Cultural Evolution: Episode 2/3 Game Theory & The Illusion of Explanatory Depth

Zero sum games are ones in which the winners and losers balance out

In Episode 1, we introduced the idea of Cultural Evolution and how the dynamics of competition and cooperation come into play. Game theory provides a way to put these tensions into context . Games like poker, baseball, and political elections have a single winner and are called zero-sum games, but there are also positive sum games — games in which your winning doesn’t mean I lose. For instance, when we hunt as a group we can land bigger game than we could if we hunted solo. By working together, we can all win and we can all be better off.

Some kinds of scenarios can be played with either a zero sum or positive sum framing depending on conditions and perceptions. Let’s say you and I are in the restaurant business vying for customers.When you are successful in a market with limited customers, you have taken a chunk of that market I can never access. Under times of slow growth or scarcity it behooves you to keep what you are learning to yourself. In fact, it may even be adaptive to sabotage others.

But if there are plenty of customers, your success is actually predictive of my success because I can succeed by copying you. When there’s plenty to go around, we can be nicer to more people — we can openly share what we’re learning about how to run our businesses.

Even during times of scarcity, we might still cooperate, but we do it at a lower scale, for instance with family and maybe friends. But even the perception of slow growth or scarcity highlights social dividing lines that are always there. It is these natural dividing lines where fractures are most likely show up, threatening our ability to solve problems.

Sometimes there really isn’t enough for everyone, but it’s not always easy to tell because perception, trust, and reality are influencing each other.

Even beliefs such as “people can’t be trusted” can spread, fueling a cycle of scarcity.

Whether true or not, when we think there aren’t enough buffalo to share with everyone or that others won’t help us hunt them, we focus on smaller game and miss out on bigger wins. To further complicate matters, even beliefs spread due to our propensity to copy others. If people believe there isn’t enough to go around or that others can’t be trusted it spreads distrust that can further impede cooperation.

It’s this kind of circular causality that pervades evolution and one reason it’s so hard to grasp. Like most of us, I learned that genes are passed down from one generation to the next [transmission] and that there also needs to be some variation for adapting to happen. But it’s the selection part of “Evolution by Natural Selection” that’s tough to describe. Many educated folks sum it up as “survival of the fittest”. Clearly there are all manner of people surviving today — many are successful, some obscenely so — but there are also plenty of people who muddle through all the way to a ripe old age.

While “survival of the fittest” strikes me as woefully inadequate, the more time I spend trying to come up with a better explanation, the less I think I understand it at all. This might well be unavoidable.

The Illusion of Explanatory Depth is often revealed only when we try to explain something we think we understand well.

In sharing his work, Michael Muthukrishna clued me into a phenomenon called the illusion of explanatory depth where we overestimate our understanding of the world. Researchers at Yale who coined the phrase suggest that it’s only when we try to articulate some understanding in our heads that we are confronted with the muddiness of what had felt crystal-clear before we started trying to explain it.

This illusion seems like a cognitive glitch, but it’s a useful glitch that helps us in copying others. When we see what people are doing who we think of as successful we tend to copy them without knowing why — and sometimes without knowing we’re doing it. It’s this copy machinery that allows traditions to emerge organically across many generations, things like taboos that help pregnant women avoid food that will harm their fetuses even though they are unaware of the potential harm.

In Figments of Reality by Stewart & Cohen, Evolution is described using Game Theory

To address my own lack of explanatory depth around evolutionary workings, I borrow an explanation from Figments of Reality, a book by Ian Stewart, a mathematician, and Jack Cohen, a biologist. They invite readers to consider…

• today’s world as a snapshot of a game that has been going for 5 billion years.
• It’s a curious game with trillions of players and no fixed rules
• Players are free to make whatever moves the constraints of physics and chemistry (and we might add society) permit.
• Playing the game entails trying as many moves as possible.
• Winning moves — those that let you, your progeny, or your kin stay in the game — are only apparent in hindsight if decipherable at all.

“Fit enough” works much of the time, and even during times of scarcity you need only be fitter than those around you.

In episode three we’ll dig deeper into the ways cooperation and competition play out across multiple scales

For more information check out Michael Muthukrishna’s research as well as that of Leonid Rozenblit & Frank Keil on The misunderstood limits of folk science: an illusion of explanatory depth

In an effort to make work that is freely shareable, I opt out of Medium’s paywall. If you find my animations useful, consider becoming a patron on Patreon: https://www.patreon.com/researchArtist

This animation was created in collaboration with Michael Muthukrishna. Michael is an Associate Professor of Economic Psychology at the London School of Economics (LSE). His other affiliations include Associate of the Department of Human Evolutionary Biology at Harvard University, Affiliate of the Developmental Economics Group at STICERD, and Technical Director of The Database of Religious History.
Michael’s research focuses on answering three broad questions: (1) Why are humans so different to other animals? (2) What are the psychological and evolutionary processes that underlie culture and social change, and how is information transmitted, maintained, and modified? (3) How can the answers to these questions be used to tackle some of the challenges we face as a species? He uses a two-pronged methodological approach to answer these questions, combining mathematical and computational modeling (evolutionary models, social network models, etc.), and experimental and data science methods from psychology and economics. He uses the “Theory of Human Behavior” that emerges from this approach to tackle a variety of related topics, including innovation, corruption, the rise of large-scale cooperation, and the navigation of cross-cultural differences.