Here’s the take home: Studying hardware won’t help you understand the capabilities of pivot tables in Excel nor Code Interpreter in ChatGPT.
Your head is filled with entire analogies, metaphors, epistemologies, and tools that you once learned and now effortlessly use for thinking. It’s how you cook, how you count, and why you think invisible germs are a good explanation for disease. But invisible spirits are not.
Studying our genes and neural hardware won’t help you understand human intelligence. Our cultural software endows us with *new* cognitive capabilities.
How does this software get written? How do we become more brilliant, creative, and improve our education systems?
Consider how we count. We went from counting 1, 2, 3, many, as some small-scale societies still count, to a full-blown number system. Numbers likely emerged as an innovation for more efficiently tracking cattle and crops – you need to know who owes you what!
This new cognitive capability used a metaphor – fingers. But there’s nothing unique about fingers & 10 is awkward (16 would be better). Cultures have counted on body parts from base 6 to 27. But to count beyond body parts, we needed a different metaphor. Something like stones.
‘Calculus’ comes from ‘pebble’ (think calcium or limestone), and was used for addition and subtraction. Stones let you think about addition or subtraction beyond how creative you can get with body parts. There are some stones, and you can throw down more or snatch some away.
Stones are great for natural numbers: 1, 2, 3, 4, 5, etc. But stones don’t make zero obvious. What does zero pebbles look like? It looks a lot like zero of everything else – it’s nothing – and ‘nothing’ is hard to imagine. Zero came a lot later. What about negatives?
The number line as a metaphor helped make zero more concrete and easily transmissible even to children. Number lines work by mapping numbers not to objects but to movement and position, but they also revealed the negative numbers, which are not otherwise intuitive!
“Negative numbers darken the very whole doctrines of the equations and make dark of the things which are in their nature excessively obvious and simple” as Francis Maseres complained in the 18th century.
Nothing about numbers is intuitive to our ape brains. But these metaphors, mental models, and cultural innovations – cultural software – literally changed our minds and gave us new capacities. They’re like software upgrades.
These kids have a Soroban abacus in their heads allowing them to swiftly add large sums: 3267 + 9853 + 6531 + 7991 + 2641 in seconds. It’s a brand new cognitive capability. New cultural software. Video here: https://twitter.com/mmuthukrishna/status/1684576156803289091?s=20
Some innovations are more general than others. For example, thanks to the invention of writing, I can convey information through straight and squiggly lines on a page. I’m doing it right now and I’m literally changing your brain.
Another lesson: Mental tools can go out of date. Mental math became less useful. My middle school teacher, warned us about not being able to +, -, x, / without a calculator (because we wouldn’t be carrying calculators in our pocket). He didn’t foresee the arrival of the iPhone.
Much of what we assume are human capabilities are actually cultural software, invented and transmitted. This can be hard to see because we all live in a bubble. Academics in Ivory Towers, coastal elites, rural small towns – all part of a big bubble.
Almost everyone you’ll ever meet went to school; can all read, write, & count; and consumes some form of television and online media.
Breaking out of this big bubble requires going back in time or to far-flung places.
If our cultural software is what makes us smart, it means that we can be deliberate in how it gets written. We can seek out new mental models, intellectually arbitrage our way to creativity & discovery, and revitalize our education systems.
If you liked this post and want to learn more about how cultural evolution can be applied to our lives, companies, and societies, please pre-order A Theory of Everyone: https://linktr.ee/theoryofeveryone. Pre-orders really help with the success of the book and Amazon pre-orders guarantee the lowest price. Thank you!
Muthukrishna, M., Henrich, J. & Slingerland, E. (2021). Psychology as a Historical Science. Annual Review ofPsychology, 72, 717-49. [Download] [Publisher] [Twitter]
Henrich, J. & Muthukrishna, M. (2021). The Origins and Psychology of Human Cooperation. Annual Review ofPsychology, 72, 207-40. [Download] [Publisher] [Twitter]
The research is also related to my forthcoming book and to a new grant, which aims to deepen our understanding of the underlying mechanisms that enable cooperation and how they can be leveraged to foster greater harmony and unity in our interconnected world.
I was invited by the Behavioural Insights Team (BIT) to speak about cultural behavioral science and its applications in public policy. I explain how, by using cultural evolution as a theory of human behavior can help some of the challenges in behavioral science in terms of long term change and contextual factors that affect whether an intervention will work. This figure from a key paper presents the history of behavioral science that has led to cultural evolutionary behavioral science as an obvious next step.
The most relevant papers are:
Muthukrishna, M. (2019). Cultural Evolutionary Public Policy. Nature Human Behaviour, 4, 12-13. [Download] [Publisher]
Schimmelpfennig, R. & Muthukrishna, M. (2023). Cultural Evolutionary Behavioural Science in Public Policy. Behavioural Public Policy. [Publisher] [Download] [Twitter] [LinkedIn]
My talk begins with an overview of the problem plaguing behavioral economics – the lack of a theoretical foundation that can guide policy interventions. I introduce cultural evolution as a possible solution to bridge the theoretical gap. By using cultural evolution as a theory of human behavior, improvements can be made in policy efficiency. For example, studying how social norms change and evolve over time will provide a foundation for implementing effective policy interventions in multicultural societies. Some of this history is captured in this figure from the paper:
Considering the historical path dependence of norms provides crucial in understanding why certain populations hold certain beliefs, like vaccine hesitancy and a distrust in healthcare systems. Identifying how people acquire cultural norms, and narrowing down the ultimate causes for behavior (through cultural distance tools like world.culturalytics.com) could provide insights into designing interventions that work.
Understanding cultural evolution and behavioral science can help reanalyze the literature on public policy, providing insights into why some approaches are successful while others are not. I explain how studying universal cognitive capabilities will provide a deeper understanding of norm change, and thus, improve policy design.
Robin Schimmelpfenning and I discussed our co-authored paper on the paradox of diversity in the collective brain. We discuss how the rate of innovation depends on sociality, information fidelity, and cultural trait diversity. While cultural trait diversity offers the largest potential for empowering innovation, it also brings with it potential coordination and cooperation challenges. Diversity, in other words, is both a source of innovation and divisive; a double-edge sword. We then propose using cultural evolvability as a framework for resolving this paradox.
Our presentation was followed by a discussion session and subsequently a panel discussion chaired by Dominic Abrams.
Matthew Syed looks at how kids’ TV got smart, and what we can learn about the developing mind from the program makers who led the way. I discuss the role of cultural evolution in this phenomenon.
Boston, Massachusetts. 1970. A group of mothers and young children assembles outside the offices of the local TV station. It’s the first phase of a fight to improve kids’ TV that would go all the way to the United States Senate. In the late 1960s, children’s television in the US was dominated by cheap cartoons and adverts for sugary snacks. Peggy Charren had something to say about it. She formed a grassroots activism group in her living room with other concerned mothers – Action for Children’s Television. It would become one of the most influential broadcast lobbying groups in history. Peggy was part of a wave of people who were starting to take kids’ TV seriously. From the creators of Sesame Street to psychological researchers like Professor Daniel Anderson who brought science into children’s program-making, Matthew draws out what we can learn from these innovators who know how to create a hit show.
So many great points included from the other guests:
Debbie Charren, Peggy’s daughter, and former schoolteacher and reading specialist;
Robert Krock, Action for Children’s Television’s former development director;
Daniel Anderson, Professor Emeritus at the Department of Psychological and Brain Sciences, University of Massachusetts Amherst;
and Andrew Davenport, creator, writer and composer of In the Night Garden, Moon and Me, and Teletubbies.
Long post, but an important topic that helps to resolve controversies such as IQ differences.
Quick summary: We reconcile behavioral genetics and cultural evolution under a dual inheritance framework. A cultural evolutionary behavioral genetic approach cuts through the nature–nurture debate and helps resolve controversies such as IQ.
Business is booming in behavioral genetics. We’re in the midst of a GWAS gold rush. Powerful computers and sequenced DNA of millions has led to an industrious search for SNPs that correlate with a variety of traits. Some even claim the curse of reverse causality has been lifted.
There’s also been a parallel revolution in cultural psychology and cultural evolution. Genes, culture, and the environment have often co-evolved, shaping our species. But the revolutions in behavioral genetics and cultural evolution have largely been independent. But, given the extensiveness of the cultural and culturally-shaped environment, cultural evolution offers an important but typically missing complement to otherwise insightful methodological and empirical analyses within behavioral genetics. Genes and culture are intertwined. For example, our jaws too weak and guts too short for a world w/o controlled fire & cooked food. It’s obvious that lower environmental variation will lead to higher heritability scores. Less obvious is how culture can mask or unmask genetic variation. Or how diffusion and innovation can increase or decrease heritability. Or how to define a single society for the purposes of measuring heritability, without being able to identify cultural cleavages that can lead to Scarr-Rowe type effects: en.wikipedia.org/wiki/Scarr-Row…
Reconciling behavioral genetics & cultural evolution offers insights for differences in heritability between and within populations, differences in heritability across development, and the rise in IQ (Flynn Effect). We’d like a discussion that nuances common interpretations of the nature and nurture of behavior.
First, let’s quickly get a common misinterpretation of heritability out of the way: Heritability is not an index of the genetic basis of a trait nor a measure of the relative contribution of nature compared to nurture. It’s the proportion of phenotypic variance for some trait that is explained by genetic variance. So obviously variability in genes, in environment, and in traits will all matter. A quick illustration: skin pigmentation and UV levels. Genes affect level of skin pigmentation and propensity for tanning instead of burning; ancestral adaptations to UV radiation at different latitudes.
Migration means melanin is mismatched to latitude: Aussies with European ancestry are more susceptible to skin cancer; Europeans with African and South Asian ancestry have higher rates of vitamin D deficiency.
A Gene×Environment approach won’t predict how heritability estimates change over time as non-genetic adaptations compensate for genetic mismatches: fairer Australians wear sunscreen, a hat, & covered clothing; darker Europeans consume vitamin D supplements & vitamind D-rich or fortified foods. Here it’s easier to see that heritability is a function not only of genes, traits, and ecology, but also of an evolving cultural environment. The environment is not an inert backdrop against which genes should be evaluated. It evolves in relation to both genes and ecology.
Four lessons before we continue. The first is obvious to behavioral geneticists, the second sometimes noted, the third and fourth are typically missing.
There is no overarching, one-quantity heritability of a trait to be discovered. There is no fixed answer to the question, “What is the heritability of skin cancer?”
Heritability will depend not only on ecology, but also on culture & specifically on diffusion and innovation—both of which can rapidly change and therefore rapidly change heritability estimates.
Diffusion and innovation are broadly directional. Cultural diffusion of sunscreen, clothing, shade & sunglasses, and cultural innovation toward more effective screening and treatment of melanomas all work to reduce heritability estimates due to a masking effect.
Were any of these an example of culture unmasking genetic effects, such as tanning salons that induce differential risk according to skin pigmentation level, we would have predicted an increase in heritability.
We might expect a stronger cultural response where ecological and cultural selection pressures are stronger—skin cancer mitigation in Australia but Vitamin D supplementation in northern Europe. Not been tested to our knowledge, but the predictions are clear.
“Which SNPs are associated with skin cancer?” is similarly culturally dependent. Societies where sunscreen use is common, we expect SNPs associated with skin pigmentation to be less predictive of skin cancer compared to societies where this is not the case.
Similarly, we would expect SNPs associated with antioxidant metabolism to be less predictive of skin cancer in societies whose foods are rich in antioxidants—such as in traditional Mediterranean cuisine.
Section 2.2 is on how cultural evolution shapes heritability through diffusion and innovation. We live on the peaks climbed by cultural evolution – human environments have already been shaped by cumulative cultural evolution—functionally overlapping with genetic evolution.
Diffusion and invention can mask or unmask genes. Examples using language, fertility, and schooling.
If Cantonese or Yoruba (both tonal) spread, heritability of language ability would increase proportional to variation in “tone” genes.
If Norwegian or Russian (both non-tonal) spread in the same population, heritability of language ability would decrease.
Contraception and social values in 20th century unmasked the effect of genes associated with reproductive behaviors and preferences (heritability rose in US). But a one-child policy or rigid childbearing norms masks the genetic effect.
School is a powerful mechanism for cultural diffusion. Heritability of literacy in:
Australia: Kindergarten: 0.84 Grade 1: 0.80
Scandinavia: Kindergarten: 0.33 Grade: 0.79
Cultural diffusion of literacy.
Australian children begin receiving compulsory literacy instruction in kindergarten, while in Scandinavia the kindergarten curriculum emphasizes social, emotional, and aesthetic development—literacy instruction only begins in Grade 1.
Assessing the genetic basis of literacy without accounting for particulars of curricula on cultural diffusion is a selection bias of unknown magnitude. Note that literacy in the home environment is already shaped by cultural evolution; there is no ‘baseline’ heritability. Heritability is a composite measure that captures both genes and culture. Saying literacy heritability in Scandinavia jumps up to 0.79 in Grade 1 reveals as much if not more about the disseminative power of modern schooling than it does about the genetic basis of literacy. Similar dynamics with innovation. Read about it in the paper.
However, one neglected factor is “cultural clustering”, where even highly useful forms of cultural knowledge may not easily permeate social barriers. Not necessarily ethnic boundaries, also class, wealth, occupation, political alignment, religion, or incidental geographic layout. Greater differential clustering can lead to a cultural Simpson’s paradox (we’ll get to that shortly, but see Section 3.4).
Cultural FST (CFST) is useful for identifying these clusters. You can read more about that paper here: https://michael.muthukrishna.com/beyond-weird-psychology-measuring-and-mapping-scales-of-cultural-and-psychological-distance/
Hopefully, you can see the importance of a cultural evolutionary behavioral genetics. We hope this target article will spark a vibrant discussion. But let’s move onto the problems that obscure the effect of culture:
(1) the WEIRD Sampling Problem
(2) the Hidden Cluster Problem
(3) the Causal Locus Problem
And then describe the:
(4) Cultural Simpson’s Paradox that emerges at their junction.
The WEIRD Sampling Problem
The WEIRD people problem? Pretty bad in genetics too. Twin studies: 94% Western: 60% US, UK, Aus; 25% Nordic 6% Non-Western: 4% China, Japan, South Korea, Taiwan
Remainder of the world, i.e. vast majority of humans are the remaining 2%
Same story in GWAS: 88% European ancestry. 72% from just 3 countries: US, UK, & Iceland 20% from Japan, China, and South Korea
From a cultural evolutionary perspective, given (a) cultural environment, (b) coevolution b/w culture & genes, & (c) cultural differences between populations, not surprising that: 1.Polygenic scores don’t translate well across ancestry groups (European scores, 42% in Africa) 2. Polygenic scores are highly sensitive to inadequately controlled population stratification. And so cultural variation and the hidden cluster problem is pernicious.
Hidden Cluster Problem
Cultural clusters (or segregated diversity) typically created by barriers impeding cultural transmission, such as topography, cultural conflict, language, social stratification by class, wealth, etc. Immigrant countries more clustered (Canada > Japan).
Countries whose borders are drawn arbitrarily with respect to the geographic arrangement of cultural groups, for example by colonial administration (many countries in Africa), are also likely to have high clustering. You can use CFST to find them: https://journals.sagepub.com/doi/abs/10.1177/0956797620916782
Note that cultural clustering is not the same as genetic clustering as we explain at length in Section 3.2.2. Indeed, reconciliation between cultural evolution and behavioral genetics requires an update in the way we think about culture.
Causal Locus Problem
Hidden cluster problem describes complexity that exists w/in social groupings. Culture is not an unstructured exogenous variable. Culture is constructive system that accumulates functional adaptations in a directed manner over time. Two key lessons here.
Lesson 1: Genes that make vs genes that break. The more complex a system, the more ways it can fail. Take the history of lighting.
Wood fire can be extinguished in 2 ways Flourescent bulbs have 7 ways to fail LEDs have 30
Faulty O-ring can explode a space shuttle and so on.
There is a fundamental asymmetry: easier to find ways to break the system than ways to explain or improve it. So too for gene function. All your cells have the same bootstrapped code, but they interact with each other, what they create, and their surroundings to create you.
There are many ways these interactions can go wrong. It is easier to identify deleterious genetic mutations than beneficial mutations. The space of failure is larger than the space of success, making genes that break more detectable than genes that make. For example, a single mutation can cause Mendelian disorders such as cystic fibrosis and Huntington’s disease, but no single mutation creates genius. Over 1000 genes have been linked to intelligence.
Each gene only explains a miniscule fraction of variation in intelligence, and the causal mechanisms are unlikely to be straightforward. In contrast to these genes that make, the causal mechanisms behind single gene mutations that cause intellectual disability—e.g. BCL11A, PHF8, ZDHHC9—are relatively well understood.
Increasing nutrition, improving schooling, and removing parasites have positive effects on IQ, but in a society where parasite infection is kept under control, we would not notice that parasite status correlates with intelligence. And by corollary, genes that provide protection against malnutrition, parasites, or pollution would only be positively associated with intelligence in environments where these insults occur. In environments where these insults have been removed, the same genes would not be associated with intelligence, and can even be deleterious, as with sickle cell trait. Not helpful if there’s no malaria.
Genes are functionally masked by cumulative cultural evolution, and we expect that this masking is extensive and systematic. A quick evolutionary and historical example: Vitamin C, the GLO gene, and dead sailors.
Vitamin C is an essential nutrient and its acquisition is thereby an essential biological function. Endogenous synthesis of vitamin C requires a gene called GLO, and GLO is present across most of the animal kingdom. But because vitamin C synthesis is metabolically costly, the gene is inactive in some species that have access to sufficient quantities of the nutrient in their diets. e.g. taxa such as teleost fishes, guinea pigs, many bats, some passerine birds, monkeys and apes.
Anthropoid primates occupy a frugivorous niche, and fruits often contain sufficient vitamin C. Here gene function is offloaded onto environmental resources. In turn, this offloading has behavioral implications. If a species becomes dependent on its environment for vitamin C, both its behavioral range and evolutionary trajectory become constrained by the availability of the nutrient. Humans are a nice example of this.
As our species migrated across the planet, we found ourselves in environments where vitamin C was in short supply. A deficiency of vitamin C causes scurvy—the bane of seafarers until the trial-and-error discovery that certain food items like sauerkraut and citrus could prevent ships from being packed with tired, bleeding, toothless, and eventually dead sailors.
Masking does not necessarily need to be in the direction from culture to genes: genetic assimilation is same process working in the opposite direction, where a trait that is regularly acquired through learning gradually transfers its locus to the genome (i.e. Baldwin effect).
Cultural Simpson’s Paradox
Which leads us to the Cultural Simpson’s Paradox. Causal Locus Problem can confound the measurement of genetic effects due to Hidden Cluster Problem obscured by WEIRD Sampling problem creating a Simpson’s paradox.
Let’s return to the UV example. The melanin-UV mismatch can be masked by the cultural diffusion of sunscreen, especially in regions with more exposure to sunlight. In other parts of the world, the issue is under-exposure to the sun causing vitamin D deficiency. Low vitamin D leads to lack of bone integrity, muscle strength, autoimmune disease, cardiovascular disease, cancer etc.
In US and France, more north you go, the the lower vitamin D levels. Makes sense, right?
But when we compare across Europe, we see the opposite pattern where people in northern countries have higher vitamin D than people in southern countries. What’s going on?
High consumption of fatty fish and cod liver oil in Northern Europe, as well as greater sun-seeking behavior in these countries compared to Mediterranean Europe. These are potent cultural adaptations.
Participants fed the traditional Norwegian fish dish mølje three times over a span of two days had 54 times the recommended daily dosage of vitamin D. The relationship between latitude and Vitamin D goes one way within a country, and the other way between the countries.
If we had been Martian anthropologists who did not know that the populated landmass known as “Europe” can in fact be broken down into sub-units called “countries”, these examples would be standard examples of a Simpson’s paradox.
In these cases, the paradox occurs when we do not know how to partition the higher-order population (Europe) into lower-order units. Fortunately, we can partition continents into countries, but in other cases, the relevant units is not as easily identifiable. Let’s move on.
We now have enough to make sense of puzzles in behavioral genetics such as (1) differences in heritability across socioeconomic levels, (2) differences in heritability across development, and (3) the Flynn effect.
SES: Heritability of IQ is higher among affluent, high socioeconomic status (SES) households than among poorer, low-SES households in some societies, but mixed in others. Why?
One explanation is ‘reciprocal causation’: genes well suited to a task can better nurture their skills in a wealthier environment than in a poorer environment and this is amplified over time. Maybe, but then why don’t we see the effect in Europe and Australia?
Here’s what we think is going on: in the US, the differences between school and home environments among high-SES households is smaller than among low-SES households. US is a land of variance. Factors such as school lotteries can dramatically affect the cultural input.
In contrast, the cultural environment is less unequal in western Europe and Australia, where, for example, high quality schools are available across SES. Where these two explanations make different predictions is for poorer countries.
Reciprocal causation would predict low heritability in poorer countries. We would predict high heritability where there is equal access to similarly poor schools and household conditions, but low heritability if inequality is high.
Incidentally we predict the opposite between human and animal environmental effects due to social transmission. It’s interesting, but not central. Check out Section 4.1.2. Let’s move onto heritability across development.
Heritability changes over the lifespan. Heritability of political orientation is similar for American identical and fraternal twins from middle childhood up to early adulthood. Right around the age at which American children leave home, this pattern is broken.
Drops for fraternal but not identical. We argue this is due to vertical vs oblique transmission and would predict a different drop off for say Italian or Croatian who leave home past 30.
Flynn effect describes the rise in IQ test scores over time. Largest in countries that have recently started modernizing, and smallest in countries that had attained modernization. No consensus to explain it, but given speed genes obviously unlikely.
We argue its caused by a rapid worldwide increase of cultural practices, technologies. Intelligence is about hardware—genes, parasites, pathogens, pollution, and nutrition affecting health and brain development, but also software—our increasingly complex cultural package.
By this account, not only is the idea of a culture-free IQ test implausible, but so too is the idea of culture-free IQ. Lots to say here. Go read Section 4.3.
Home stretch: Cultural Evolutionary Behavioral Genetics. The thrust of our theoretical case is that human psychology and behavior have a large cultural component that has been changing over history.
Most recently our psychology has been shaped by the advent of writing, numeracy, different types of agriculture, the Industrial Revolution, the Internet, and smart phones.
As new adaptive traits emerge, initially those who possess these traits will have an advantage, as in the case of access to new food sources, better healthcare, more efficient technologies, or easier methods of learning.
But eventually the traits will reach fixation in the population through the processes of cultural diffusion, at least until they are unseated by subsequent innovations. We predict that these cultural dynamics are reflected in heritability estimates.
As any geneticist knows, genetic heritability is a function of the variability in the environment, variability in genes, and variability in the phenotype. There is little to predict if the phenotype is homogenous, as in the number of fingers or kidneys.
There is little to predict with if the environment or genes are homogenous. But what is factored into the environment includes not only the physical ecology, but also the cultural environment.
While variance in genes and ecology may be relatively stable, the variance in the cultural environment is continually changing through the processes of cultural evolution. A genetic account of human psychology and behavior must also account for culture and cultural evolution.
Section 5 and the conclusion tie everything together, but I’ll leave you to read it (muth.io/cegh). There’s a formal model with some pretty graphs in the Appendix:
I was selected as one of 11 teams of researchers to receive inaugural awards of the Grand Challenges for Human Flourishing with a project titled ‘What does cultural evolution look like in the 21st century, and how can we use the answer to ensure continued human flourishing?’.
Templeton World Charity Foundation (TWCF) announced the initial investment in a $60 million commitment for bold research that pushes the boundaries of scientific knowledge to help people flourish.
More than 500 teams of scientists from over 350 academic institutions across the world answered the request for ideas, which push beyond traditional measures of physical and mental health to include happiness, meaning and purpose, spiritual well-being and striving in adversity. The 11 awards represent the work of more than 40 researchers at over two dozen institutions and amount to more than $1 million to encourage further exploration of these ideas and the advancement of science in human flourishing.
Some of the questions I hope to tackle include:
What does cultural evolution look like when people are united by a global Internet, but separated by filtered social network feeds?
How does our social learning psychology interpret this information to decide what is true, what others think, and whom we can trust?
What does cultural evolution look like when people separated by geographic and cultural distance regularly interact and even live together in the same country?
How do societies with very different cultural evolutionary histories find common ground to cooperate on global challenges?
Cultural evolution and dual inheritance theory are the closest we have come to a “theory of human behaviour” and “theory of social change”. But so far, we’ve focused our efforts on understanding the past – human origins and human history – rather than understanding the present or preparing for the future. The framework offers answers for what has led to human flourishing thus far, how we’ve overcome challenges on the path toward greater cooperation, and why some societies have diverged from others. I will be helping the Templeton World Charity Foundation (TWCF) strategise about how cultural evolution works in the 21st century. How this framework that helps explain human flourishing can also help ensure continued flourishing—support economic development, strengthen democratic institutions, and catalyse collective action to tackle the challenges of a post-climate changed world.
I gave a talk on “Cooperation and the moral circle: When cooperation harms the collective good” as part of the SPSP 2021 Justice and Morality Pre-Conference. It’s part of some new work on the problem of the expanding moral circle as it links to cooperation, corruption, prosocial, and antisocial behavior. A related working paper is available here: https://www.biorxiv.org/content/10.1101/2021.02.19.432029v2
Today’s episode is a conversation with Dr. Michael Muthukrishna, an Associate Professor of Economic Psychology at the London School of Economics.
Michael’s research takes on a suite of topics that all start from a single big question: Why are we so different from other animals? Part of the answer has to do with our neural hardware. There’s no question we’ve got big brains—and Michael has some cool things to say about why they may have gotten so big. But Michael is just as focused on our cultural software—the tools and ideas we develop, tweak, share, and accumulate over time. You might say he’s more impressed by our collective brains than by our individual brains. To study all this, Michael builds formal theories and computational models; he runs experiments; and he constructs and analyzes huge databases.
We cover a lot of ground in this episode. We talk about the finding that the size and interconnectedness of a social group affects the cultural skills that group can develop and maintain. We consider what actually powers innovation (hint: it’s not lone geniuses). We discuss how diversity is a bit double-edged and why psychology needs to become a historical science. And that, my friends, is hardly all—we also touch on cetaceans, religious history, and spinning plates.
I’ve been hoping to have Michael on the show for months now. His work is deeply theoretical, advancing the basic science of what it means to be human. But it’s also engaged with important practical issues—issues like corruption and cultural diversity. Without further ado, here’s my conversation with Dr. Michael Muthukrishna. Enjoy!
I gave a keynote at the Monk Prayogshala organized SPSP Bridge-Building Session. I introduced cultural evolution and dual inheritance theory as a theory of human behavior and how it can be used to a create a more holistic post-WEIRD psychological and behavioral science. My final points:
Our psychology is shaped by our societies, and our societies are shaped by their histories. We can do better than butterfly collecting–just measuring cross-cultural diffs. For psychology to develop a full theory of human behavior, we need historical psychology.
Psychology is shaped by millions of years of genetic evolution, thousands of years of cultural evolution, & a short lifetime of experience; yet, much of the field has focused on that short lifetime of experience. The WEIRD People Problem is not only about geography but history.
Past societies can be as culturally distant as distant societies. Cohort effects are a sliver of the cross-temporal variation we would expect in a culturally evolving species. History serves as a kind of psychological fossil record, a source of “data from dead minds”.
We (1) review work in historical psychology; (2) introduce methods including causal inference & how to extract data from dead minds; (3) explore the role of theory in mapping history to psychology; and (4) provide some conclusions concerning the future of this field.
E.g.s: Religious evolution & social psych. Some gods gained the ability to see into hearts & control an afterlife contingent on compliance. In many large-scale societies, these gods became omniscient, omnipotent, & omnibenevolent, coevolving with the scale of their societies.
This historical theory makes predictions not only about expected relationships in the historical record but also about expected contemporary cross-cultural diversity in religious beliefs and cognition. In doing so, the theory links historical psychology to cultural psychology.
WEIRD Psychology may have its origins in suppressing kin networks, changing family structures, & related via one particular religion: The Catholic Church
Institutions rest on invisible cultural and psychological pillars. E.g. a constitution’s proclamations are irrelevant without a belief in the rule of law, or norms of punishment for violations of this rule.
We discuss the importance of causal inference techniques in historical psychology: instrumental variables, difference-in-differences, regression discontinuity. Some e.g. use for slavery & trust in strangers; agriculture & sex diff, gender inequality, collectivism; personality.
Historical psychology includes the psychology of the past – data from dead minds, cognitive archeology. Historical databases are emerging. But sometimes the data is qualitative requiring tools like text analysis.
We discuss some examples of the importance of theory. A society has codependent norms, values, beliefs, behaviors, and institutions. If one takes an exploratory approach and looks for correlations in history, there are many to be found. Theory helps clarify causality.
Collaboration between psychologists, historians, and other humanities scholars is important (see religiondatabase.org for an e.g.). We discuss challenges & strategies.
Taking history seriously is a critical part of moving beyond the WEIRD people problem and making psychology a genuinely universal science of human cognition and behavior.
Diversity is a double edged sword. Governments and organizations often push for greater diversity and tolerance for diversity, because the human tendency is toward squashing difference and selecting others like ourselves. But diversity can both help and harm innovation.
On the one hand, there’s intellectual arbitrage: discoveries and technologies situated in one discipline that draw on a key insight from another. Here diversity is a fuel for the engine of innovation.
On the other hand, diversity is, by definition, divisive. Without a common understanding, common goals, and common language, the flow of ideas in social networks is stymied, preventing recombination and reducing innovation. How do we reap the benefits without paying the costs?
Consider the challenge of collaborations between scientists and humanities scholars (or even between scientists in different disciplines). The key is to find common ground through strategies such as optimal assimilation, translators and bridges, or division into subgroups.
Resolving the tension between diversity and selection is at the core of a successful innovation strategy. And there are many possible solutions.
Some dimensions of diversity matter more than others—without a common language, communication is difficult. On the other hand, food preferences create little more than an easily solved coordination challenge for lunch.
But between these are many dimensions where optimal assimilation may be desirable and traits can be optimized, such as psychological safety so people feel free to share unorthodox ideas.
Other strategies include interdisciplinary translators. In my role at the Database of Religious History (DRH)—a large science and humanities collaboration—we have benefited from a few scholars trained in both to bridge the gap.
Innovation can also be divided into independent groups, coordinating within the group but competing against others trying different strategies (e.g. competition between firms).
Check out the full issue here: https://www.nae.edu/244665/Winter-Issue-of-The-Bridge-on-Complex-Unifiable-Systems
I was a panelist at the Behavioral Science for Global Good at Behavioral Insights Group (BIG) conference hosted by Harvard Business School (add link) / Harvard Kennedy School (add link). The goal of the panel was to offer insight into the ways in which behavioral science may need to change in the future in order to fulfill its stated mission to make a positive difference in the world—particularly on how to expand our focus beyond predominantly WEIRD researchers, WEIRD research topics, and WEIRD populations.
My fellow panelists included:
Dolly Chugh, Associate Professor of Management and Organizations at NYU
Chaning Jang, CSO / VP of Research at the Busara Center for Behavioral Economics
Shinobu Kitayama, Robert B. Zajonc Collegiate Professor of Psychology at University of Michigan
Steven Roberts, Assistant Professor of Psychology at Stanford University
Neela Saldanha, Senior Advisor at the Busara Center for Behavioral Economics – who did a wonderful job chairing the discussion.