Tag: Biology

Mozart’s Brain and the Fighter Pilot

Reading Time: 6 minutes

Most of us want to be smarter but have no idea how to go about improving our mental apparatus. We intuitively think that if we raised our IQ a few points that we’d be better off intellectually. This isn’t necessarily the case. I know a lot of people with high IQs that make terribly stupid mistakes. The way around this is by improving not our IQ, but our overall cognition.

Cognition, argues Richard Restak, “refers to the ability of our brain to attend, identify, and act.” You can think of this as a melange of our moods, thoughts, decisions, inclinations and actions.

Included among the components of cognition are alertness, concentration, perceptual speed, learning, memory, problem solving, creativity, and mental endurance.

All of these components have two things in common. First, our efficacy at them depends on how well the brain is functioning relative to its capabilities. Second, this efficacy function can be improved with the right discipline and the right habits.

Restak convincingly argues that we can make our brains work better by “enhancing the components of cognition.” How we go about improving our brain performance, and thus cognition, is the subject of his book Mozart’s Brain and the Fighter Pilot.

Improving Our Cognitive Power

To improve the brain we need to exercise our cognitive powers. Most of us believe that physical exercise helps us feel better and live healthier; yet how many of us exercise our brain? As with our muscles and our bones, “the brain improves the more we challenge it.”

This is possible because the brain retains a high degree of plasticity; it changes in response to experience. If the experiences are rich and varied, the brain will develop a greater number of nerve cell connections. If the experiences are dull and infrequent, the connections will either never form or die off.

If we’re in stimulating and challenging environments, we increase the number of nerve cell connections. Our brain literally gets heavier, as the number of synapses (connections between neurons) increases. The key that many people miss here is “rich and varied.”

Memory is the most important cognitive function. Imagine if you lost your memory permanently: Would you still be you?

“We are,” Restak writes, “what we remember.” And poor memories are not limited to those who suffer from Alzheimer’s disease. While some of us are genetically endowed with superlative memories, the rest of us need not fear.

Aristotle suggested that our mind was a wax tablet in a short book on memory, arguing that the passage of time fades the image unless we take steps to preserve it. He was right in ways he never knew; memory researchers know now that, like a wax tablet, our memory changes every time we access it, due to the plasticity Restak refers to. It can also be molded and improved, at least to a degree.

Long ago, the Greeks hit upon the same idea — mostly starting with Plato — that we don’t have to accept our natural memory. We can take steps to improve it.

Learning and Knowledge Acquisition

When we learn something new, we expand the complexity of our brain. We literally increase our brainpower.

[I]ncrease your memory and you increase your basic intelligence. … An increased memory leads to easier, quicker accessing of information, as well as greater opportunities for linkages and associations. And, basically, you are what you can remember.

Too many of us can’t remember these days, because we’ve outsourced our brain. One of the most common complaints at the neurologist’s office for people over forty is poor memory. Luckily most of these people do not suffer from something neurological, but rather the cumulative effect of disuse — a graceful degradation of their memory.

Those who are not depressed (the commonest cause of subjective complaints of memory impairment) are simply experiencing the cumulative effect of decades of memory disuse. Part of this disuse is cultural. Most businesses and occupations seldom demand that their employees recite facts and figures purely from memory. In addition, in some quarters memory is even held in contempt. ‘He’s just parroting a lot of information he doesn’t really understand’ is a common put-down when people are enviously criticizing someone with a powerful memory. Of course, on some occasions, such criticisms are justified, particularly when brute recall occurs in the absence of understanding or context. But I’m not advocating brute recall. I’m suggesting that, starting now, you aim for a superpowered memory, a memory aimed at quicker, more accurate retrieval of information.

Prior to the printing press, we had to use our memories. Epics such as The Odyssey and The Iliad, were recited word-for-word. Today, however, we live in a different world, and we forget that these things were even possible. Information is everywhere. We need not remember anything thanks to technology. This helps and hinders the development of our memory.

[Y]ou should think of the technology of pens, paper, tape recorders, computers, and electronic diaries as an extension of the brain. Thanks to these aids, we can carry incredible amounts of information around with us. While this increase in readily available information is generally beneficial, there is also a downside. The storage and rapid retrieval of information from a computer also exerts a stunting effect on our brain’s memory capacities. But we can overcome this by working to improve our memory by aiming at the development and maintenance of a superpowered memory. In the process of improving our powers of recall, we will strengthen our brain circuits, starting at the hippocampus and extending to every other part of our brain.

Information is only as valuable as what it connects to. Echoing the latticework of mental models, Restek states:

Everything that we learn is stored in the brain within that vast, interlinking network. And everything within that network is potentially connected to everything else.

From this we can draw a reasonable conclusion: if you stop learning mental capacity declines.

That’s because of the weakening and eventual loss of brain networks. Such brain alterations don’t take place overnight, of course. But over a varying period of time, depending on your previous training and natural abilities, you’ll notice a gradual but steady decrease in your powers if you don’t nourish and enhance these networks.

The Better Network: Your Brain or the Internet

Networking is a fundamental operating principle of the human brain. All knowledge within the brain is based on networking. Thus, any one piece of information can be potentially linked with any other. Indeed, creativity can be thought of as the formation of novel and original linkages.

In his book, Weaving the Web: The Original Design and the Ultimate Destiny of the World Wide Web, Tim Berners-Lee, the creator of the Internet, distills the importance of the brain forming connections.

A piece of information is really defined only by what it’s related to, and how it’s related. There really is little else to meaning. The structure is everything. There are billions of neurons in our brains, but what are neurons? Just cells. The brain has no knowledge until connections are made between neurons. All that we know, all that we are, comes from the way our neurons are connected.

Cognitive researchers now accept that it may not be the size of the human brain which gives it such unique abilities — other animals have large brains as well. Rather its our structure; the way our neurons are structured, arranged, and linked.

The more you learn, the more you can link. The more you can link, the more you increase the brain’s capacity. And the more you increase the capacity of your brain the better able you’ll be to solve problems and make decisions quickly and correctly. This is real brainpower.

Multidisciplinary Learning

Restak argues that a basic insight about knowledge and intelligence is: “The existence of certain patterns, which underlie the diversity of the world around us and include our own thoughts, feelings, and behaviors.”

Intelligence enhancement therefore involves creating as many neuronal linkages as possible. But in order to do this we have to extricate ourselves from the confining and limiting idea that knowledge can be broken down into separate “disciplines” that bear little relation to one another.

This brings the entire range of ideas into play, rather than just silos of knowledge from human-created specialities. Charlie Munger and Richard Feynman would probably agree that such over-specialization can be quite limiting. As the old proverb goes, the frog in the well knows nothing of the ocean.

Charles Cameron, a game theorist, adds to this conversation:

The entire range of ideas can legitimately be brought into play: and this means not only that ideas from different disciplines can be juxtaposed, but also that ideas expressed in ‘languages’ as diverse as music, painting, sculpture, dance, mathematics and philosophy can be juxtaposed, without first being ‘translated’ into a common language.

Mozart’s Brain and the Fighter Pilot goes on to provide 28 suggestions and exercises for enhancing your brain’s performance, a few of which we’ll cover in future posts.

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Immigration, Extinction, and Island Equilibrium

Reading Time: 4 minutes

Equilibrium is an important concept that permeates many disciplines. In chemistry we think about the point where the rate of forward reaction is equal to the rate of backward reaction. In economics we think of the point where supply equals demand. In physics we can see how gravity is balanced by forward velocity to create things like planetary orbits.

No matter which discipline we are examining, the core idea remains the same: Equilibrium is a state where opposing forces are balanced.

In biology, equilibrium is so important that it can mean the difference between life or death; for a species, it can decide whether they will thrive or become extinct.

In The Song of the Dodo, David Quammen dives into how equilibrium affects a species’ ability to survive, and how it impacts our ability to save animals on the brink of extinction.

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Historically, the concept of island equilibrium was studied with a focus on the interplay between evolution (as the additive) and extinction (as the subtractive). It was believed that speciation, the process where one species becomes two or more species, caused any increase in the number of inhabitants on an island. In this view, the insularity of islands created a remoteness that could only be overcome by the long processes of evolution. 

However, Robert MacArthur and E.O. Wilson, the co-authors of the influential Theory of Island Biogeography, realized that habitats would show a tendency towards equilibrium much sooner than could be accounted for by speciation. They argued the ongoing processes that most influenced this balance were immigration and extinction.

The type of extinctions we’re referring to in this case are local extinctions, specific to the island in question. A species can go extinct on a particular island and yet be thriving elsewhere; it depends on local conditions.

As for immigration, it’s just what you’d expect: The movement of species from one place to another. Island immigration describes the many ingenious ways in which plants, animals, and insects travel to islands. For instance, not only will insects hitch rides on birds and debris (man made or natural, think garbage and sticks/uprooted seaweed), animals will do the same if the debris is massive enough.

Seeds, meanwhile, make the trip in the feces of birds, which helps to introduce new plant species to the island, while highly motivated swimmers (escapees of natural disasters/predators/famine) and hitchhikers on human ships (think rats) make it over in their own unusual ways.

We can plot this process of immigration and extinction graphically, in a way you’re probably familiar with. Quammen explains:

picture1

The decrease in immigration rate and the increase in extinction rate are graphed not against elapsed time but against the number of species present on a given island. As an island fills up with species, immigration declines and extinction increases, until they offset each other at an equilibrium level. At that level, the rate of continuing immigration is just canceled by the rate of continuing extinction, and there is no net gain or loss of species. The phenomenon of offsetting increase and decrease – the change of identities on the roster of species – is known as turnover. One species of butterfly arrives, another species of butterfly dies out, and in the aftermath the island has the same number of butterfly species as before. Equilibrium with turnover.

So while the specific species inhabiting the island will change over time, the numbers will tend to roll towards a balanced point where the two curves intersect.

Of course, not all equilibrium graphs will look the like one above. Indeed, MacArthur and Wilson hoped this theory would be used not just to explain equilibriums, but to also help predict potential issues.

When either curve is especially steep – reflecting the fact that immigration decreases especially sharply or extinction increases especially sharply – their crossing point shifts leftward, toward zero. The shift means that, at equilibrium, in this particular set of circumstances, there will be relatively few resident species.

In other words, high extinction and low immigration yield an impoverished ecosystem. To you and me it’s a dot in Cartesian space, but to an island it represents destiny.

There are two key ideas that can help us understand the equilibrium point on a given island.

First, the concept of species-area relationship: We see a larger number of a given species on larger islands and a smaller number of a given species on smaller islands.

Second, the concept of species quantity on remote islands: Immigration is much more difficult the further away an island is from either a mainland or a cluster of other islands, meaning that fewer species will make it there.

In other words, size and remoteness are directly correlated to the fragility of any given species inhabiting an island.

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Equilibrium, immigration, evolution, extinction – these are all ideas that bleed into so many more areas than biogeography. What happens to groups when they are isolated? Jared Diamond had some interesting thoughts on that. What happens to products or businesses which don’t keep up with co-evolution? They go extinct due to the Red Queen Effect. What happens to our mind and body when we feel off balance? Our life is impoverished.

Reading a book like The Song of the Dodo helps us to better understand these key concepts which, in turn, helps us more fundamentally understand the world.

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Batesian Mimicry: Why Copycats Are Successful

Reading Time: 5 minutes

One of our first interview guests for The Knowledge Project was the former NFL executive Michael Lombardi. In our interview, we discussed topics ranging from the nature of leadership to decision making in a football context. Mike is one of the wisest thinkers associated with the game.

We heard Mike on an NFL podcast recently, and in a brief clip you can listen to here, Mike makes a fascinating comment on differentiating between a Mimic and the Real Thing:

“There’s two kinds of snakes you come across. There’s the Texas Coral Snake, and the Mexican Milk Snake, and they both look exactly alike. The Texas Coral Snake is dangerous, it’s venomous, it can kill you in a minute. The Mexican Milk Snake can’t do anything to you; it’s an impostor.”

Mike got the idea from my friend and CEO of Glenair, Peter Kaufman. Following Mike’s lead, we chose to dig in a little further.

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Turns out there are a host of Coral Snake Mimics, all designed to look exactly as fierce as the true bad guys. Besides the Mexican Milk Snake, there is the Scarlet King Snake, the Florida Scarlet Snake, and the California Mountain Kingsnake. (At least.)

For an example, here are the Texas Coral Snake on the left and the Mexican Milk Snake on the right. Pretty damn close!

220px-lampropeltis_triangulum_annulata

According to Wikipedia, the Texas Coral Snake’s venom is a “powerful neurotoxin, causing neuromuscular dysfunction”, and terrifyingly describes its bite as coming from “a pair of hollow, small, fixed fangs in the front of its upper jaw, through which the venom is injected and encouraged via a chewing motion. Due to this method of venom delivery, a coral snake must bite and hold on for a brief time to deliver a significant amount of venom…”

The Milk Snake, on the other hand, is described as a pretty ideal pet: “The Mexican Milk Snake adapts well to captive care, and its smaller size and striking colorations can make it an attractive choice for a pet snake. They are normally docile, and not typically apt to bite or expel musk.”

So, how is it that these two look alike? It’s due to a phenomenon called Batesian Mimicry.

In the 1850s, the naturalist Henry Walter Bates found a certain set of butterflies who were clearly not of the same species but whose wings looked almost the same to the naked eye. After thinking it over, Bates eventually figured out what was going on: While the butterflies which were toxic to potential predators (the “models”) were able to operate freely and relatively unmolested, there had also developed a “mimic” population of butterflies which wasn’t toxic at all, yet still went untouched!

In fact, biologists eventually figured out that the more toxic and dangerous the “model” was and the more frequently they appeared in the local population, the easier it was for its “mimics” to get by! Predators simply wouldn’t take the risk of mixing up the two. If there aren’t as many “models” around or they aren’t that dangerous, the mimics have a harder time.

This is a wonderful model, and in the practical world we live in, a similar phenomenon abounds: Copycats or “pretenders to the throne” are often very effective, very convincing “mimics” of the true champions. They dress the part, they talk the talk, and they know what buttons to push. But in the end, they are merely chauffeurs.

We see a very Batesian effect at work: The more impressive the “model,” the more effective its mimics can be in convincing people they too are impressive, and in all the same ways. But for every Warren Buffett (just one by our count), there has been many “future” Warren Buffett’s. For every Steve Jobs, there have been many “next” Steve Jobs’.

In fact, sometimes even just appearances can be quite convincing: now-disgraced Theranos founder Elizabeth Holmes was very fond of wearing a very Steve Jobsian black turtleneck outfit.

It seems almost a law of nature that success will be copied, sometimes in a very disgraceful way. (Charlie Munger thinks that the fundamental algorithm of life is “Repeat what works.”)

Because they can be very convincing,  we must be wise enough to watch out for Batesian mimicry — even in ourselves.

This brings up an interesting, at times paradoxical, question: Who can best tell the difference between a Coral Snake and its Mimics? The Coral Snake itself.

The real thing knows a fake. Charlie Munger once commented on this in relation to the field of money management:

“It’s very hard to tell the difference between a good money manager and someone who just has the patter down. If you aren’t a good money manager yourself, rather than trying to pick one, you’re probably better off with a low cost index fund. ‘It takes one to know one’.”

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An insight this good is only possible through continued study across the largest and most relevant fields of study. Peter got this idea by studying biology, a field full of incredible insight but, strangely underappreciated by most “non-biologists”. It’s not just ideas about predators and prey, but niches, competition, co-evolutionary arms races and a whole host of others which give us massive insight into the human world.

Peter realized that studying across fields like biology and physics is something like buying an index fund: It works because you captures all the important companies traded on the public exchange, not just a select few. That means you capture the massive winners, which tend to greatly outweigh the failures.

Studying across all of the important fields gives you the same advantage, except it’s even better: If an index fund buys a new position, it must sell something to do so; consequently, the “big winners” can only impact your portfolio in a limited way. But if you come to understand a new Great Idea, you don’t have to give up the ones you already know! This is a great advantage.

And so it’s worth taking the time to work on learning all the big ideas you can find, not just the ones you want to learn. In that search, you’ll find a host of big winners you didn’t even know existed.

If you liked this post, you’ll probably also love:

The Need for Biological Thinking to Solve Complex Problems — How should we think about complexity? Should we use a biological or physics system? The answer, of course, is that it depends. It’s important to have both tools available at your disposal.

The Founder Principle: A Wonderful Idea from Biology — In his brilliant The Song of the Dodo, David Quammen gives us not only the stories of many brilliant biological naturalists including Mayr, but we also get a deep dive into the core concepts of evolution and extinction, including the Founder Effect.

Biology Enables. Culture Forbids. — From a biological perspective, nothing is unnatural. Whatever is possible is by definition also natural.

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The Founder Principle: A Wonderful Idea from Biology

Reading Time: 5 minutes

We’ve all been taught natural selection; the mechanism by which species evolve through differential reproductive success. Most of us are familiar with the idea that random mutations in DNA cause variances in offspring, some of which survive more frequently than others. However, this is only part of the story.

Sometimes other situations cause massive changes in species populations, and they’re often more nuanced and tough to spot.

One such concept comes from one of the most influential biologists in history, Ernst Mayr. He called it The Founder Principle, a mechanism by which new species are created by a splintered population; often with lower genetic diversity and an increased risk of extinction.

In the brilliant The Song of the Dodo: Island Biography in an Age of Extinction, David Quammen gives us not only the stories of many brilliant biological naturalists including Mayr, but we also get a deep dive into the core concepts of evolution and extinction, including the founder principle.

Quammen begins by outlining the basic idea:

When a new population is founded in an isolated place, the founders usually constitute a numerically tiny group – a handful of lonely pioneers, or just a pair, or maybe no more than one pregnant female. Descending from such a small number of founders, the new population will carry only a minuscule and to some extent random sample of the gene pool of the base population. The sample will most likely be unrepresentative, encompassing less genetic diversity than the larger pool. This effect shows itself whenever a small sample is taken from a large aggregation of diversity; whether the aggregation consists of genes, colored gum balls, M&M’s, the cards of a deck, or any other collection of varied items, a small sample will usually contain less diversity than the whole.

Why does the founder principle happen? It’s basically applied probability. Perhaps an example will help illuminate the concept.

Think of yourself playing a game of poker (five card draw) with a friend. The deck of cards is separated into four suits: Diamonds, hearts, clubs and spades, each suit having 13 cards for a total of 52 cards.

Now look at your hand of five cards. Do you have one card from each suit? Maybe. Are all five cards from the same suit? Probably not, but it is possible. Will you get the ace of spades? Maybe, but not likely.

This is a good metaphor for how the founder principle works. The gene pool carried by a small group of founders is unlikely to be precisely representative of the gene pool of the larger group. In some rare cases it will be very unrepresentative, like you getting dealt a straight flush.

It starts to get interesting when this founder population starts to reproduce, and genetic drift causes the new population to diverge significantly from its ancestors. Quammen explains:

Already isolated geographically from its base population, the pioneer population now starts drifting away genetically. Over the course of generations, its gene pool becomes more and more different from the gene pool of the base population – different both as to the array of alleles (that is, the variant forms of a given gene) and as to the commonness of each allele.

The founder population, in some cases, will become so different that it can no longer mate with the original population. This new species may even be a competitor for resources if the two populations are ever reintroduced. (Say, if a land bridge is created between two islands, or humans bring two species back in contact.)

Going back to our card metaphor, let’s pretend that you and your friend are playing with four decks of cards — 208 total cards. Say we randomly pulled out forty cards from those decks. If there are absolutely no kings in the forty cards you are playing with, you will never be able to create a royal flush (ace+king+queen+jack+10 of the same suit). It doesn’t matter how the cards are dealt, you can never make a royal flush with no kings.

Thus it is with species: If a splintered-off population isn’t carrying a specific gene variant (allele), that variant can never be represented in the newly created population, no matter how prolific that gene may have been in the original population. It’s gone. And as the rarest variants disappear, the new population becomes increasingly unlike the old one, especially if the new population is small.

Some alleles are common within a population, some are rare. If the population is large, with thousands or millions of parents producing thousands or millions of offspring, the rare alleles as well as the common ones will usually be passed along. Chance operation at high numbers tends to produce stable results, and the proportions of rarity and commonness will hold steady. If the population is small, though, the rare alleles will most likely disappear […] As it loses its rare alleles by the wayside, a small pioneer population will become increasingly unlike the base population from which it derived.

Some of this genetic loss may be positive (a gene that causes a rare disease may be missing), some may be negative (a gene for a useful attribute may be missing) and some may be neutral.

The neutral ones are the most interesting: A neutral gene at one point in time may become a useful gene at another point. It’s like playing a round of poker where 8’s are suddenly declared “wild,” and that card suddenly becomes much more important than it was the hand before. The same goes for animal traits.

Take a mammal population living on an island, having lost all of its ability to swim. That won’t mean much if all is well and it is never required to swim. But the moment there is a natural disaster such as a fire, having the ability to swim the short distance to the mainland could be the difference between survival or extinction.

That’s why the founder principle is so dangerous: The loss of genetic diversity often means losing valuable survival traits. Quammen explains:

Genetic drift compounds the founder-effect problem, stripping a small population of the genetic variation that it needs to continue evolving. Without that variation, the population stiffens toward uniformity. It becomes less capable of adaptive response. There may be no manifest disadvantages in uniformity so long as environmental circumstances remain stable; but when circumstances are disrupted, the population won’t be capable of evolutionary adjustment. If the disruption is drastic, the population may go extinct.

This loss of adaptability is one of the two major issues caused by the founder principle, the second being inbreeding depression. A founder population may have no choice but to only breed within its population and a symptom of too much inbreeding is the manifestation of harmful genetic variants among inbred individuals. (One reason humans consider incest a dangerous activity.) This too increases the fragility of species and decreases their ability to evolve.

The founder principle is just one of many amazing ideas in The Song of the Dodo. In fact, we at Farnam Street feel the book is so important that it made our list of books we recommend to improve your general knowledge of the world and it was the first book we picked for our learning community reading group.

If you have already read this book and want more we suggest Quammen’s The Reluctant Mr. Darwin or his equally thought provoking Spillover: Animal Infections and the Next Human Pandemic. Another wonderful and readable book on species evolution is The Beak of the Finch, by Jonathan Weiner.

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The Green Lumber Fallacy: The Difference between Talking and Doing

Reading Time: 6 minutes

“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 us. We 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.

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Frozen Accidents: Why the Future Is So Unpredictable

Reading Time: 7 minutes

“Each of us human beings, for example, is the product of an enormously long
sequence of accidents,any of which could have turned out differently.”
— Murray Gell-Mann

***

What parts of reality are the product of an accident? The physicist Murray Gell-Mann thought the answer was “just about everything.” And to Gell-Mann, understanding this idea was the the key to understanding how complex systems work.

Gell-Mann believed two things caused what we see in the world:

  1. A set of fundamental laws
  2. Random “accidents” — the little blips that could have gone either way, and had they, would have produced a very different kind of world.

Gell-Mann pulled the second part from Francis Crick, co-discoverer of the human genetic code, who argued that the code itself may well have been an “accident” of physical history rather than a uniquely necessary arrangement.

These accidents become “frozen” in time, and have a great effect on all subsequent developments; complex life itself is an example of something that did happen a certain way but probably could have happened other ways — we know this from looking at the physics.

This idea of fundamental laws plus accidents and the non-linear second-order effects they produce became the science of complexity and chaos theory.

Gell-Mann discussed the fascinating idea further in a 1996 essay on Edge:

Each of us human beings, for example, is the product of an enormously long sequence of accidents, any of which could have turned out differently. Think of the fluctuations that produced our galaxy, the accidents that led to the formation of the solar system, including the condensation of dust and gas that produced Earth, the accidents that helped to determine the particular way that life began to evolve on Earth, and the accidents that contributed to the evolution of particular species with particular characteristics, including the special features of the human species. Each of us individuals has genes that result from a long sequence of accidental mutations and chance matings, as well as natural selection.

Now, most single accidents make very little difference to the future, but others may have widespread ramifications, many diverse consequences all traceable to one chance event that could have turned out differently. Those we call frozen accidents.

These “frozen accidents” occur at every nested level of the world: As Gell-Mann points out, they are an outcome in physics (the physical laws we observe may be accidents of history); in biology (our genetic code is largely a byproduct of “advantageous accidents” as discussed by Crick); and in human history, as we’ll discuss. In other words, the phenomenon hits all three buckets of knowledge.

Gell-Mann gives a great example of how this plays out on the human scale:

For instance, Henry VIII became king of England because his older brother Arthur died. From the accident of that death flowed all the coins, all the charters, all the other records, all the history books mentioning Henry VIII; all the different events of his reign, including the manner of separation of the Church of England from the Roman Catholic Church; and of course the whole succession of subsequent monarchs of England and of Great Britain, to say nothing of the antics of Charles and Diana. The accumulation of frozen accidents is what gives the world its effective complexity.

The most important idea here is that the frozen accidents of history have a nonlinear effect on everything that comes after. The complexity we see comes from simple rules and many, many “bounces” that could have gone in any direction. Once they go a certain way, there is no return.

This principle is illustrated wonderfully in the book The Origin of Wealth by Eric Beinhocker. The first example comes from 19th century history:

In the late 1800s, “Buffalo Bill” Cody created a show called Buffalo Bill’s Wild West Show, which toured the United States, putting on exhibitions of gun fighting, horsemanship, and other cowboy skills. One of the show’s most popular acts was a woman named Phoebe Moses, nicknamed Annie Oakley. Annie was reputed to have been able to shoot the head off of a running quail by age twelve, and in Buffalo Bill’s show, she put on a demonstration of marksmanship that included shooting flames off candles, and corks out of bottles. For her grand finale, Annie would announce that she would shoot the end off a lit cigarette held in a man’s mouth, and ask for a brave volunteer from the audience. Since no one was ever courageous enough to come forward, Annie hid her husband, Frank, in the audience. He would “volunteer,” and they would complete the trick together. In 1880, when the Wild West Show was touring Europe, a young crown prince (and later, kaiser), Wilhelm, was in the audience. When the grand finale came, much to Annie’s surprise, the macho crown prince stood up and volunteered. The future German kaiser strode into the ring, placed the cigarette in his mouth, and stood ready. Annie, who had been up late the night before in the local beer garden, was unnerved by this unexpected development. She lined the cigarette up in her sights, squeezed…and hit it right on the target.

Many people have speculated that if at that moment, there had been a slight tremor in Annie’s hand, then World War I might never have happened. If World War I had not happened, 8.5 million soldiers and 13 million civilian lives would have been saved. Furthermore, if Annie’s hand had trembled and World War I had not happened, Hitler would not have risen from the ashes of a defeated Germany, and Lenin would not have overthrown a demoralized Russian government. The entire course of twentieth-century history might have been changed by the merest quiver of a hand at a critical moment. Yet, at the time, there was no way anyone could have known the momentous nature of the event.

This isn’t to say that other big events, many bad, would not have precipitated in the 20th century. Almost certainly there would have been wars and upheavals.

But the actual course of history was in some part determined by small chance event which had no seeming importance when it happened. The impact of Wilhelm being alive rather than dead was totally non-linear. (A small non-event had a massively disproportionate effect on what happened later.)

This is why predicting the future, even with immense computing power, is an impossible task. The chaotic effects of randomness, with small inputs having disproportionate and massive effects, makes prediction a very difficult task. That’s why we must appreciate the role of randomness in the world and seek to protect against it.

Another great illustration from The Origin of Wealth is a famous story in the world of technology:

[In 1980] IBM approached a small company with forty employees in Bellevue, Washington. The company, called Microsoft, was run by a Harvard dropout named bill Gates and his friend Paul Allen. IBM wanted to talk to the small company about creating a version of the programming language BASIC for the new PC. At their meeting, IBM asked Gates for his advice on what operating systems (OS) the new machine should run. Gates suggested that IBM talk to Gary Kildall of Digital Research, whose CP/M operating system had become the standard in the hobbyist world of microcomputers. But Kildall was suspicious of the blue suits from IBM and when IBM tried to meet him, he went hot-air ballooning, leaving his wife and lawyer to talk to the bewildered executives, along with instructions not to sign even a confidentiality agreement. The frustrated IBM executives returned to Gates and asked if he would be interested in the OS project. Despite never having written an OS, Gates said yes. He then turned around and license a product appropriately named Quick and Dirty Operating System, or Q-DOS, from a small company called Seattle Computer Products for $50,000, modified it, and then relicensed it to IBM as PC-DOS. As IBM and Microsoft were going through the final language for the agreement, Gates asked for a small change. He wanted to retain the rights to sell his DOS on non-IBM machines in a version called MS-DOS. Gates was giving the company a good price, and IBM was more interested in PC hardware than software sales, so it agreed. The contract was signed on August 12, 1981. The rest, as they say, is history. Today, Microsoft is a company worth $270 billion while IBM is worth $140 billion.

At any point in that story, business history could have gone a much different way: Kildall could have avoided hot-air ballooning, IBM could have refused Gates’ offer, Microsoft could have not gotten the license for QDOS. Yet this little episode resulted in massive wealth for Gates and a long period of trouble for IBM.

Predicting the outcomes of a complex system must clear a pretty major hurdle: The prediction must be robust to non-linear “accidents” with a chain of unforeseen causation. In some situations this is doable: We can confidently rule out that Microsoft will not go broke in the next 12 months; the chain of events needed to take it under quickly is so low as to be negligible, no matter how you compute it. (Even IBM made it through the above scenario, although not unscathed.)

But as history rolls on and more “accidents” accumulate year by year, a “Fog of the Future” rolls in to obscure our view. In order to operate in such a world, we must learn that predicting is inferior to building systems that don’t require prediction, as Mother Nature does. And if we must predict, must confine our predictions to areas with few variables that lie in our circle of competence, and understand the consequences if we’re wrong.

If this topic is interesting to you, try exploring the rest of the Origin of Wealth, which discusses complexity in the economic realm in great (but readable) detail; also check out the rest of Murray Gell-Mann’s essay on Edge. Gell-Mann also wrote a book on the topic called The Quark and the Jaguar which is worth checking out. The best writer on randomness and robustness in the face of an uncertain future is of course Nassim Taleb, whom we have written about many times.

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