Schimmelpfennig, R. & Muthukrishna, M. (2023). Cultural Evolutionary Behavioural Science in Public Policy. Behavioural Public Policy. [Publisher] [Download] [Twitter] [LinkedIn]
Muthukrishna, M., Bell, A. V., Henrich, J., Curtin, C., Gedranovich, A., McInerney, J. & Thue, B. (2020). Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance. Psychological Science, 31(6), 678-701. [Download] [Supplementary] [Code] [Summary Post] [Publisher] [Twitter]
Henrich, J. & Muthukrishna, M. (2021). The Origins and Psychology of Human Cooperation. Annual Review ofPsychology, 72, 207-40. [Download] [Publisher] [Twitter]
Muthukrishna, M., Henrich, J. & Slingerland, E. (2021). Psychology as a Historical Science. Annual Review ofPsychology, 72, 717-49. [Download] [Publisher] [Twitter]
Muthukrishna, M., Francois, P., Pourahmadi, S., & Henrich, J. (2017). Corrupting Cooperation and How Anti-Corruption Strategies May Backfire. Nature Human Behaviour, 1(0138). [Download] [Summary Post] [Publisher]
Muthukrishna, M., Doebeli, M., Chudek, M., & Henrich, J. (2018). The Cultural Brain Hypothesis: How culture drives brain expansion, sociality, and life history. PLOS Computational Biology, 14(11): e1006504. [Download] [Supplementary] [Summary Post] [Publisher] [Twitter]
Schimmelpfennig, R., Razek, L., Schnell, E., & Muthukrishna, M. (2021). Paradox of Diversity in the Collective Brain. Philosophical Transactions of the Royal Society B: Biological Sciences. [Download] [Summary Post] [Publisher] [Twitter]
Uchiyama, R., Spicer, R. & Muthukrishna, M. (2021). Cultural Evolution of Genetic Heritability. [Target article]. Behavioral and Brain Sciences, 1-147. [Download] [Summary Post] [Publisher] [Twitter]
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.
Here’s the take home: diversity empowers innovation through recombination but also by definition divides us. We call this the paradox of diversity. A principled way to resolve this tension is by considering cultural evolvability.
We discuss implications for entrepreneurship, polarization & a nuanced take on diversity. This framework can also guide researchers and practitioners in how to reap the benefits of diversity by reducing costs.
Let’s start with innovation: A folk understanding of innovation is that it’s driven by a talented few – the giants upon whose shoulders we stand. But that view is inconsistent with theoretical and empirical work in cultural evolution.
Instead, innovations emerge as ideas flow through our social networks, requiring a specific innovator no more than your thoughts require a specific neuron. See: Innovation in the Collective Brain
People are often unaware of how little they actually deeply understand about the world – what’s referred to as the “knowledge illusion” or “illusion of explanatory depth”. The Knowledge Illusion is a good pop book on the topic.
The world is not only complicated, but more complicated than our psychology allows us to believe. Innovations emerge through incremental improvements through partial causal models and large leaps through serendipity & recombination.
Three key levers that affect innovation are sociality (size & interconnectedness of a population), transmission fidelity (how well you can transmit information between people), & cultural trait diversity. Diversity has the most potential benefit and the largest challenges.
Let me say a bit about each. 1. Sociality: in general +ve relationship, because large pops had to solve the coordination problem to become large. Interconnectivity has an optimal point. Small work groups can be easily overconnected; large pops should be more connected.
2. Transmission fidelity: under selection as cultural complexity increases. Hunter-gatherers not much explicit instruction.Industrial revolution eventually led to schools to download a minimum common cultural package – reading, writing, arithmetic, algorithms for thinking.
Today we have the printing press, radio, TV, Internet, social media, and Zoom. But there’s still too much to learn. Unless you get a PhD, 21C students don’t learn mathematics developed after 1900; scientific training is longer, & major contributions are made at an older age.
We spend longer learning, delaying kids. Theres limit to pop size & transmission; how long you can delay being productive. Another path is to divide up info & labor-specialize. Get smart at 1 thing & stupid at everything else: cultural trait diversity
Different kinds of diversity & different ways to measure it. Our focus is on cultural trait diversity-beliefs, behaviors, assumptions, values, technologies, & other transmissible traits. e.g. languages, processing techniques, technical skills, family structure & occupation.
In the public discourse, diversity often refers to ancestry or physical characteristics-skin color, ethnic origin, religion, sex, gender, sexual orientation, or ability. These may correlate with cultural trait diversity, but correlation may weaken over generations.
For example, Americans with different ancestries may possess similar WEIRD psychology (part of why I have an issue with the WEIRD=White take, though that’s a separate issue). I’ll use diversity from herein, but that’s what we mean.
Diversity can be distributed in different ways: Diversity between pops culturally evolves as pops adapt to local differences, influencing future generations through historical path dependence created by past conditions or founder populations. See also: Psychology as a Historical Science
Diversity within populations evolves as information and labor are divided as discussed above.
Within-population diversity includes disciplinary differences, such as the sciences and humanities, industry specialisations, guilds, and firms. Diversity can be structured as ‘cultural clusters’ by ethnicity, class, wealth, occupation, politics, religion, or incidental geographic layout. Cultural clusters may intersect, such as in ethnic occupation specialization-lots of examples. See also: Beyond WEIRD Psychology: Measuring and Mapping Scales of Cultural and Psychological Distance
Diversity may also exist within certain individuals—multicultural individuals, ‘third culture kids’ (like Barack Obama), interdisciplinary researchers, and so on.
Diversity is therefore both the product of cultural evolution and fuel for the engine of further innovation
But without common understanding & common goals, the flow of ideas in social networks is stymied, preventing recombination, and reducing innovation. Consider communication without a common language or collaborations between scientists & humanities, or different scientists.
We formalize this paradox of diversity trade off in the paper and will be exploring solutions in future work. Check out the paper for details. We argue cultural evolvability is the right way to think about this.
Evolvability refers to not how well adapted a population is to current circumstances, but its ability to evolve to future circumstances. Variation or diversity, and the forces that create and stabilise that diversity are key factors that create evolvability.
Cultural evolvability is a balance between diversity and selection, exploring and exploiting, sampling and specialising, convergent and divergent thinking, stability and change, efficiency and flexibility.
Lots of related work on diversity and selection, explore-exploit or sampling-specialising trade-off in development, search for global solutions & avoidance of saddle points within machine learning.
As an aside, ML insights: in a sufficiently high dimensional space there are effectively no local optima, only saddle points with some dimension that allows escape. Biological & cultural systems have large dimensionality, there are no true evolutionary stable equilibria.
Next, we review the diversity literature through the lens of cultural evolvability. First we lay out 9 challenges to interpreting the literature. It’s a literature that would be benefit from theory. See also: A Problem in Theory
Diversity overlaps with challenging aspects of psychology, norms & institutions: racism, prejudice, xenophobia, sexism, discrimination, power differences, social and economic inequalities.
Love to write about at some point, here we focus on coordination challenges, which influence and are influenced by these problematic features of the world. Our goal is to review the overall patterns in the literature and make sense of these in light of cultural evolvability.
Here’s some of the mixed lit: Within countries, diversity is often approximated by birthplace diversity, professional diversity, ethnic diversity or linguistic diversity. Research looking at the relationship between diversity and economic growth suggests: positive effect of birthplace diversity, but -ve effect of ethnic and linguistic diversity. Research asking questions about immigrants in general often ignore the heterogeneity – cultural distance and education (effectively the cultural traits in your head) matter. Even more mixed in firms. Overall, educational diversity and deep level diversity seem to be positive for innovation within a firm. Mixed effects within teams – we think the paradox of diversity can disentangle.
We derive some insights:
1. Cultural evolvability means tolerance for diversity. Currently less adaptive traits may be more adaptive when the environment changes. Different environments lead to different evolvability strategies. In materially insecure societies, not following a successful “Tiger Mom” strategy—working hard to secure scarce educational opportunities and subsequent employment opportunities—has a much larger cost. But this leads to incremental over radical innovation.
2. Cultural evolvability means under-optimization & inequality. Cultural evolvability necessarily means inequality in outcomes, because not all will have the optimal strategy for the current environment.
Firms face a tradeoff: strategies that favour efficiency & strategies that favour flexibility. Consistent, strong cultures perform well in stable markets, but poorly during times of change. Under-optimizing and allowing for flexibility increases a firm’s evolvability.
Not all firms can bear the cost of under-optimising in the short term-high risk, high value approaches better suited to larger firms or larger countries. Read about Satya Nadella and Microsoft:
Compromize strategies: skunkworks, ecosystems of different firms trying different strategies (e.g. Silicon Valley), or countries composed of different states or regions trying different approaches (e.g. what Justice Brandeis described as “laboratories of democracy”).
In shared multi-agent reinforcement learning, diversity increases performance through exploration and individualized behaviors. Evolvability means many approaches will be suboptimal or even fail, but the successful approaches can be spread and benefit the group as a whole.
Indeed one of the benefits of access to multiple cultures in pluralistic, multicultural societies is the ability to create new approaches by learning, borrowing, copying from each other and other cultures. We should do more of that.
3. Cultural evolvability helps explain levels of entrepreneurship. Cultural evolvability requires doing something different. Most new businesses fail & the willingness to take a risk depends on personal and population-level costs and benefits.
A. personal cost of deviation: many deviations will result in lower payoffs than following the majority trait. If it were obvious how to do better, most of the population would already use the better strategy. Tolerating diversity in traits, thus, means tolerating failure.
Reducing cost of failure increases entrepreneurship: bankruptcy laws, social safety nets, rich parents – a child with parents in the top 1% income distribution is 10 times more likely to be an inventor than a child born below the median, controlling for measures of ability.
B. population-level benefit of deviation. In a large economy with a large customer base comes large rewards for large innovations – the few winners can win bigger. Amazon can make more money in the United States than in Australia. Here’s a great video of Bezos describing his vision back in 1997:
C. Who pays the cost and who benefits from the innovation at a population-level, a function of the scale of cooperation. Even if at an individual-level the benefits of entrepreneurship don’t outweigh costs, they may do so at a population-level.
Silicon Valley offers an example. For every Apple & Amazon, there are 1000s of start-ups that have failed – most start-ups fail & the overwhelming majority never receive funding (114) – ‘unicorns’ are called unicorns for a reason. But the few successes pay for the failures.
4. Cultural evolvability prevents polarization & cultural speciation. Harshly punishing minor deviations increases extremism. If you’re harshly punished anyway, may as well take the extreme position. If there weretolerance for diverse view points, I’d moderate my position.
Model and results also inform debates on freedom of speech, predicting large sanctions for small deviations may encourage a divided society. By corrolary tolerating multicultural diversity of opinions and cultural traits may prevent polarization.
Cultural clustering complicates everything, but I’ll let you read about that in the paper. It gets into colonialism, resource competition, and intergroup violence. 50/ To conclude, diversity has been central to the success of all life. Until around 1.2 billion years ago the source of that diversity was mutation – genetic innovation through serendipity and incremental improvement alone. Single cells reproducing by simple replication.
Sex unlocked the recombinatorial power of diversity, increasing evolvability and the speed of evolution. So too with culture, but there are many barriers to cultural traits meeting and recombining.
We live in an increasingly connected & multicultural world. Migration is a constant feature of the human story, but since the Age of Mass Migration, more people from more culturally distant societies live side by side. Their countries of origin must coordinate as never before.
So much human potential is lost through unequal access to information and adaptive cultural traits. The goal of any society or org should be to reap the benefits of diversity and minimize the costs, thereby maximizing human potential. We discuss several strategies.
Humans are a deeply cooperative species. Our greatest achievements and our worst atrocities are both cooperative acts. In a more diverse world, the challenge is greater, so too are the potential gains.
Considering the limitations of psychology today, I discussed ways in which we can move beyond WEIRD (Western, Educated, Industrialized, Rich, and Democratic) psychology in a global collaborative manner and strengthen the links between basic and applied policy research. I also discussed the importance of historical psychology.
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!
This year’s Diverse Intelligences Summer Institute was held online due to the pandemic. I delivered a lecture over Zoom on “What affects our level of intelligence?” followed by a lively discussion with the students. The lecture discussed brain evolution, the Cultural Brain Hypothesis, collective brain, and a cultural evolutionary account of intelligence. You can watch it below:
I spent the last week back at Harvard University discussing research on cultural evolution and innovation with the Learning Innovations Laboratory (LILA), part of Project Zero at the Harvard Graduate School of Education. The LILA group include people from industry and the military. Every year the group invites two academics to discuss their research and how it might be applied to problems faced by members of the group. This year, Mary Ann Glynn and I were invited. It was an intellectually enriching opportunity to apply my work to current challenges in corporations and other organizations.
The ideas presented in my two talks were beautifully captured in the graphics below:
The Science of Cultural Evolution: What Makes Humans So Different
Sources of Innovation: The Secret of Human Success
I spent the last couple of days at a small conference on cumulative culture organized by Claudio Tennie and his two PhD students Elisa Bandini and Eva Reindl. The theme was “When and How does Cumulative Culture Emerge”. It was an excellent meeting – large enough to have a diversity of views, small enough to have interesting conversations with almost all participants.
To very briefly summarize, innovation is often assumed to be an individual endeavor driven by geniuses and then passed on to the masses. Consider Thomas Edison and the lightbulb or Gutenberg and the printing press. We argue that rather than a result of far-sighted geniuses, innovations are an emergent property of our species’ cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains.
Innovations, large or small, do not require heroic geniuses any more than your thoughts hinge on a particular neuron.
We argue that rates of innovation are heavily influenced by:
transmission fidelity, and
We discuss some of the forces that affect these factors. These factors can also shape each other. For example, we provide preliminary evidence that transmission efficiency is affected by sociality—languages with more speakers are more efficient.
We argue that collective brains can make each of their constituent cultural brains more innovative. This perspective sheds light on traits, such as IQ, that have been implicated in innovation. A collective brain perspective can help us understand otherwise puzzling findings in the IQ literature, including group differences, heritability differences, and the dramatic increase in IQ test scores over time.