I was invited to present my work on Corruption, Cooperation, & the Evolution of Prosocial Institutions at LSE-Stanford Conference on Long-Run Development in Latin America. This year’s conference was hosted at the London School of Economics.
I spent the last week in Erice, Sicily, Italy at the Future Directions on the Evolution of Rituals, Beliefs, and Religious Minds workshop at The Ettore Majorana Foundation and Centre for Scientific Culture. Edward Slingerland and I presented “Durkheim with Data: The Database of Religious History”. I focused on some analyses using Database of Religious History data.
The conference included several excellent discussions at the cutting edge of the evolution and cognitive science of religion.
Other speakers and attendees included:
Scott Atran (Oxford University)
Jeanet Sinding Bentzen (University of Copenhagen)
Paul Bloom (Yale University)
Pascal Boyer (Washington University at St Louis)
Joseph Bulbulia (University of Auckland)
Russell Gray (Max Plank Institute for the Science of Human History
Joseph Henrich (Harvard University)
Cristine Legare (University of Texas at Austin)
Hillary Lenfesty (Arizona State University)
Robert McCauley (Emory University)
Ara Norenzayan (University of British Columbia)
Stefano Parmigiani (University of Parma)
Eleanor Power (London School of Economics and Political Science)
Colleen Shantz (University of Toronto)
Edward Slingerland (University of British Columbia
Jesper Sørensen (University of Aarhus)
Ann Taves (University of California, Santa Barbara)
Harvey Whitehouse (Oxford University)
Aiyana Willard(Oxford University)
David S. Wilson (Binghamton University)
Dimitris Xygalatas (University of Connecticut)
Ettore Majorana Foundation and Centre for Scientific Culture is famous for the 1982 Erice Statement.
PBS has a new 4-part documentary series on First Civilizations; a sequel to their successful series First Peoples. The new series charts the rise of civilization clustered around 4 topics: War, Religion, Cities, and Trade. I’m the key contributor for episode 3 on Cities, which premieres tonight. I travel through Tokyo, Japan discussing innovation, inequality, sociality, and collective brains. A short clip from the episode below:
You can read more about the research behind this episodes in these review papers (written to be accessible to the general reader):
Introduction to Cultural Evolution
|Chudek, M., Muthukrishna, M. & Henrich, J. (2015) Cultural Evolution. In Handbook of Evolutionary Psychology, 2nd Edition. Edited by D. M. Buss. [Download]|
Introduction to Collective Brains
|Muthukrishna, M. & Henrich, J. (2016). Innovation in the Collective Brain. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1690). [Telegraph] [Scientific American] [Video] [Evonomics] [LSE Business Review] [Summary Post] [Download]|
If you want to learn more, I recommend 3 recent books on the topic:
This week I was invited to speak at the Centre for Experimental Social Sciences (CESS), Nuffield College and Oxford University. I presented a talk on “Corruption, Competition & Scales of
Cooperation: Corruption is Rooted in our Relationships” based on my recent paper “Corrupting cooperation and how anti-corruption strategies may backfire” (more details).
I also discussed the general approach to understanding corruption using cultural evolution and the science of cooperation – corruption is one scale of cooperation undermining another. For example, nepotism is cooperation at the scale of kin, well explained by inclusive fitness, undermining cooperation at the scale of the formal institution. More on this framework can be found at ProMarket or Evonomics. Finally, I presented some work in progress based on this approach, including some work by my students.
Last week, my paper with Kieran Fox and Susanne Shultz was published in Nature Ecology and Evolution. The paper was a multiyear project, which consisted of countless hours spent poring through marine mammal literature to create the most comprehensive database of cetacean physiology, social structure, life history, and behavior to date. We then used this database to test some of the predictions of the Social Brain and Cultural Brain Hypotheses. Some of the confirmations of these predictions are shown in Figure 3 of the paper below.
Cetaceans represent a great test for the Social Brain and Cultural Brain Hypotheses (CBH), because of how evolutionarily alien these species are, and how strange their underwater world is compared to the world we inhabit. We have previously tested the CBH predictions with primates, but their evolutionary closeness to humans means that the relationships we find may be due to our evolutionary logic or due to these features (such as large brains and high sociality) being present in a common ancestor. Thus finding these relationships in cetaceans is strong evidence for the evolutionary logic. It also sets up cetaceans as an interesting control group for understanding human evolution.
The ongoing massive media response and public interest in marine mammals and the evolutionary sciences was heartwarming. Altmetrics suggested a score of 1026, in the top 5 of articles in Nature Ecology and Evolution, receiving the most attention of recent articles and top 50 of all articles of a similar age. Highlights included several video and audio interviews, including with BBC World News, BBC World Service Radio “Science in Action”, CBC “The Broadcast” (below), and the front page of the print edition of the The Times and front page of the website of The Guardian.
Selected Media Coverage
Scientific American (republished in January print edition of magazine)
Some unexpected places, including Cosmo 🙂
I chaired a themed session on “Cultural Evolution and Economics” at the Inaugural Cultural Evolution Society Conference. Speakers including myself, my student collaborator Xueheng Li, and Heidi Colleran. My PhD student, Ryutaro Uchiyama presented some new analyses on the Cultural Brain Hypothesis in a parallel session.
I presented a the “Cultural Evolution of Economics” with some illustrations on how cultural evolution can help economists and how economists can help those interested in cultural evolution. To illustrate this, I presented some recent and upcoming work on cooperation, corruption, democracy and economic growth. Abstract below:
Homo Economicus are extinct or on the verge of extinction, or so it would appear from outside economics. But within economics, reports of their death have been greatly exaggerated. Economicus’ persist, in part because alternative theories of human behavior are not readily integrated into existing economic approaches. To paraphrase Buckminster Fuller, criticism is not sufficient—you need to build a better model. I’ll discuss collaborations at the London School of Economics that are attempting to build that better model by integrating cultural evolutionary theory into economics. A cultural evolutionary approach seats corruption as a special case of cooperation, offering new means to understand and combat it (Muthukrishna, et al., 2017, “Corrupting Cooperation and How Anti-Corruption Strategies May Backfire”, Nature Human Behavior). A cultural evolutionary approach helps identify the invisible cultural pillars that support successful economic and democratic institutions (Stimmler & Muthukrishna, 2017, “When Cooperation Promotes Corruption and Undermines Democracy”, Working Paper; Muthukrishna, et al., in prep, “A WEIRD scale of cultural distance”). A cultural evolutionary approach reveals the relationship between economic growth, inequality, tolerance for inequality, and widespread beliefs—like “evil eye” and witchcraft—that have economic implications (Li & Muthukrishna, 2017, “The coevolution of Economic Growth, Inequality, Tolerance for Inequality, and Belief in Evil Eye”, Working Paper). These related studies reveal how cultural evolution may offer new approaches to age old problems, but also how the economic toolkit may be deployed to understand culturally evolved beliefs and behaviors.
Li presented an economic model and corresponding experimental test on the co-evolution of economic growth, inequality, tolerance for inequality and the widespread belief in “evil eye“.
All together a lot of fun and excellent talks by lots of familiar names and even more familiar faces. Many thanks to the Max Planck Institute for the Science of Human History, Russell Gray and the rest of the organizing committee: Andy Whiten, Fiona Jordan , Joe Brewer, Michele Gelfand, Michelle Kline, and Olivier Morin.
This month, my paper with Patrick Francois, Shayan Pourahmadi, and Joe Henrich was published in Nature Human Behaviour. Manfred Malinski did a great job summarizing and contextualizing some of the key findings. The key findings were:
- Introducing the possibility of bribes into an institutional punishment public goods game results in reduced contributions.
- In an institutional punishment public goods game, stronger leaders result in more cooperation. In our modified “bribery game”, stronger leaders result in less cooperation.
- Anti-corruption measures including transparency and tying leaders payoffs to the success of the public good result improve contributions, except if economic potential is low and leaders are weak. Here, they can actually further reduce contributions.
- Culture matters. Exposure to corrupt norms via living in corrupt places increases bribes, but having an ethnic heritage that includes corrupt countries, but not having actually lived there yourself results in less bribery.
Figures 1, 2 and 3, reproduced below illustrate these results.
Selected Media Coverage
Folha de S.Paulo (Brazil; Interview)
The Statesman (India)
Corruption is Rooted in Our Relationships
There is nothing natural1 about democracy. There is nothing natural about living in communities with complete strangers. There is nothing natural about large-scale anonymous cooperation. Yet, this morning, I bought a coffee from Starbucks with no fear of being poisoned or cheated. I caught a train on London’s underground packed with people I’ve never met before and will probably never meet again. If we were commuting chimps in a space that small, it would have been a scene out of the latest Planet of the Apes by the time we reached Holborn station. We’ll return to this mystery in a moment.
There is something very natural about prioritizing your family over other people. There is something very natural about helping your friends and others in your social circle. And there is something very natural about returning favors given to you. These are all smaller scales of cooperation that we share with other animals and that are well described by the math of evolutionary biology. The trouble is that these smaller scales of cooperation can undermine the larger-scale cooperation of modern states. Although corruption is often thought of as a falling from grace, a challenge to the normal functioning state—it’s in the etymology of the word—it’s perhaps better understood as the flip side of cooperation. One scale of cooperation, typically the one that’s smaller and easier to sustain, undermines another.
When a leader gives his daughter a government contract, it’s nepotism. But it’s also cooperation at the level of the family, well explained by inclusive fitness2, undermining cooperation at the level of the state. When a manager gives her friend a job, it’s cronyism. But it’s also cooperation at the level of friends, well explained by reciprocal altruism3, undermining the meritocracy. Bribery is a cooperative act between two people, and so on. It’s no surprise that family-oriented cultures like India and China are also high on corruption, particularly nepotism. Even in the Western world, it’s no surprise that Australia, a country of mates, might be susceptible to cronyism. Or that breaking down kin networks predicts lower corruption and more successful democracies (Akbari, Bahrami-Rad & Kimbrough, 2017; Schulz, 2017). Part of the problem is that these smaller scales of cooperation are easier to sustain and explain than the kind of large-scale anonymous cooperation that we in the Western world have grown accustomed to.
So how is it that some states prevent these smaller scales of cooperation from undermining large-scale anonymous cooperation? The typical answer is that more successful nations have better institutions. All that’s required is the right set of rules to make society function. But even on the face of it, this answer seems incomplete. If it were true, Liberia, who borrowed more than its flag from the United States, ought to be much more successful than it is4. Instead, these institutions are supported by invisible cultural pillars without which the institutions would fail. For example, without a belief in rule of law—that the law applies to all and cannot be changed on the whim of the leader—it doesn’t matter what the constitution or legal code says, no one is listening. Without a long time horizon, decisions are judged on how well they serve our immediate needs making larger-scale projects, like reducing the effects of Climate Change, harder to justify5. Similarly, institutions often lack the punitive power to actually punish perpetrators. For example, most people in the US and UK pay their taxes, even though in reality the IRS and Her Majesty’s Revenue and Customs lack the power to prosecute widespread non-compliance; your probability of getting caught is low. The tax compliant majority may never discover that they can cheat or how to get away with it (Chetty, et al. 2013) and they may not actively seek this information as long as the probability of getting caught is non-zero, the system seems fair, and it seems like everyone else is complying. Or in other words, it’s a combination of norms and institutions. But, it gets tricky—institutions are themselves hardened or codified norms6 and the norms themselves evolve in response to the present environment and due to path-dependence of previous environments, past decisions, and the places migrants come from. Modern groups vary on individualism (Talhelm, et al., 2014) and even sexist attitudes (Alesina, et al., 2013) based on their ancestors’ farming practices7. The science of cultural evolution describes the evolution of these norms and introduces the possibility of out-of-equilibria behavior (people behaving in ways that do not benefit them individually) for long enough for institutions to try to stabilize the new equilibria. For a summary of cultural evolution, see Joseph Henrich’s excellent book and for an even shorter summary see this chapter). How do we begin to understand these processes?
The real world is messy and before we start running randomized control trials or preparing case studies, it’s useful to model the basic dynamics of cooperation using a simpler form that gets at the core elements of the challenge. One commonly used model is called the “Public Goods Game”. The gist of the game is that I give you, and say 9 others, $10. Whatever you put into a pool (the public good), I’ll multiply by say 3, but then I’ll divide the money equally regardless of contribution. This is similar to paying your taxes for public goods that we all benefit from, like roads, clean water, or environmental protections. The dilemma is this: the best move is for everyone to put all their money in the pool. Then they’ll all go home with $30. But it’s in my best interests to put nothing in the pool and let everyone else put their money in. If I put in nothing and they put in $10 each, I’ll go home with almost $40 ($10*9*3people / 10 = $37). What happens when we play this game?
Well, if we play it in a WEIRD8 nation, where prosocial norms tend to be higher, people put about half their money in, but as they gradually realize they can make more by putting in less, contributions dwindle to zero. One way to sustain contributions is to introduce peer punishment—allow people to spend some portion of their money to punish other people. This is similar to the kind of punishment we might see in a small village. I know who you are or at least I know your parents or people you know. If you steal my crops, I’ll punish you myself or ruin your reputation. In the game, if we introduce the possibility of peer punishment, contributions rise again. The problem is that this doesn’t scale well. As the number of people grows, we get second-order free-riding—people prefer to let someone else pay the cost of punishment. When someone cuts a queue, you grumble—someone ought to tell that person off! Someone other than me… And you can also get counter-punishment—revenge for being punished. The best solution seems to be to create a punishment institution. Pick one person as a “Leader” and allow them to extract taxes that can be used to punish free-riders. This works really well and scales up nicely. It’s similar to a functioning police force and judiciary in WEIRD nations. In fact, the models suggest that the more power you give to the leader, the more cooperation they can sustain. Aha! Problem solved. Not quite. Models like these are very useful for distilling the core of a phenomenon, they can miss things. Recall where we started—smaller-scales of cooperation can undermine the larger-scale.
In our recently published paper, we wanted to show just how easy it was to break that well-functioning institution. We did it by introducing the possibility of another very simple form of cooperation—you scratch my back, I’ll scratch yours—bribery. And then we wanted to show the power of invisible cultural pillars by measuring people’s cultural background and by trying to fix corruption using common anti-corruption strategies. We wanted to show that these strategies, including transparency, don’t work in all contexts and can even backfire.
Our “Bribery Game” was the usual institutional punishment public goods game with the punishing leader, but with one additional choice—players could not only keep money for themselves or contribute to the public pool, they could also contribute to the leader. And the leader could not only punish or not punish, they could instead accept that contribution. What happened? On average, we saw contributions fall by 25% compared to the game without bribery as an option. More than double what the pound has fallen against the USD since Brexit (~12%9). Fine, bribery is costly. The World Bank estimates $1 trillion is paid in bribes alone; in Kenya, 8 out of 10 interactions with public officials involves a bribe, and as Manfred Milinski points out in his summary of our paper, most of humanity—6 billion people—live in nations with high levels of corruption. Our model also reveals that unlike the typical institutional punishment public goods game, where stronger institutions mean that more cooperation can be sustained, when bribery is an option, stronger institutions mean more bribery. A small bribe multiplied by the number of players will make you a lot richer than your share of the public good! So can we fix it?
The usual answer is transparency. There are also some interesting approaches, like tying a leader’s salary to the country’s GDP—the Singaporean model10. So what happened when we introduced these strategies? Well, when the public goods multiplier was high (economic potential—potential to make money using legitimate means—was high) or the institution had power to punish, then contributions went up. Not to levels without bribery as an option, but higher. But in poor contexts with weak punishing institutions, transparency had no effect or backfired. As did the Singaporean model11. Why? Consider what transparency does. It tells us what people are doing. But as psychological and cultural evolutionary research reveals, this solves a common knowledge problem and reveals the descriptive norm—what people are doing. For it to have any hope of changing behavior, we need a prescriptive or proscriptive norm against corruption. Without this, transparency just reinforces that everyone is accepting bribes and you’d be a fool not to. People who have lived in corrupt countries will have felt this frustration first hand. There’s a sense that it’s not about bad apples—the society is broken in ways that are sometimes difficult to articulate. But societal norms are not arbitrary. They are adapted to the local environment and influenced by historical contexts. In our experiment, the parameters created the environment. If there really is no easy way to legitimately make money and the state doesn’t have the power to punish free-riders, then bribery really is the right option. So even among Canadians, admittedly some of the nicest people in the world, in these in-game parameters, corruption was difficult to eradicate. When the country is poor and the state has no power, transparency doesn’t tell you not to pay a bribe, it solves a different problem—it tells you the price of the bribe. Not “should I pay”, but “how much”?
There were some other nuances to the experiment that deserve follow up. If we had played the game in Cameroon instead of Canada, we suspect baseline bribery would have been higher. Indeed, people with direct exposure to corruption norms encouraged more corruption in the game controlling for ethnic background. And those with an ethnic background that included more corrupt countries, but without direct exposure were actually better cooperators than the 3rd generation+ Canadians. These results may reveal some of the effects of migration and historical path dependence. Of course, great caution is required in applying these results to the messiness of the real world. We hope to further investigate these cultural patterns in future work. The experiment also reveals that corruption may be quite high in developed countries, but its costs aren’t as easily felt. Leaders in richer nations like the United States may accept “bribes” in the form of lobbying or campaign funding and these may indeed be costly for the efficiency of the economy, but it may be the difference between a city building 25 or 20 schools. In a poor country similar corruption may be the difference between a city building 3 or 1 school. Five is more than 3, but 3 is three times more than 1. In a rich nation, the cost of corruption may be larger in absolute value, but in a poorer nation, it may be larger in relative value and felt more acutely.
The take home is that cooperation and corruption are two sides of the same coin; different scales of cooperation competing. This approach gives us a powerful theoretical and empirical toolkit for developing a framework for understanding corruption, why some states succeed and others fail, why some oscillate, and the triggers that may lead to failed states succeeding and successful states failing. Our cultural evolutionary biases lead us to look for whom to learn from and perhaps whom to avoid. They lead us to blame individuals for corruption. But just as atrocities are the acts of many humans cooperating toward an evil end, corruption is a feature of a society not individuals. Indeed, corruption is arguably easier to understand than my fearless acceptance of my anonymous barista’s coffee. Our tendency to favor those who share copies of our genes—a tendency all animals share—lead to both love of family and nepotism. Putting our buddies before others is as ancient as our species, but it creates inefficiencies in a meritocracy. Innovations are often the result of applying well-established approaches in one area to the problems of another. We hope the science of cooperation and cultural evolution will give us new tools in combating corruption.
1 Putting aside what it means for something to be natural for our species, suffice to say these are recent inventions in our evolutionary history, by no means culturally universal, and not shared by our closest cousins.
2 Genes that identify and favor copies of themselves will spread.
3 Helping those who help you.
4 The United Nations Human Development Index ranks the United States 10th in the world. Liberia is 177th.
5 Temporal discounting the degree to which we value the future less than the present. Our tendency to value the present over the future is one reason we don’t yet have Moon or Mars colonies, but the degree to which we do this varies from society to society.
6 Written laws can serve a signaling and coordination function; rather than having to interpret norms from the environment. When previously contentious norms are sufficiently well established, you may do well to codify them in law (legislating before they are established might mean more punishment—consider the history of prohibition in the United States).
7 Not that agriculture is the main reason for these cultural differences!
8 Western Educated Industrialized Rich Democratic
9 This doesn’t upset me at all 😐.
10 Singapore’s leaders are the highest paid in the world, but the nation also has one of the lowest corruption rates in the world—lower than the Netherlands, Canada, Germany, UK, Australia, and United States [source].
11 Note, there are some conceptual issues that make interpretation of the Singaporean treatment ambiguous. We discuss this in the supplementary. We’ll have to further explore this in a future study. Such is science.
~$2.4 million Templeton Foundation Grant for The Database of Religious History: A Digital Humanities Approach to Religious Cultural History
Ted Slingerland and I were awarded a Templeton Foundation grant for “The Database of Religious History: A Digital Humanities Approach to Religious
Cultural History” ($2,342,841). The grant will take us through to 2020, by which time we hope to have set up the project as a foundation.
If you’re a historian, please let us know if you would like to contribute. For everyone else, I encourage you to browse through our data: http://religiondatabase.org/browse/landing/
I was recently interviewed by Focus Magazine, a popular magazine in the Russian-speaking world. It was a wide-ranging interview, where we discussed my research on cultural evolution and the implications for some of the events taking place in the world today, including the Migration Crisis, climate change, and the rise of populist politicians.
The first part was a brief introduction to the science of cultural evolution: https://focus.ua/society/367070/
The second part dealt with contemporary societal-level implications: https://focus.ua/society/367860/
I gave a keynote presentation at the Lorentz Center conference on “Trusting and the Law“. This was my first legal conference. The audience included judges, lawyers, and legal scholars. I presented a talk on “Economic Psychology and the Science of Cultural Evolution”, where I discussed some of the “invisible cultural pillars” that uphold legal institutions. It was fascinating to discuss differences in the approach to “evidence” in science and the law.
I was invited to present my work on innovation and cultural evolution at the “Cultural Transmission and Social Norms Workshop” hosted by the School of Economics at The University of East Anglia, UK. I presented “Innovation in the Collective Brain: The Transmission and Evolution of Norms and Culture”, beginning with an introduction to cultural evolution for the audience of primarily economists. I then discussed innovation as a product of our “collective brains“.
|Muthukrishna, M. & Henrich, J. (2016). Innovation in the Collective Brain. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1690). [Telegraph] [Scientific American] [Video] [Evonomics] [LSE Business Review] [Summary Post] [Download] [Data]|
On Thursday, I was at the Council of Graduate Schools (CGS) Annual Meeting in Washington, DC to receive this year’s CGS/ProQuest Distinguished Dissertation Award in the Social Sciences. The award ceremony was held in the Regency Ballroom of the beautiful Omni Shoreham. The press release with more details can be found here: http://www.proquest.com/about/news/2016/Winners-of-2016-CGS-ProQuest-Distinguished-Dissertation-Awards.html.
It was an unexpected honor, but also validation of my research agenda and approach to science. My acceptance speech was a brief summary of my dissertation and Dual Inheritance Theory and Cultural Evolution more generally.
Templeton Foundation Grant for The Database of Religious History: Data Science Approaches to Religious Cultural History ($215K; 18 months)
I was recently awarded an 18 month grant (with Co-PI Ted Slingerland) for “The Database of Religious History: Data Science Approaches to Religious Cultural History” ($215, 050). The grant will enable us to continue a critical period in the project’s development. We are hoping to secure additional funds to ensure a self-sustaining future for the project.
Part of this period was improving the data entry and browsing interface. If you’re a historian, please let us know if you would like to contribute. For everyone else, I encourage you to browse through our data: http://religiondatabase.org/browse/landing/
I was invited to present my work on human evolution and the evolution of brains at the “Evolution of cognition and longevity: Adaptation to a new technological environment” meeting at the Grande Galerie de l’Evolution, National Museum of Natural History in Paris, France. I presented “The Cultural Brain Hypothesis & Information Grandmother Hypothesis: How culture drives brain expansion and alters life history”, where I discussed the Cultural Brain Hypothesis (my dissertation; paper currently under review). I also presented some work in progress on the Information Grandmother Hypothesis.
The Cultural Brain Hypothesis is a more parsimonious explanation for the relationships that have been shown between brain size, group size, adaptive knowledge, social learning, and aspects of life history. The Cumulative Cultural Brain Hypothesis is a set of predictions derived from the evolutionary processes that lead to these relationships for the conditions that lead to an autocatalytic take-off between brain size and adaptive knowledge – the uniquely human pathway. The Information Grandmother Hypothesis extends this theory to explain the evolution of menopause and lifespan.
Speakers were biologists of all kinds. Speakers included:
Herve Chneiweiss (UPMC)
Barbara Demeneix (MNHN)
Donata Luiselli (University of Bologna)
Jean-Marie Robine (GDR INSERM/EPHE)
Kaare Christensen (Danish Aging Research Center)
Eline Slagboom (Leiden University Medical Center)
Claudio Franceschi (University of Bologna)
David Hill (University of Edinburgh)
Paolo Garagnani (University of Bologna)
Eileen Crimmins (USC Davis School of Gerontology)
Dorly Deeg (VU University, Amsterdam)
Carol Brayne (CFAS)
Carole Dufouil (INSERM)
Dominique Grimaud-Herve (MNHN)
David Raichlen (University of Arizona)
Viviane Slon (Max Planck Institute for Evolutionary Anthropology)
James R Carey (UC Davis)
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
SPSSI-UK organized a symposium on the Migration Crisis. The symposium was attended by an array of social scientists, but also policy makers, impact officers, and community organizers. I presented some work in progress on “The Paradox of Diversity, Migration, and Cultural Evolution in Europe”. My talk briefly introduced the science of cultural evolution (for a quick intro, see Cultural Evolution), the implications of cultural evolutionary theory for managing the migration crisis, and some results from a new tool I’ve been building to better quantify the size and dimensions of cultural differences.
More on this “Cultural Distance” tool soon.
The outcome of the discussions will also be released by SPSSI-UK as a white paper (in prep).
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.
Other speakers and attendees included:
Carel van Schaik (University of Zurich)
Christine Caldwell (University of Stirling)
Pete Richerson (UC Davis)
Helena Miton (Central European University)
Rachel Kendal (Durham University)
Olivier Morin (Max Planck Institute for the Science of Human History)
Mathieu Charbonneau (Central European University)
Andrew Buskell (London School of Economics)
Alex Mesoudi (University of Exeter)
Rachel Harrison (University of St Andrews)
Takao Sasaki (Oxford)
Celia Heyes (Oxford)
Elena Miu (University of St Andrews)
Julie Coultas (University of Sussex)
Keith Jensen (University of Manchester)
Thibaud Gruber (University of Geneva)
I spent the weekend at a productive interdisciplinary workshop on “Religion, Ritual, Conflict, and Cooperation: Archaeological and Historical Approaches” at the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford University. CASBS is located on the top of one of the beautiful hills around Stanford.
We discussed the challenges and successes in inferring religious belief and practice from the archeological and historical record and new theoretical models and tools for exploring religious history, including the Database of Religious History (DRH).
Other attendees included:
David Carballo (Boston University)
Chris Carleton (Simon Fraser University)
Jesse Chapman (Stanford University)
Mark Csikszentmihalyi (UC Berkeley)
Megan Daniels (Stanford University)
Russell Gray (Director, Max Planck Institute for the History and the Sciences)
Conn Herriott (University of Jerusalem)
Ian Hodder (Stanford University)
Joseph Manning (Yale University)
Jessica McCutcheon (University of British Columbia)
Frances Morphy (Australian National University)
Howard Morphy (Australian National University)
Ian Morris (Stanford University)
Ara Norenzayan (University of British Columbia)
Beate Pongratz-Leisten (NYU)
Neil Price (Uppsala)
Benjamin Purzycki (University of British Columbia)
Ben Raffield (Simon Fraser University)
Katrinka Reinhart (Stanford University)
Celia Schultz (University of Michigan)
Edward Slingerland (University of British Columbia)
Charles Stanish (UCLA)
Brenton Sullivan (Colgate College)
Edward Swenson (University of Toronto)
Robban Toleno (University of British Columbia)
Robyn Walsh (University of Miami)
Joseph Watts (University of Auckland)
Last week, my paper with Joe Henrich on “Innovation in the Collective Brain” was published in Philosophical Transactions of the Royal Society B: Biological Sciences. I explain some of the key points in the video below:
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.
The paper outlines how many human brains, which evolved primarily for the acquisition of culture, together beget a collective brain. Within these collective brains, the three main sources of innovation are:
- recombination, and
- incremental improvement.
We argue that rates of innovation are heavily influenced by:
- transmission fidelity, and
- cultural variance.
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.