequences but also follow you for the rest of your life. Evaluating how responsible you are being in terms of limiting transmission, would you bet a loved one’s life on it?

Which leads us to Hanlon’s Razor. It’s hard not to get angry at reports of beach parties during spring break or at the guy four doors down who has his friends over to hang out every night. For your own sanity, try using Hanlon’s Razor to evaluate their behavior. They are not being malicious and trying to kill people. They are just exceptionally and tragically ignorant.

Finally, on a day-to-day basis, trying to make small decisions with incomplete information, you can use inversion. You can look at the problem backwards. When the best way forward is far from clear, you ask yourself what you could do to make things worse, and then avoid doing those things.

Models for society

Applying mental models aids in the understanding the dynamics of the large-scale social response.

Currently we are seeing the counterintuitive measures with first-order negatives (closing businesses) but second- and third-order positives (reduced transmission, less stress on the healthcare system). Second-order thinking is an invaluable tool at all times, including during a pandemic. It’s so important that we encourage the thinking, analysis, and decision-making that factors in the effects of the effects of the decisions we make.

In order to improve the maps that our leaders have to make decisions, we need to sort through the feedback loops providing the content. If we can improve not only the feedback but also the pace of iterations, we have a better chance of making good decisions.

For example, if we improve the rate of testing and the speed of the results, it would be a major game-changer. Imagine if knowing whether you had the virus or not was a $0.01 test that gave you a result in less than a minute. In that case, we could make different decisions about social openness, even in the absence of a vaccine (however, this may have invasive privacy implications, as tracking this would be quite difficult otherwise).

As we watch the pandemic and its consequences unfold, it becomes clear that leadership and authority are not the same thing. Our hierarchical instincts emerge strongly in times of crisis. Leadership vacuums, then, are devastating, and disasters expose the cracks in our hierarchies. However, we also see that people can display strong leadership without needing any authority. A pandemic provides opportunities for such leadership to emerge at community and local levels, providing alternate pathways for meeting the needs of many.

One critical model we can use to look at society during a pandemic is Ecosystems. When we think about ecosystems, we might imagine a variety of organisms interacting in a forest or the ocean. But our cities are also ecosystems, as is the earth as a whole. Understanding system dynamics can give us a lot of insight into what is happening in our societies, both at the micro and macro level.

One property of ecosystems that is useful to contemplate in situations like a pandemic is resilience—the speed at which an ecosystem recovers after a disturbance. There are many factors that contribute to resilience, such as diversity and adaptability. Looking at our global situation, one factor threatening to undermine our collective resilience is that our economy has rewarded razor-thin efficiency in the recent past. The problem with thin margins is they offer no buffer in the face of disruption. Therefore, ecosystems with thin margins are not at all resilient. Small disturbances can bring them down completely. And a pandemic is not a small disturbance.

Some argue that what we are facing now is a Black Swan: an unpredictable event beyond normal expectations with severe consequences. Most businesses are not ready to face one. You could argue that an economic recession is not a black swan, but the particular shape of this pandemic is testing the resiliency of our social and economic ecosystems regardless. The closing of shops and business, causing huge disruption, has exposed fragile supply chains. We just don’t see these types of events often enough, even if we know they’re theoretically possible. So we don’t prepare for them. We don’t or can’t create big enough personal and social margins of safety. Individuals and businesses don’t have enough money in the bank. We don’t have enough medical facilities and supplies. Instead, we have optimized for a narrow range of possibilities, compromising the resilience of systems we rely on.

Finally, as we look at the role national borders are playing during this pandemic, we can use the Thermodynamics model to gain insight into how to manage flows of people during and after restrictions. Insulation requires a lot of work, as we are seeing with our borders and the subsequent effect on our economies. It’s unsustainable for long periods of time. Just like how two objects of different temperatures that come into contact with each other eventually reach thermal equilibrium, people will mix with each other. All borders have openings of some sort. It’s important to extend planning to incorporate the realistic tendencies of reintegration.

Some final thoughts about the future

As we look for opportunities about how to move forward both as individuals and societies, Cooperation provides a useful lens. Possibly more critical to evolution than competition, cooperation is a powerful force. It’s rampant throughout the biological world; even bacteria cooperate. As a species, we have been cooperating with each other for a long time. All of us have given up some independence for access to resources provided by others.

Pandemics are intensified because of connection. But we can use that same connectivity to mitigate some negative effects by leveraging our community networks to create cooperative interactions that fill gaps in the government response. We can also use the cooperation lens to create more resilient connections in the future.

Finally, we need to ask ourselves how we can improve our antifragility. How can we get to a place where we grow stronger through change and challenge? It’s not about getting “back to normal.” The normal that was our world in 2019 has proven to be fragile. We shouldn’t want to get back to a time when we were unprepared and vulnerable.

Existential threats are a reality of life on earth. One of the best lessons we can learn is to open our eyes and integrate planning for massive change into how we approach our lives. This will not be the last pandemic, no matter how careful we are. The goal now should not be about assigning blame or succumbing to hindsight bias to try to implement rules designed to prevent a similar situation in the future. We will be better off if we make changes aimed at increasing our resilience and embracing the benefits of challenge.

Still curious? Learn more by reading The Great Mental Models.

Standing on the Shoulders of Giants

Innovation doesn’t occur in a vacuum. Doers and thinkers from Shakespeare to Jobs, liberally “stole” inspiration from the doers and thinkers who came before. Here’s how to do it right.

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“If I have seen further,” Isaac Newton wrote in a 1675 letter to fellow scientist Robert Hooke, “it is by standing on the shoulders of giants.”

It can be easy to look at great geniuses like Newton and imagine that their ideas and work came solely out of their minds, that they spun it from their own thoughts—that they were true originals. But that is rarely the case.

Innovative ideas have to come from somewhere. No matter how unique or unprecedented a work seems, dig a little deeper and you will always find that the creator stood on someone else’s shoulders. They mastered the best of what other people had already figured out, then made that expertise their own. With each iteration, they could see a little further, and they were content in the knowledge that future generations would, in turn, stand on their shoulders.

Standing on the shoulders of giants is a necessary part of creativity, innovation, and development. It doesn’t make what you do less valuable. Embrace it.

Everyone gets a lift up

Ironically, Newton’s turn of phrase wasn’t even entirely his own. The phrase can be traced back to the twelfth century, when the author John of Salisbury wrote that philosopher Bernard of Chartres compared people to dwarves perched on the shoulders of giants and said that “we see more and farther than our predecessors, not because we have keener vision or greater height, but because we are lifted up and borne aloft on their gigantic stature.”

Mary Shelley put it this way in the nineteenth century, in a preface for Frankenstein: “Invention, it must be humbly admitted, does not consist in creating out of void but out of chaos.”

There are giants in every field. Don’t be intimidated by them. They offer an exciting perspective. As the film director Jim Jarmusch advised, “Nothing is original. Steal from anywhere that resonates with inspiration or fuels your imagination. Devour old films, new films, music, books, paintings, photographs, poems, dreams, random conversations, architecture, bridges, street signs, trees, clouds, bodies of water, light, and shadows. Select only things to steal from that speak directly to your soul. If you do this, your work (and theft) will be authentic. Authenticity is invaluable; originality is non-existent. And don’t bother concealing your thievery—celebrate it if you feel like it. In any case, always remember what Jean-Luc Godard said: ‘It’s not where you take things from—it’s where you take them to.’”

That might sound demoralizing. Some might think, “My song, my book, my blog post, my startup, my app, my creation—surely they are original? Surely no one has done this before!” But that’s likely not the case. It’s also not a bad thing. Filmmaker Kirby Ferguson states in his TED Talk: “Admitting this to ourselves is not an embrace of mediocrity and derivativeness—it’s a liberation from our misconceptions, and it’s an incentive to not expect so much from ourselves and to simply begin.”

There lies the important fact. Standing on the shoulders of giants enables us to see further, not merely as far as before. When we build upon prior work, we often improve upon it and take humanity in new directions. However original your work seems to be, the influences are there—they might just be uncredited or not obvious. As we know from social proof, copying is a natural human tendency. It’s how we learn and figure out how to behave.

In Antifragile: Things That Gain from Disorder, Nassim Taleb describes the type of antifragile inventions and ideas that have lasted throughout history. He describes himself heading to a restaurant (the likes of which have been around for at least 2,500 years), in shoes similar to those worn at least 5,300 years ago, to use silverware designed by the Mesopotamians. During the evening, he drinks wine based on a 6,000-year-old recipe, from glasses invented 2,900 years ago, followed by cheese unchanged through the centuries. The dinner is prepared with one of our oldest tools, fire, and using utensils much like those the Romans developed.

Much about our societies and cultures has undeniably changed and continues to change at an ever-faster rate. But we continue to stand on the shoulders of those who came before in our everyday life, using their inventions and ideas, and sometimes building upon them.

Not invented here syndrome

When we discredit what came before or try to reinvent the wheel or refuse to learn from history, we hold ourselves back. After all, many of the best ideas are the oldest. “Not Invented Here Syndrome” is a term for situations when we avoid using ideas, products, or data created by someone else, preferring instead to develop our own (even if it is more expensive, time-consuming, and of lower quality.)

The syndrome can also manifest as reluctance to outsource or delegate work. People might think their output is intrinsically better if they do it themselves, becoming overconfident in their own abilities. After all, who likes getting told what to do, even by someone who knows better? Who wouldn’t want to be known as the genius who (re)invented the wheel?

Developing a new solution for a problem is more exciting than using someone else’s ideas. But new solutions, in turn, create new problems. Some people joke that, for example, the largest Silicon Valley companies are in fact just impromptu incubators for people who will eventually set up their own business, firm in the belief that what they create themselves will be better.

The syndrome is also a case of the sunk cost fallacy. If a company has spent a lot of time and money getting a square wheel to work, they may be resistant to buying the round ones that someone else comes out with. The opportunity costs can be tremendous. Not Invented Here Syndrome detracts from an organization or individual’s core competency, and results in wasting time and talent on what are ultimately distractions. Better to use someone else’s idea and be a giant for someone else.

Why Steve Jobs stole his ideas

“Creativity is just connecting things. When you ask creative people how they did something, they feel a little guilty because they didn’t really do it. They just saw something. It seemed obvious to them after a while; that’s because they were able to connect experiences they’ve had and synthesize new things.” 

— Steve Jobs

In The Runaway Species: How Human Creativity Remakes the World, Anthony Brandt and David Eagleman trace the path that led to the creation of the iPhone and track down the giants upon whose shoulders Steve Jobs perched. We often hail Jobs as a revolutionary figure who changed how we use technology. Few who were around in 2007 could have failed to notice the buzz created by the release of the iPhone. It seemed so new, a total departure from anything that had come before. The truth is a little messier.

The first touchscreen came about almost half a century before the iPhone, developed by E.A. Johnson for air traffic control. Other engineers built upon his work and developed usable models, filing a patent in 1975. Around the same time, the University of Illinois was developing touchscreen terminals for students. Prior to touchscreens, light pens used similar technology. The first commercial touchscreen computer came out in 1983, soon followed by graphics boards, tablets, watches, and video game consoles. Casio released a touchscreen pocket computer in 1987 (remember, this is still a full twenty years before the iPhone.)

However, early touchscreen devices were frustrating to use, with very limited functionality, often short battery lives, and minimal use cases for the average person. As touchscreen devices developed in complexity and usability, they laid down the groundwork for the iPhone.

Likewise, the iPod built upon the work of Kane Kramer, who took inspiration from the Sony Walkman. Kramer designed a small portable music player in the 1970s. The IXI, as he called it, looked similar to the iPod but arrived too early for a market to exist, and Kramer lacked the marketing skills to create one. When pitching to investors, Kramer described the potential for immediate delivery, digital inventory, taped live performances, back catalog availability, and the promotion of new artists and microtransactions. Sound familiar?

Steve Jobs stood on the shoulders of the many unseen engineers, students, and scientists who worked for decades to build the technology he drew upon. Although Apple has a long history of merciless lawsuits against those they consider to have stolen their ideas, many were not truly their own in the first place. Brandt and Eagleman conclude that “human creativity does not emerge from a vacuum. We draw on our experience and the raw materials around us to refashion the world. Knowing where we’ve been, and where we are, points the way to the next big industries.”

How Shakespeare got his ideas

Nothing will come of nothing.”  

— William Shakespeare, King Lear

Most, if not all, of Shakespeare’s plays draw heavily upon prior works—so much so that some question whether he would have survived today’s copyright laws.

Hamlet took inspiration from Gesta Danorum, a twelfth-century work on Danish history by Saxo Grammaticus, consisting of sixteen Latin books. Although it is doubtful whether Shakespeare had access to the original text, scholars find the parallels undeniable and believe he may have read another play based on it, from which he drew inspiration. In particular, the accounts of the plight of Prince Amleth (which has the same letters as Hamlet) involves similar events.

Holinshed’s Chronicles, a co-authored account of British history from the late sixteenth century, tells stories that mimic the plot of Macbeth, including the three witches. Holinshed’s Chronicles itself was a mélange of earlier texts, which transferred their biases and fabrications to Shakespeare. It also likely inspired King Lear.

Parts of Antony and Cleopatra are copied verbatim from Plutarch’s Life of Mark Anthony. Arthur Brooke’s 1562 poem The Tragicall Historye of Romeus and Juliet was an undisguised template for Romeo and Juliet. Once again, there are more giants behind the scenes—Brooke copied a 1559 poem by Pierre Boaistuau, who in turn drew from a 1554 story by Matteo Bandello, who in turn drew inspiration from a 1530 work by Luigi da Porto. The list continues, with Plutarch, Chaucer, and the Bible acting as inspirations for many major literary, theatrical, and cultural works.

Yet what Shakespeare did with the works he sometimes copied, sometimes learned from, is remarkable. Take a look at any of the original texts and, despite the mimicry, you will find that they cannot compare to his plays. Many of the originals were dry, unengaging, and lacking any sort of poetic language. J.J. Munro wrote in 1908 that The Tragicall Historye of Romeus and Juliet “meanders on like a listless stream in a strange and impossible land; Shakespeare’s sweeps on like a broad and rushing river, singing and foaming, flashing in sunlight and darkening in cloud, carrying all things irresistibly to where it plunges over the precipice into a waste of waters below.”

Despite bordering on plagiarism at times, he overhauled the stories with an exceptional use of the English language, bringing drama and emotion to dreary chronicles or poems. He had a keen sense for the changes required to restructure plots, creating suspense and intensity in their stories. Shakespeare saw far further than those who wrote before him, and with their help, he ushered in a new era of the English language.

Of course, it’s not just Newton, Jobs, and Shakespeare who found a (sometimes willing, sometimes not) shoulder to stand upon. Facebook is presumed to have built upon Friendster. Cormac McCarthy’s books often replicate older history texts, with one character coming straight from Samuel Chamberlain’s My Confessions. John Lennon borrowed from diverse musicians, once writing in a letter to the New York Times that though the Beatles copied black musicians, “it wasn’t a rip off. It was a love in.”

In The Ecstasy of Influence, Jonathan Lethem points to many other instances of influences in classic works. In 1916, journalist Heinz von Lichberg published a story of a man who falls in love with his landlady’s daughter and begins a love affair, culminating in her death and his lasting loneliness. The title? Lolita. It’s hard to question that Nabokov must have read it, but aside from the plot and name, the style of language in his version is absent from the original.

The list continues. The point is not to be flippant about plagiarism but to cultivate sensitivity to the elements of value in a previous work, as well as the ability to build upon those elements. If we restrict the flow of ideas, everyone loses out.

The adjacent possible

What’s this about? Why can’t people come up with their own ideas? Why do so many people come up with a brilliant idea but never profit from it? The answer lies in what scientist Stuart Kauffman calls “the adjacent possible.” Quite simply, each new innovation or idea opens up the possibility of additional innovations and ideas. At any time, there are limits to what is possible, yet those limits are constantly expanding.

In Where Good Ideas Come From: The Natural History of Innovation, Steven Johnson compares this process to being in a house where opening a door creates new rooms. Each time we open the door to a new room, new doors appear and the house grows. Johnson compares it to the formation of life, beginning with basic fatty acids. The first fatty acids to form were not capable of turning into living creatures. When they self-organized into spheres, the groundwork formed for cell membranes, and a new door opened to genetic codes, chloroplasts, and mitochondria. When dinosaurs evolved a new bone that meant they had more manual dexterity, they opened a new door to flight. When our distant ancestors evolved opposable thumbs, dozens of new doors opened to the use of tools, writing, and warfare. According to Johnson, the history of innovation has been about exploring new wings of the adjacent possible and expanding what we are capable of.

A new idea—like those of Newton, Jobs, and Shakespeare—is only possible because a previous giant opened a new door and made their work possible. They in turn opened new doors and expanded the realm of possibility. Technology, art, and other advances are only possible if someone else has laid the groundwork; nothing comes from nothing. Shakespeare could write his plays because other people had developed the structures and language that formed his tools. Newton could advance science because of the preliminary discoveries that others had made. Jobs built Apple out of the debris of many prior devices and technological advances.

The questions we all have to ask ourselves are these: What new doors can I open, based on the work of the giants that came before me? What opportunities can I spot that they couldn’t? Where can I take the adjacent possible? If you think all the good ideas have already been found, you are very wrong. Other people’s good ideas open new possibilities, rather than restricting them.

As time passes, the giants just keep getting taller and more willing to let us hop onto their shoulders. Their expertise is out there in books and blog posts, open-source software and TED talks, podcast interviews, and academic papers. Whatever we are trying to do, we have the option to find a suitable giant and see what can be learned from them. In the process, knowledge compounds, and everyone gets to see further as we open new doors to the adjacent possible.

The Green Lumber Fallacy: The Difference between Talking and Doing

“Clearly, it is unrigorous to equate skills at doing with skills at talking..”

— Nassim Taleb

“All that glitters is not gold,” the saying goes. We’re often fooled by aesthetics of things into thinking they are the thing. The gist of the Green Lumber Fallacy is this: What works in the real world is not necessarily match our stories of why it works. Unimportant details can often seduce us into thinking we know the reasons for something when we really don’t. Only time filters reality from narrative.

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Before we get to the meat, let’s review an elementary idea in biology that will be relevant to our discussion.

If you’re familiar with evolutionary theory, you know that populations of organisms are constantly subjected to “selection pressures” — the rigors of their environment which lead to certain traits being favored and passed down to their offspring and others being thrown into the evolutionary dustbin.

Biologists dub these advantages in reproduction “fitness” — as in, the famously lengthening of giraffe necks gave them greater “fitness” in their environment because it helped them reach high up, untouched leaves.

Fitness is generally a relative concept: Since organisms must compete for scarce resources, their fitnesses is measured in the sense of giving a reproductive advantage over one another.

Just as well, a trait that might provide great fitness in one environment may be useless or even disadvantageous in another. (Imagine draining a pond: Any fitness advantages held by a really incredible fish becomes instantly worthless without water.) Traits also relate to circumstance. An advantage at one time could be a disadvantage at another and vice versa.

This makes fitness an all-important concept in biology: Traits are selected for if they provide fitness to the organism within a given environment.

Got it? OK, let’s get back to the practical world.

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The Black Swan thinker Nassim Taleb has an interesting take on fitness and selection in the real world:  People who are good “doers” and people who are good “talkers” are often selected for different traits. Be careful not to mix them up.

In his book Antifragile, Taleb uses this idea to invoke a heuristic he’d once used when hiring traders on Wall Street:

The more interesting their conversation, the more cultured they are, the more they will be trapped into thinking that they are effective at what they are doing in real business (something psychologists call the halo effect, the mistake of thinking that skills in, say, skiing translate unfailingly into skills in managing a pottery workshop or a bank department, or that a good chess player would be a good strategist in real life).

Clearly, it is unrigorous to equate skills at doing with skills at talking. My experience of good practitioners is that they can be totally incomprehensible–they do not have to put much energy into turning their insights and internal coherence into elegant style and narratives. Entrepreneurs are selected to be doers, not thinkers, and doers do, they don’t talk, and it would be unfair, wrong, and downright insulting to measure them in the talk department.

In other words, the selection pressures for an entrepreneur are very different from those on a corporate manager or bureaucrat: Entrepreneurs and risk-takers succeed or fail not so much on their ability to talk, explain, and rationalize as their ability to get things done.

While the two can often go together, Nassim figured out that they frequently don’t. We judge people as ignorant when it’s really us who are ignorant.

When you think about it, there’s no a priori reason great intellectualizing and great doing must go together: Being able to hack together an incredible piece of code gives you great fitness in the world of software development while doing great theoretical computer science probably gives you better fitness in academia. The two skills don’t have to be connected. Great economists don’t usually make great investors.

But we often confuse the two realms.  We’re tempted to think that a great investor must be fluent in behavioral economics or a great CEO fluent in Mckinsey-esque management narratives, but in the real world, we see this intuition constantly in violation.

The investor Walter Schloss worked from 9-5, barely left his office, and wasn’t considered an entirely high IQ man, but he compiled one of the great investment records of all time. A young Mark Zuckerberg could hardly be described as a prototypical manager or businessperson, yet somehow built one of the most profitable companies in the world by finding others that complemented his weaknesses.

There are a thousand examples: Our narratives about the type of knowledge or experience we must have or the type of people we must be in order to become successful are often quite wrong; in fact, they border on naive. We think people who talk well can do well, and vice versa. This is simply not always so.

We won’t claim that great doers cannot be great talkers, rationalizers, or intellectuals. Sometimes they are. But if you’re seeking to understand the world properly, it’s good to understand that the two traits are not always co-located. Success, especially in some “narrow” area like plumbing, programming, trading, or marketing, is often achieved by rather non-intellectual folks. Their evolutionary fitness doesn’t come from the ability to talk but do. This is part of reality.

The Green Lumber Fallacy

Taleb calls this idea the Green Lumber Fallacy, after a story in the book What I Learned Losing a Million Dollars.

Taleb describes it in Antifragile:

In one of the rare noncharlatanic books in finance, descriptively called What I Learned Losing a Million Dollars, the protagonist makes a big discovery. He remarks that a fellow named Joe Siegel, one of the most successful traders in a commodity called “green lumber,” actually thought it was lumber painted green (rather than freshly cut lumber, called green because it had not been dried). And he made it his profession to trade the stuff! Meanwhile the narrator was into grand intellectual theories and narratives of what caused the price of commodities to move and went bust.

It is not just that the successful expert on lumber was ignorant of central matters like the designation “green.” He also knew things about lumber that nonexperts think are unimportant. People we call ignorant might not be ignorant.

The fact that predicting the order flow in lumber and the usual narrative had little to do with the details one would assume from the outside are important. People who do things in the field are not subjected to a set exam; they are selected in the most non-narrative manager — nice arguments don’t make much difference. Evolution does not rely on narratives, humans do. Evolution does not need a word for the color blue.

So let us call the green lumber fallacy the situation in which one mistakes a source of visible knowledge — the greenness of lumber — for another, less visible from the outside, less tractable, less narratable.

The main takeaway is that the real causative factors of success are often hidden from usWe think that knowing the intricacies of green lumber are more important than keeping a close eye on the order flow. We seduce ourselves into overestimating the impact of our intellectualism and then wonder why “idiots” are getting ahead.

But for “skin in the game” operations, selection and evolution don’t care about great talk and ideas unless they translate into results. They care what you do with the thing more than that you know the thing. They care about actually avoiding risk rather than your extensive knowledge of risk management theories. (Of course, in many areas of modernity there is no skin in the game, so talking and rationalizing can be and frequently are selected for.)

As Taleb did with his hiring heuristic, this should teach us to be a little skeptical of taking good talkers at face value, and to be a little skeptical when we see “unexplainable” success in someone we consider “not as smart.” There might be a disconnect we’re not seeing because we’re seduced by a narrative. (A problem someone like Lee Kuan Yew avoided by focusing exclusively on what worked.)

And we don’t have to give up our intellectual pursuits in order to appreciate this nugget of wisdom; Taleb is right, but it’s also true that combining the rigorous, skeptical knowledge of “what actually works” with an ever-improving theory structure of the world might be the best combination of all — selected for in many more environments than simple git-er-done ability, which can be extremely domain and environment dependent. (The green lumber guy might not have been much good outside the trading room.)

After all, Taleb himself was both a successful trader and the highest level of intellectual. Even he can’t resist a little theorizing.

Intervention Bias: When to Step in and When To Leave Things Alone

When we want to improve a situation, our first instinct is often to change something. Try something new. Make adjustments. Anything other than what we’re already doing.

But this approach is frequently misguided. Sometimes doing nothing at all or removing inputs is the better approach.

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Nassim Taleb, author of many books—The Black SwanFooled By Randomness, and The Bed of Procrustes— also wrote a book on fragility called Antifragile (antifragile defined).

One of the core ideas of Antifragile is around our tendency to intervene in situations regardless of whether that benefit is a net positive. There is a term for this, iatrogenics. Why do we do this? I can think of three good reasons: 1) we struggle to think in systems, 2) we believe that systems would benefit from our intervention and guidance, and 3) we believe that we know how to fix things to make them better.

The first reason is that we are unable to think in terms of second, third, and nth order consequences. More importantly, we are unaware that we need to. The second reason is that we see systems operating and see a flaw in the system that we could do better. Usually, it’s minor. This combines with the third reason, which is we think we are the very person that needs to fix the system.

Here’s Taleb expanding on this idea:

There is a mental defect psychologists call illusion of control that lead to a default to action rather than inaction, even when the benefits of inaction might be greater than those of action. So the intervention bias” (do something seems better than doing nothing, which is fine except that there are cases in which it gets us in trouble). The illusion of control was meant to show how “irrational” (according to some norm of behavior) we humans can be by giving ourselves the illusion to manage the uncontrollable around us: for instance gamblers cannot resist the pressure to do something in order to improve the outcome, such as throw the die with violence when they need a high number, or throw it softly in order to get a low one. Traders cannot resist wearing the same “lucky” shirt (often unwashed) to improve their day and feel they need to find similar way to take control of their destiny. This mental bias leads to all manner of patently “irrational” actions such as belief in paranormal, alternative medicine and many such actions often put under the umbrella magical thinking. Now the irony is that while this bias was devised to expose patently nonscientific fields, it largely affects many things you learn in college, particularly in social science. Many matters we deem scientific are just the fruit of that very illusion of control masquerading as science with, of course, actions to “improve” mankind.

Why is the scientific illusion of control worse than that of the pedestrian version? Because, tout simplement, these gamblers superstitions are benign, not much worse than doing nothing —they may be even beneficial in hidden ways, and in the right environment. But a doctor tinkering with your system or an army playing with a complex system with opaque causal links, say by invading Iraq, giving chemicals to kids and threatening their brain balance, or intervening in the environment, is far worse than nothing.

This variant of the illusion of control leads to the denigration of acts of omission (not doing something, letting things run their own course, leaving nature or the human body alone) as compared to doing something (such as operating on a patient or prescribing medication). This, we will see is the reason medicine used, until recent history, to kill more patients than it saved (and did not even get close to realizing it), and economists of the sophisticated equation-carrying variety, I will hope to convince you, have been particularly harmful to the economic health of societies —central bankers , and finance ministers, by tinkering with economic life, have caused massive instability.

Taleb posted an interesting table regarding intervention bias.


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