Category: Science

The Stormtrooper Problem: Why Thought Diversity Makes Us Better

Reading Time: 6 minutes

Diversity of thought makes us stronger, not weaker. Without diversity we die off as a species. We can no longer adapt to changes in the environment. We need each other to survive.

***

Diversity is how we survive as a species. This is a quantifiable fact easily observed in the biological world. From niches to natural selection, diversity is the common theme of success for both the individual and the group.

Take the central idea of natural selection: The genes, individuals, groups, and species with the most advantageous traits in a given environment survive and reproduce in greater numbers. Eventually, those advantageous traits spread. The overall population becomes more suited to that environment. This occurs at multiple levels from single genes to entire ecosystems.

That said, natural selection cannot operate without a diverse set of traits to select from! Without variation, selection cannot improve the lot of the higher-level group.

Thought Diversity

This is why I find it frustrating that we often seem to struggle with diversity of thought. This type of diversity shouldn’t threaten us. It should energize us. It means we have a wider variety of resources to deal with the inevitable challenges we face as a species.

Imagine that a meteor is on its way to earth. A crash would be the end of everyone. No matter how self-involved we are, no one wants to see humanity wiped out. So what do we do? Wouldn’t you hope that we could call on more than three people to help find a solution?

Ideally there would be thousands of people with different skills and backgrounds tackling this meteor problem, many minds and lots of options for changing the rock’s course and saving life as we know it. The diversity of backgrounds—variations in skills, knowledge, ways of looking at and understanding the problem—might be what saves the day. But why wait for the threat? A smart species would recognize that if diversity of knowledge and skills would be useful for dealing with a meteor, then diversity would be probably useful in a whole set of other situations.

For example, very few businesses can get by with one knowledge set that will take their product from concept to the homes of customers. You would never imagine that a business could be staffed with clones and be successful. It would be the ultimate in social proof. Everyone would literally be saying the same thing.

The Stormtrooper Problem

Intelligence agencies face a unique set of problems that require creative, un-googleable solutions to one-off problems.

You’d naturally think they would value and seek out diversity in order to solve those problems. And you’d be wrong. Increasingly it’s harder and harder to get a security clearance.

Do you have a lot of debt? That might make you susceptible to blackmail. Divorced? You might be an emotional wreck, which could mean you’ll make emotional decisions and not rational ones. Do something as a youth that you don’t want anyone to know? That makes it harder to trust you. Gay but haven’t told anyone? Blackmail risk. Independently wealthy? That means you don’t need our paycheck, which means you might be harder to work with. Do you have a nuanced opinion of politics? What about Edward Snowden? Yikes. The list goes on.

As the process gets harder and harder (trying to reduce risk), there is less and less diversity in the door. The people that make it through the door are Stormtroopers.

And if you’re one of the lucky Stormtrooopers to make it in, you’re given a checklist career development path. If you want a promotion, you know the exact experience and training you need to receive one. It’s simple. It doesn’t require much thought on your part.

The combination of these two things means that employees increasingly look at—and attempt to solve—problems the same way. The workforce is less effective than it used to be. This means you have to hire more people to do the same thing or outsource more work to people that hire misfits. This is the Stormtrooper problem.

Creativity and Innovation

Diversity is necessary in the workplace to generate creativity and innovation. It’s also necessary to get the job done. Teams with members from different backgrounds can attack problems from all angles and identify more possible solutions than teams whose members think alike. Companies also need diverse skills and knowledge to keep a company functioning. Finance superstars may not be the same people who will rock marketing. And the faster things change, the more valuable diversity becomes for allowing us to adapt and seize opportunity.

We all know that any one person doesn’t have it all figured out and cannot possibly do it all. We can all recognize that we rely on thousands of other people every day just to live. We interact with the world through the products we use, the entertainment we consume, the services we provide. So why do differences often unsettle us?

Any difference can raise this reaction: gender, race, ethnic background, sexual orientation. Often, we hang out with others like us because, let’s face it, communicating is easier with people who are having a similar life experience. And most of us like to feel that we belong. But a sense of belonging should not come at the cost of diversity.

Where Birds Got Feathers

Consider this: Birds did not get their feathers for flying. They originally developed them for warmth, or for being more attractive to potential mates. It was only after feathers started appearing that birds eventually began to fly. Feathers are considered an exaptation, something that evolved for one purpose but then became beneficial for other reasons. When the environment changes, which it inevitably does, a species has a significantly increased chance of survival if it has a diversity of traits that it can re-purpose. What can we re-purpose if everyone looks, acts, and thinks the same?

Further, a genetically homogeneous population is easy to wipe out. It baffles me that anyone thinks they are a good idea. Consider the Irish Potato Famine. In the mid-19th century a potato disease made its way around much of the world. Although it devastated potato crops everywhere, only in Ireland did it result in widespread devastation and death. About one quarter of Ireland’s population died or emigrated to avoid starvation over just a few years. Why did this potato disease have such significant consequences there and not anywhere else?

The short answer is a lack of diversity. The potato was the staple crop for Ireland’s poor. Tenant farms were so small that only potatoes could be grown in sufficient quantity to—barely—feed a family. Too many people depended on this one crop to meet their nutritional needs. In addition, the Irish primarily grew one type of potato, so most of the crops were vulnerable to the same disease. Once the blight hit, it easily infected potato fields all over Ireland, because they were all the same.

You can’t adapt if you have nothing to adapt. If we are all the same, if we’ve wiped out every difference because we find it less challenging, then we increase our vulnerability to complete extinction. Are we too much alike to survive unforeseen challenges?

Even the reproductive process is, at its core, about diversity. You get half your genes from your mother and half from your father. These can be combined in so many different ways that 21 siblings are all going to be genetically unique.

Why is this important? Without this diversity we never would have made it this far. It’s this newness, each time life is started, that has given us options in the form of mutations. They’re like unexpected scientific breakthroughs. Some of these drove our species to awesome new capabilities. The ones that resulted in less fitness? These weren’t likely to survive. Success in life, survival on the large scale, has a lot to do with the potential benefits created by the diversity inherent in the reproductive process.

Diversity is what makes us stronger, not weaker. Biologically, without diversity we die off as a species. We can no longer adapt to changes in the environment. This is true of social diversity as well. Without diversity, we have no resources to face the inevitable challenges, no potential for beneficial mutations or breakthroughs that may save us. Yet we continue to have such a hard time with that. We’re still trying to figure out how to live with each other. We’re nowhere near ready for that meteor.

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Alexander von Humboldt and the Invention of Nature: Creating a Holistic View of the World Through A Web of Interdisciplinary Knowledge

Reading Time: 5 minutes

In his piece in 2014’s Edge collection This Idea Must Die: Scientific Theories That Are Blocking Progress, dinosaur paleontologist Scott Sampson writes that science needs to “subjectify” nature. By “subjectify”, he essentially means to see ourselves connected with nature, and therefore care about it the same way we do the people with whom we are connected.

That’s not the current approach. He argues: “One of the most prevalent ideas in science is that nature consists of objects. Of course, the very practice of science is grounded in objectivity. We objectify nature so that we can measure it, test it, and study it, with the ultimate goal of unraveling its secrets. Doing so typically requires reducing natural phenomena to their component parts.”

But this approach is ultimately failing us.

Why? Because much of our unsustainable behavior can be traced to a broken relationship with nature, a perspective that treats the nonhuman world as a realm of mindless, unfeeling objects. Sustainability will almost certainly depend upon developing mutually enhancing relations between humans and nonhuman nature.

This isn’t a new plea, though. Over 200 years ago, the famous naturalist Alexander Von Humboldt (1769-1859) was facing the same challenges.

In her compelling book The Invention of Nature: Alexander Von Humboldt’s New World, Andrea Wulf explores Humboldt as the first person to publish works promoting a holistic view of nature, arguing that nature could only be understood in relation to the subjectivity of experiencing it.

Fascinated by scientific instruments, measurements and observations, he was driven by a sense of wonder as well. Of course nature had to be measured and analyzed, but he also believed that a great part of our response to the natural world should be based on the senses and emotions.

Humboldt was a rock star scientist who ignored conventional boundaries in his exploration of nature. Humboldt’s desire to know and understand the world led him to investigate discoveries in all scientific disciplines, and to see the interwoven patterns embedded in this knowledge — mental models anyone?

If nature was a web of life, he couldn’t look at it just as a botanist, a geologist or a zoologist. He required information about everything from everywhere.

Humboldt grew up in a world where science was dry, nature mechanical, and man an aloof and separate chronicler of what was before him. Not only did Humboldt have a new vision of what our understanding of nature could be, but he put humans in the middle of it.

Humboldt’s Essay on the Geography of Plants promoted an entirely different understanding of nature. Instead of only looking at an organism, … Humboldt now presented relationships between plants, climate and geography. Plants were grouped into zones and regions rather than taxonomic units. … He gave western science a new lens through which to view the natural world.

Revolutionary for his time, Humboldt rejected the Cartesian ideas of animals as mechanical objects. He also argued passionately against the growing approach in the sciences that put man atop and separate from the rest of the natural world. Promoting a concept of unity in nature, Humboldt saw nature as a “reflection of the whole … an organism in which the parts only worked in relation to each other.”

Furthermore, that “poetry was necessary to comprehend the mysteries of the natural world.”

Wulf paints one of Humboldt’s greatest achievements as his ability and desire to make science available to everyone. No one before him had “combined exact observation with a ‘painterly description of the landscape”.

By contrast, Humboldt took his readers into the crowded streets of Caracas, across the dusty plains of the Llanos and deep into the rainforest along the Orinoco. As he described a continent that few British had ever seen, Humboldt captured their imagination. His words were so evocative, the Edinburgh Review wrote, that ‘you partake in his dangers; you share his fears, his success and his disappointment.’

In a time when travel was precarious, expensive and unavailable to most people, Humboldt brought his experiences to anyone who could read or listen.

On 3 November 1827, … Humboldt began a series of sixty-one lectures at the university. These proved so popular that he added another sixteen at Berlin’s music hall from 6 December. For six months he delivered lectures several days a week. Hundreds of people attended each talk, which Humboldt presented without reading from his notes. It was lively, exhilarating and utterly new. By not charging any entry fee, Humboldt democratized science: his packed audiences ranged from the royal family to coachmen, from students to servants, from scholars to bricklayers – and half of those attending were women. Berlin had never seen anything like it.

The subjectification of nature is about seeing nature, experiencing it. Humboldt was a master of bringing people to worlds they couldn’t visit, allowing them to feel a part of it. In doing so, he wanted to force humanity to see itself in nature. If we were all part of the giant web, then we all had a responsibility to understand it.

When he listed the three ways in which the human species was affecting the climate, he named deforestation, ruthless irrigation and, perhaps most prophetically, the ‘great masses of steam and gas’ produced in the industrial centres. No one but Humboldt had looked at the relationship between humankind and nature like this before.

His final opus, a series of books called Cosmos, was the culmination of everything that Humboldt had learned and discovered.

Cosmos was unlike any previous book about nature. Humboldt took his readers on a journey from outer space to earth, and then from the surface of the planet into its inner core. He discussed comets, the Milky Way and the solar system as well as terrestrial magnetism, volcanoes and the snow line of mountains. He wrote about the migration of the human species, about plants and animals and the microscopic organisms that live in stagnant water or on the weathered surface of rocks. Where others insisted that nature was stripped of its magic as humankind penetrated into its deepest secrets, Humboldt believed exactly the opposite. How could this be, Humboldt asked, in a world in which the coloured rays of an aurora ‘unite in a quivering sea flame’, creating a sight so otherworldly ‘the splendour of which no description can reach’? Knowledge, he said, could never ‘kill the creative force of imagination’ – instead it brought excitement, astonishment and wondrousness.

This is the ultimate subjectivity of nature. Being inspired by its beauty to try and understand how it works. Humboldt had respect for nature, for the wonders it contained, but also as the system in which we ourselves are an inseparable part.

Wulf concludes at the end that Humboldt,

…was one of the last polymaths, and died at a time when scientific disciplines were hardening into tightly fenced and more specialized fields. Consequently his more holistic approach – a scientific method that included art, history, poetry and politics alongside hard data – has fallen out of favour.

Maybe this is where the subjectivity of nature has gone. But we can learn from Humboldt the value of bringing it back.

In a world where we tend to draw a sharp line between the sciences and the arts, between the subjective and the objective, Humboldt’s insight that we can only truly understand nature by using our imagination makes him a visionary.

A little imagination is all it takes.

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Warnings From Sleep: Nightmares and Protecting The Self

Reading Time: 3 minutes

“All of this is evidence that the mind, although asleep,
is constantly concerned about the safety and integrity of the self.”

***

Rosalind Cartwright — also known as the Queen of Dreams — is a leading sleep researcher. In The Twenty-four Hour Mind: The Role of Sleep and Dreaming in Our Emotional Lives, she explores the role of nightmares and how we use sleep to protect ourselves.

When our time awake is frightening or remains unpressed, the sleeping brain “may process horrible images with enough raw fear attached to awaken a sleeper with a horrendous nightmare.” The more trauma we have in our lives the more likely we are to experience anxiety and nightmares after a horrific event.

The common feature is a threat of harm, accompanied by a lack of ability to control the circumstances of the threat, and the lack of or inability to develop protective behaviors.

The strategies we use for coping effectively with extreme stress and fear are controversial. Should we deny the threatening event and avoid thinking about it better than thinking about it and becoming sensitized to it?

One clear principle that comes out of this work is that the effects of trauma on sleep and dreaming depend on the nature of the threat. If direct action against the threat is irrelevant or impossible (as it would be if the trauma was well in the past), then denial may be helpful in reducing stress so that the person can get on with living as best they can. However, if the threat will be encountered over and over (such as with spousal abuse), and direct action would be helpful in addressing the threat, then denial by avoiding thinking about the danger (which helps in the short-term) will undermine problem-solving efforts and mastery in the long run. In other words, if nothing can be done, emotion-coping efforts to regulate the distress (dreaming) is a good strategy; but if constructive actions can be taken, waking problem-solving action is more adaptive.

What about nightmares?

Nightmares are defined as frightening dreams that wake the sleeper into full consciousness and with a clear memory of the dream imagery. These are not to be confused with sleep terrors. There are three main differences between these two. First, nightmare arousals are more often from late in the night’s sleep, when dreams are longest and the content is most bizarre and affect-laden (emotional); sleep terrors occur early in sleep. Second, nightmares are REM sleep-related, while sleep terrors come out of non-REM (NREM) slow-wave sleep (SWS). Third, sleepers experience vivid recall of nightmares, whereas with sleep terrors the experience is of full or partial amnesia for the episode itself, and only rarely is a single image recalled.

Nightmares abort the REM sleep, a critical component of our always on brain, Cartwright explains:

If we are right that the mind is continuously active throughout sleep—reviewing emotion-evoking new experiences from the day, scanning memory networks for similar experiences (which will defuse immediate emotional impact), revising by updating our organized sense of ourselves, and rehearsing new coping behaviors—nightmares are an exception and fail to perform these functions.

The impact is to temporarily relieve the negative emotion. The example Cartwright gives is “I am not about to be eaten by a monster. I am safe in my own bed.” But because the nightmare has woken me up, the nightmare is of no help in regulating my emotions (a critical role of sleep). As we learn to manage negative emotions while we are awake, that is, as we grow up, nightmares reduce in frequency and we develop skills for resolving fears.

It’s not always fear that wakes us from a nightmare. We can also be woken by anger, disgust, and grief.

Cartwright concludes, with an interesting insight, on the role of sleep in consolidating and protecting “the self.”:

[N]ightmares appear to be more common in those who have intense reactions to stress. The criteria cited for nightmare disorder in the diagnostic manual for psychiatric disorders, the Diagnostic and Statistical Manual IV-TR (DSM IV-TR), include this phrase “frightening dreams usually involving threats to survival, security, or self-esteem.” This theme may sound familiar: Remember that threats to self-esteem seem to precede NREM parasomnia awakenings. All of this is evidence that the mind, although asleep, is constantly concerned about the safety and integrity of the self.

The Twenty-four Hour Mind goes on to explore the history of sleep research through case studies and synthesis.

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The Science of Sleep: Regulating Emotions and the Twenty-four Hour Mind

Reading Time: 7 minutes

“Memory is never a precise duplicate of the original; instead, it is a continuing act of creation..”

— Rosalind Cartwright

Rosalind Cartwright is one of the leading sleep researchers in the world. Her unofficial title is Queen of Dreams.

In The Twenty-four Hour Mind: The Role of Sleep and Dreaming in Our Emotional Lives, she looks back on the progress of sleep research and reminds us there is much left in the black box of sleep that we have yet to shine light on.

In the introduction she underscores the elusive nature of sleep:

The idea that sleep is good for us, beneficial to both mind and body, lies behind the classic advice from the busy physician: “Take two aspirins and call me in the morning.” But the meaning of this message is somewhat ambiguous. Will a night’s sleep plus the aspirin be of help no matter what ails us, or does the doctor himself need a night’s sleep before he is able to dispense more specific advice? In either case, the presumption is that there is some healing power in sleep for the patient or better insight into the diagnosis for the doctor, and that the overnight delay allows time for one or both of these natural processes to take place. Sometimes this happens, but unfortunately sometimes it does not. Sometimes it is sleep itself that is the problem.

Cartwright underscores that our brains like to run on “automatic pilot” mode, which is one of the reasons that getting better at things requires concentrated and focused effort. She explains:

We do not always use our highest mental abilities, but instead run on what we could call “automatic pilot”; once learned, many of our daily cognitive behaviors are directed by habit, those already-formed points of view, attitudes, and schemas that in part make us who we are. The formation of these habits frees us to use our highest mental processes for those special instances when a prepared response will not do, when circumstances change and attention must be paid, choices made or a new response developed. The result is that much of our baseline thoughts and behavior operate unconsciously.

Relating this back to dreams, and one of the more fascinating parts of Cartwright’s research, is the role sleep and dreams play in regulating emotions. She explains:

When emotions evoked by a waking experience are strong, or more often were under-attended at the time they occurred, they may not be fully resolved by nighttime. In other words, it may take us a while to come to terms with strong or neglected emotions. If, during the day, some event challenges a basic, habitual way in which we think about ourselves (such as the comment from a friend, “Aren’t you putting on weight?”) it may be a threat to our self-concepts. It will probably be brushed off at the time, but that question, along with its emotional baggage, will be carried forward in our minds into sleep. Nowadays, researchers do not stop our investigations at the border of sleep but continue to trace mental activity from the beginning of sleep on into dreaming. All day, the conscious mind goes about its work planning, remembering, and choosing, or just keeping the shop running as usual. On balance, we humans are more action oriented by day. We stay busy doing, but in the inaction of sleep we turn inward to review and evaluate the implications of our day, and the input of those new perceptions, learnings, and—most important—emotions about what we have experienced.

What we experience as a dream is the result of our brain’s effort to match recent, emotion-evoking events to other similar experiences already stored in long-term memory. One purpose of this sleep-related matching process, this putting of similar memory experiences together, is to defuse the impact of those feelings that might otherwise linger and disrupt our moods and behaviors the next day. The various ways in which this extraordinary mind of ours works—the top-level rational thinking and executive deciding functions, the middle management of routine habits of thought, and the emotional relating and updating of the organized schemas of our self-concept—are not isolated from each other. They interact. The emotional aspect, which is often not consciously recognized, drives the not-conscious mental activity of sleep.

Later in the book, she writes more about how dreams regulate emotions:

Despite differences in terminology, all the contemporary theories of dreaming have a common thread — they all emphasize that dreams are not about prosaic themes, not about reading, writing, and arithmetic, but about emotion, or what psychologists refer to as affect. What is carried forward from waking hours into sleep are recent experiences that have an emotional component, often those that were negative in tone but not noticed at the time or not fully resolved. One proposed purpose of dreaming, of what dreaming accomplishes (known as the mood regulatory function of dreams theory) is that dreaming modulates disturbances in emotion, regulating those that are troublesome. My research, as well as that of other investigators in this country and abroad, supports this theory. Studies show that negative mood is down-regulated overnight. How this is accomplished has had less attention.

I propose that when some disturbing waking experience is reactivated in sleep and carried forward into REM, where it is matched by similarity in feeling to earlier memories, a network of older associations is stimulated and is displayed as a sequence of compound images that we experience as dreams. This melding of new and old memory fragments modifies the network of emotional self-defining memories, and thus updates the organizational picture we hold of “who I am and what is good for me and what is not.” In this way, dreaming diffuses the emotional charge of the event and so prepares the sleeper to wake ready to see things in a more positive light, to make a fresh start. This does not always happen over a single night; sometimes a big reorganization of the emotional perspective of our self-concept must be made—from wife to widow or married to single, say, and this may take many nights. We must look for dream changes within the night and over time across nights to detect whether a productive change is under way. In very broad strokes, this is the definition of the mood-regulatory function of dreaming, one basic to the new model of the twenty-four hour mind I am proposing.

In another fascinating part of her research, Cartwright outlines the role of sleep in skill enhancement. In short, “sleeping on it” is wise advice.

Think back to “take two aspirins and call me in the morning.” Want to improve your golf stroke? Concentrate on it before sleeping. An interval of sleep has been proven to bestow a real benefit for both laboratory animals and humans when they are tested on many different types of newly learned tasks. You will remember more items or make fewer mistakes if you have had a period of sleep between learning something new and the test of your ability to recall it later than you would if you spent the same amount of time awake.

Most researchers agree “with the overall conclusion that one of the ways sleep works is by enhancing the memory of important bits of new information and clearing out unnecessary or competing bits, and then passing the good bits on to be integrated into existing memory circuits.” This happens in two steps.

The first is in early NREM sleep when the brain circuits that were active while we were learning something new, a motor skill, say, or a new language, are reactivated and stay active until REM sleep occurs. In REM sleep, these new bits of information are then matched to older related memories already stored in long-term memory networks. This causes the new learning to stick (to be consolidated) and to remain accessible for when we need it later in waking.

As for the effect of alcohol has before sleep, Carlyle Smith, a Canadian Psychologist, found that it reduces memory formation, “reducing the number of rapid eye movements” in REM sleep. The eye movements, similar to the ones we make while reading, are how we do scanning of visual information.

The mind is active 24 hours a day:

If the mind is truly working continuously, during all 24 hours of the day, it is not in its conscious mode during the time spent asleep. That time belongs to the unconscious. In waking, the two types of cognition, conscious and unconscious, are working sometimes in parallel, but also often interacting. They may alternate, depending on our focus of attention and the presence of an explicit goal. If we get bored or sleepy, we can slip into a third mode of thought, daydreaming. These thoughts can be recalled when we return to conscious thinking, which is not generally true of unconscious cognition unless we are caught in the act in the sleep lab. This third in-between state is variously called the preconscious or subconscious, and has been studied in a few investigations of what is going on in the mind during the transition before sleep onset.

Toward the end, Cartwright explores the role of sleep.

[I]n good sleepers, the mind is continuously active, reviewing experience from yesterday, sorting which new information is relevant and important to save due to its emotional saliency. Dreams are not without sense, nor are they best understood to be expressions of infantile wishes. They are the result of the interconnectedness of new experience with that already stored in memory networks. But memory is never a precise duplicate of the original; instead, it is a continuing act of creation. Dream images are the product of that creation. They are formed by pattern recognition between some current emotionally valued experience matching the condensed representation of similarly toned memories. Networks of these become our familiar style of thinking, which gives our behavior continuity and us a coherent sense of who we are. Thus, dream dimensions are elements of the schemas, and both represent accumulated experience and serve to filter and evaluate the new day’s input.

Sleep is a busy time, interweaving streams of thought with emotional values attached, as they fit or challenge the organizational structure that represents our identity. One function of all this action, I believe, is to regulate disturbing emotion in order to keep it from disrupting our sleep and subsequent waking functioning. In this book, I have offered some tests of that hypothesis by considering what happens to this process of down-regulation within the night when sleep is disordered in various ways.

Cartwright develops several themes throughout The Twenty-four Hour Mind. First is that the mind is continuously active. Second is the role of emotion in “carrying out the collaboration of the waking and sleeping mind.” This includes exploring whether the sleeping mind “contributes to resolving emotional turmoil stirred up by some real anxiety inducing circumstance.” Third is how sleeping contributes to how new learning is retained. Accumulated experiences serve to filter and evaluate the new day’s input.

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Competition, Cooperation, and the Selfish Gene

Reading Time: 6 minutes

Richard Dawkins has one of the best-selling books of all time for a serious piece of scientific writing.

Often labeled “pop science”, The Selfish Gene pulls together the “gene-centered” view of evolution: It is not really individuals being selected for in the competition for life, but their genes. The individual bodies (phenotypes) are simply carrying out the instructions of the genes. This leads most people to a very “competition focused” view of life. But is that all?

***

More than 100 years before The Selfish Gene, Charles Darwin had famously outlined his Theory of Natural Selection in The Origin of Species.

We’re all hopefully familiar with this concept: Species evolve over long periods time through a process of heredity, variation, competition, and differential survival.

The mechanism of heredity was invisible to Darwin, but a series of scientists, not without a little argument, had figured it out by the 1970’s: Strands of the protein DNA (“genes”) encoded instructions for the building of physical structures. These genes were passed on to offspring in a particular way – the process of heredity. Advantageous genes were propagated in greater numbers. Disadvantageous genes, vice versa.

The Selfish Gene makes a particular kind of case: Specific gene variants grow in proportion to a gene pool by, on average, creating advantaged physical bodies and brains. The genes do their work through “phenotypes” – the physical representation of their information. As Helena Cronin would put in her book The Ant and the Peacock, “It is the net selective value of a gene’s phenotypic effect that determines the fate of the gene.”

This take of the evolutionary process became influential because of the range of hard-to-explain behavior that it illuminated.

Why do we see altruistic behavior? Because copies of genes are present throughout a population, not just in single individuals, and altruism can cause great advantages in those gene variants surviving and thriving. (In other words, genes that cause individuals to sacrifice themselves for other copies of those same genes will tend to thrive.)

Why do we see more altruistic behavior among family members? Because they are closely related, and share more genes!

Many problems seemed to be solved here, and the Selfish Gene model became one for all-time, worth having in your head.

However, buried in the logic of the gene-centered view of evolution is a statistical argument. Gene variants rapidly grow in proportion to the rest of the gene pool because they provide survival advantages in the average environment that the gene will experience over its existence. Thus, advantageous genes “selfishly” dominate their environment before long. It’s all about gene competition.

This has led many people, some biologists especially, to view evolution solely through the lens of competition. Unsurprisingly, this also led to some false paradigms about a strictly “dog eat dog” world where unrestricted and ruthless individual competition is deemed “natural”.

But what about cooperation?

***

The complex systems researcher Yaneer Bar-Yam argues that not only is the Selfish Gene a limiting concept biologically and possibly wrong mathematically (too complex to address here, but if you want to read about it, check out these pieces), but that there are more nuanced ways to understand the way competition and cooperation comfortably coexist. Not only that, but Bar-Yam argues that this has implications for optimal team formation.

In his book Making Things Work, Bar-Yam lays out a basic message: Even in the biological world, competition is a limited lens through which to see evolution. There’s always a counterbalance of cooperation.

Counter to the traditional perspective, the basic message of this and the following chapter is that competition and cooperation always coexist. People see them as opposing and incompatible forces. I think that this is a result of an outdated and one-sided understanding of evolution…This is extremely useful in describing nature and society; the basic insight that “what works, works” still holds. It turns out, however, that what works is a combination of competition and cooperation.

Bar-Yam uses the analogy of a sports team which exists in context of a sports league – let’s say the NBA. Through this lens we can see why players, teams, and leagues compete and cooperate. (The obvious analogy is that genes, individuals, and groups compete and cooperate in the biological world.)

In general, when we think about the conflict between cooperation and completion in team sports, we tend to think about the relationships between the players on a team. We care deeply about their willingness to cooperate and we distinguish cooperative “team players” from selfish non-team players, complaining about the latter even when their individual skill is formidable.

The reason we want players to cooperate is so that they can compete better as a team. Cooperation at the level of the individual enables effective competition at the level of the group, and conversely, the competition between teams motivates cooperation between players. There is a constructive relationship between cooperation and competition when they operate at different levels of organization.

The interplay between levels is a kind of evolutionary process where competition at the team level improves the cooperation between players. Just as in biological evolution, in organized team sports there is a process of selection of winners through competition of teams. Over time, the teams will change how they behave; the less successful teams will emulate strategies of teams that are doing well.

At every level then, there is an interplay between cooperation and competition. Players compete for playing time, and yet must be intensively cooperative on the court to compete with other teams. At the next level up, teams compete with each other for victories, and yet must cooperate intensively to sustain a league at all.

They create agreed upon rules, schedule times to play, negotiate television contracts, and so on. This allows the league itself to compete with other leagues for scarce attention from sports fans. And so on, up and down the ladder.

Competition among players, teams, and leagues is certainly a crucial dynamic. But it isn’t all that’s going on: They’re cooperating intensely at every level, because a group of selfish individuals loses to a group of cooperative ones.

And it is the same among biological species. Genes are competing with each other, as are individuals, tribes, and species. Yet at every level, they are also cooperating. The success of the human species is clearly due to its ability to cooperate in large numbers; and yet any student of war can attest to its deadly competitive nature. Similar dynamics are at play with ants, rats, and chimpanzees, among other species of insect and animal. It’s a yin and yang world.

Bar-Yam thinks this has great implications for how to build successful teams.

Teams will improve naturally – in any organization – when they are involved in a competition that is structured to select those teams that are better at cooperation. Winners of a competition become successful models of behavior for less successful teams, who emulate their success by learning their strategies and by selecting and trading team members.

For a business, a society, or any other complex system made up of many individuals, this means that improvement will come when the system’s structure involves a completion that rewards successful groups. The idea here is not a cutthroat competition of teams (or individuals) but a competition with rules that incorporate some cooperative activity with a mutual goal.

The dictum that “politics is the art of marshaling hatreds” would seem to reflect this notion: A non-violent way for competition of cooperative groups for dominance. As would the incentive systems of majorly successful corporations like Nucor and the best hospital systems, like the Mayo Clinic. Even modern business books are picking up on it.

Individual competition is important and drives excellence. Yet, as Bar-Yam points out, it’s ultimately not a complete formula. Having teams compete is more effective: You need to harness competition and cooperation at every level. You want groups pulling together, creating emerging effects where the whole is greater than the sum of the parts (a recurrent theme throughout nature).

You should read his book for more details on both this idea and the concept of complex systems in general. Bar-Yam also elaborated on his sports analogy in a white-paper here. If you’re interested in complex systems, check out this post on frozen accidents. Also, for more on creating better groups, check out how Steve Jobs did it.

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Scientific Concepts We All Ought To Know

Reading Time: 11 minutes

John Brockman’s online scientific roundtable Edge.org does something fantastic every year: It asks all of its contributors (hundreds of them) to answer one meaningful question. Questions like What Have You Changed Your Mind About? and What is Your Dangerous Idea?

This year’s was particularly awesome for our purposes: What Scientific Term or Concept Ought To Be More Known?

The answers give us a window into over 200 brilliant minds, with the simple filtering mechanism that there’s something they know that we should probably know, too. We wanted to highlight a few of our favorites for you.

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From Steven Pinker, a very interesting thought on The Second Law of Thermodynamics (Entropy). This reminded me of the central thesis of The Origin of Wealth by Eric Beinhocker. (Which we’ll cover in more depth in the future: We referenced his work in the past.)

The Second Law of Thermodynamics states that in an isolated system (one that is not taking in energy), entropy never decreases. (The First Law is that energy is conserved; the Third, that a temperature of absolute zero is unreachable.) Closed systems inexorably become less structured, less organized, less able to accomplish interesting and useful outcomes, until they slide into an equilibrium of gray, tepid, homogeneous monotony and stay there.

In its original formulation the Second Law referred to the process in which usable energy in the form of a difference in temperature between two bodies is dissipated as heat flows from the warmer to the cooler body. Once it was appreciated that heat is not an invisible fluid but the motion of molecules, a more general, statistical version of the Second Law took shape. Now order could be characterized in terms of the set of all microscopically distinct states of a system: Of all these states, the ones that we find useful make up a tiny sliver of the possibilities, while the disorderly or useless states make up the vast majority. It follows that any perturbation of the system, whether it is a random jiggling of its parts or a whack from the outside, will, by the laws of probability, nudge the system toward disorder or uselessness. If you walk away from a sand castle, it won’t be there tomorrow, because as the wind, waves, seagulls, and small children push the grains of sand around, they’re more likely to arrange them into one of the vast number of configurations that don’t look like a castle than into the tiny few that do.

The Second Law of Thermodynamics is acknowledged in everyday life, in sayings such as “Ashes to ashes,” “Things fall apart,” “Rust never sleeps,” “Shit happens,” You can’t unscramble an egg,” “What can go wrong will go wrong,” and (from the Texas lawmaker Sam Rayburn), “Any jackass can kick down a barn, but it takes a carpenter to build one.”

Scientists appreciate that the Second Law is far more than an explanation for everyday nuisances; it is a foundation of our understanding of the universe and our place in it. In 1915 the physicist Arthur Eddington wrote:

[…]

Why the awe for the Second Law? The Second Law defines the ultimate purpose of life, mind, and human striving: to deploy energy and information to fight back the tide of entropy and carve out refuges of beneficial order. An underappreciation of the inherent tendency toward disorder, and a failure to appreciate the precious niches of order we carve out, are a major source of human folly.

To start with, the Second Law implies that misfortune may be no one’s fault. The biggest breakthrough of the scientific revolution was to nullify the intuition that the universe is saturated with purpose: that everything happens for a reason. In this primitive understanding, when bad things happen—accidents, disease, famine—someone or something must have wanted them to happen. This in turn impels people to find a defendant, demon, scapegoat, or witch to punish. Galileo and Newton replaced this cosmic morality play with a clockwork universe in which events are caused by conditions in the present, not goals for the future. The Second Law deepens that discovery: Not only does the universe not care about our desires, but in the natural course of events it will appear to thwart them, because there are so many more ways for things to go wrong than to go right. Houses burn down, ships sink, battles are lost for the want of a horseshoe nail.

Poverty, too, needs no explanation. In a world governed by entropy and evolution, it is the default state of humankind. Matter does not just arrange itself into shelter or clothing, and living things do everything they can not to become our food. What needs to be explained is wealth. Yet most discussions of poverty consist of arguments about whom to blame for it.

More generally, an underappreciation of the Second Law lures people into seeing every unsolved social problem as a sign that their country is being driven off a cliff. It’s in the very nature of the universe that life has problems. But it’s better to figure out how to solve them—to apply information and energy to expand our refuge of beneficial order—than to start a conflagration and hope for the best.

Richard Nisbett (a social psychologist) has a great one — a concept we’ve hit on before but is totally underappreciated by most people: The Fundamental Attribution Error.

Modern scientific psychology insists that explanation of the behavior of humans always requires reference to the situation the person is in. The failure to do so sufficiently is known as the Fundamental Attribution Error. In Milgram’s famous obedience experiment, two-thirds of his subjects proved willing to deliver a great deal of electric shock to a pleasant-faced middle-aged man, well beyond the point where he became silent after begging them to stop on account of his heart condition. When I teach about this experiment to undergraduates, I’m quite sure I‘ve never convinced a single one that their best friend might have delivered that amount of shock to the kindly gentleman, let alone that they themselves might have done so. They are protected by their armor of virtue from such wicked behavior. No amount of explanation about the power of the unique situation into which Milgram’s subject was placed is sufficient to convince them that their armor could have been breached.

My students, and everyone else in Western society, are confident that people behave honestly because they have the virtue of honesty, conscientiously because they have the virtue of conscientiousness. (In general, non-Westerners are less susceptible to the fundamental attribution error, lacking as they do sufficient knowledge of Aristotle!) People are believed to behave in an open and friendly way because they have the trait of extroversion, in an aggressive way because they have the trait of hostility. When they observe a single instance of honest or extroverted behavior they are confident that, in a different situation, the person would behave in a similarly honest or extroverted way.

In actual fact, when large numbers of people are observed in a wide range of situations, the correlation for trait-related behavior runs about .20 or less. People think the correlation is around .80. In reality, seeing Carlos behave more honestly than Bill in a given situation increases the likelihood that he will behave more honestly in another situation from the chance level of 50 percent to the vicinity of 55-57. People think that if Carlos behaves more honestly than Bill in one situation the likelihood that he will behave more honestly than Bill in another situation is 80 percent!

How could we be so hopelessly miscalibrated? There are many reasons, but one of the most important is that we don’t normally get trait-related information in a form that facilitates comparison and calculation. I observe Carlos in one situation when he might display honesty or the lack of it, and then not in another for perhaps a few weeks or months. I observe Bill in a different situation tapping honesty and then not another for many months.

This implies that if people received behavioral data in such a form that many people are observed over the same time course in a given fixed situation, our calibration might be better. And indeed it is. People are quite well calibrated for abilities of various kinds, especially sports. The likelihood that Bill will score more points than Carlos in one basketball game given that he did in another is about 67 percent—and people think it’s about 67 percent.

Our susceptibility to the fundamental attribution error—overestimating the role of traits and underestimating the importance of situations—has implications for everything from how to select employees to how to teach moral behavior.

Cesar Hidalgo, author of what looks like an awesome book, Why Information Grows, wrote about Criticality, which is a very important and central concept to understanding complex systems:

In physics we say a system is in a critical state when it is ripe for a phase transition. Consider water turning into ice, or a cloud that is pregnant with rain. Both of these are examples of physical systems in a critical state.

The dynamics of criticality, however, are not very intuitive. Consider the abruptness of freezing water. For an outside observer, there is no difference between cold water and water that is just about to freeze. This is because water that is just about to freeze is still liquid. Yet, microscopically, cold water and water that is about to freeze are not the same.

When close to freezing, water is populated by gazillions of tiny ice crystals, crystals that are so small that water remains liquid. But this is water in a critical state, a state in which any additional freezing will result in these crystals touching each other, generating the solid mesh we know as ice. Yet, the ice crystals that formed during the transition are infinitesimal. They are just the last straw. So, freezing cannot be considered the result of these last crystals. They only represent the instability needed to trigger the transition; the real cause of the transition is the criticality of the state.

But why should anyone outside statistical physics care about criticality?

The reason is that history is full of individual narratives that maybe should be interpreted in terms of critical phenomena.

Did Rosa Parks start the civil rights movement? Or was the movement already running in the minds of those who had been promised equality and were instead handed discrimination? Was the collapse of Lehman Brothers an essential trigger for the Great Recession? Or was the financial system so critical that any disturbance could have made the trick?

As humans, we love individual narratives. We evolved to learn from stories and communicate almost exclusively in terms of them. But as Richard Feynman said repeatedly: The imagination of nature is often larger than that of man. So, maybe our obsession with individual narratives is nothing but a reflection of our limited imagination. Going forward we need to remember that systems often make individuals irrelevant. Just like none of your cells can claim to control your body, society also works in systemic ways.

So, the next time the house of cards collapses, remember to focus on why we were building a house of cards in the first place, instead of focusing on whether the last card was the queen of diamonds or a two of clubs.

The psychologist Adam Alter has another good one on a concept we all naturally miss from time to time, due to the structure of our mind. The Law of Small Numbers.

In 1832, a Prussian military analyst named Carl von Clausewitz explained that “three quarters of the factors on which action in war is based are wrapped in a fog of . . . uncertainty.” The best military commanders seemed to see through this “fog of war,” predicting how their opponents would behave on the basis of limited information. Sometimes, though, even the wisest generals made mistakes, divining a signal through the fog when no such signal existed. Often, their mistake was endorsing the law of small numbers—too readily concluding that the patterns they saw in a small sample of information would also hold for a much larger sample.

Both the Allies and Axis powers fell prey to the law of small numbers during World War II. In June 1944, Germany flew several raids on London. War experts plotted the position of each bomb as it fell, and noticed one cluster near Regent’s Park, and another along the banks of the Thames. This clustering concerned them, because it implied that the German military had designed a new bomb that was more accurate than any existing bomb. In fact, the Luftwaffe was dropping bombs randomly, aiming generally at the heart of London but not at any particular location over others. What the experts had seen were clusters that occur naturally through random processes—misleading noise masquerading as a useful signal.

That same month, German commanders made a similar mistake. Anticipating the raid later known as D-Day, they assumed the Allies would attack—but they weren’t sure precisely when. Combing old military records, a weather expert named Karl Sonntag noticed that the Allies had never launched a major attack when there was even a small chance of bad weather. Late May and much of June were forecast to be cloudy and rainy, which “acted like a tranquilizer all along the chain of German command,” according to Irish journalist Cornelius Ryan. “The various headquarters were quite confident that there would be no attack in the immediate future. . . . In each case conditions had varied, but meteorologists had noted that the Allies had never attempted a landing unless the prospects of favorable weather were almost certain.” The German command was mistaken, and on Tuesday, June 6, the Allied forces launched a devastating attack amidst strong winds and rain.

The British and German forces erred because they had taken a small sample of data too seriously: The British forces had mistaken the natural clustering that comes from relatively small samples of random data for a useful signal, while the German forces had mistaken an illusory pattern from a limited set of data for evidence of an ongoing, stable military policy. To illustrate their error, imagine a fair coin tossed three times. You’ll have a one-in-four chance of turning up a string of three heads or tails, which, if you make too much of that small sample, might lead you to conclude that the coin is biased to reveal one particular outcome all or almost all of the time. If you continue to toss the fair coin, say, a thousand times, you’re far more likely to turn up a distribution that approaches five hundred heads and five hundred tails. As the sample grows, your chance of turning up an unbroken string shrinks rapidly (to roughly one-in-sixteen after five tosses; one-in-five-hundred after ten tosses; and one-in-five-hundred-thousand after twenty tosses). A string is far better evidence of bias after twenty tosses than it is after three tosses—but if you succumb to the law of small numbers, you might draw sweeping conclusions from even tiny samples of data, just as the British and Germans did about their opponents’ tactics in World War II.

Of course, the law of small numbers applies to more than military tactics. It explains the rise of stereotypes (concluding that all people with a particular trait behave the same way); the dangers of relying on a single interview when deciding among job or college applicants (concluding that interview performance is a reliable guide to job or college performance at large); and the tendency to see short-term patterns in financial stock charts when in fact short-term stock movements almost never follow predictable patterns. The solution is to pay attention not just to the pattern of data, but also to how much data you have. Small samples aren’t just limited in value; they can be counterproductive because the stories they tell are often misleading.

There are many, many more worth reading. Here’s a great chance to build your multidisciplinary skill-set.

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