🚨New paper (& #RStats pckg) in Psych Methods: “Parsimony in Model Selection: Tools for Assessing Fit Propensity” w/ Carl Falk
Say you have 2 theories rep in 2 stats models. Which theory/model is correct? The one that best fits the data right?
Ok, but what about parsimony?
Occams razor: given 2 equally ﬁtting models, all else being equal pick the simpler / more parsimonious, model. But how do you quantify parsimony?
Some researchers equate parsimony with degrees of freedom, but as we show you can have fewer parameters, but less parsimony.
Another way to think about it is what Kris Preacher called “fit propensity”. Some models may ﬁt the given data better not because they represent a more correct theory, but because they would fit any data better. Even nonsensical data. It’s the opposite of parsimony.
Incidentally, the context for this research is the theory crisis and the importance of formalizing theory, even if in a statistical model. More here:
New paper: we argue that the replication crisis is rooted in more than methodological malpractice and statistical shenanigans. It’s also a result of a lack of a cumulative theoretical framework: & (nature.com/articles/s4156…)(muth.io/theory-nhb)
Back to fit propensity.
Fit propensity is often ignored in model selection. Perhaps because the answer to “how do we assess fit propensity?” has been “not easily”. In this paper, we fix that.
We offer a toolkit and 5 step process for researchers to assess parsimony of SEMs using an R package (ockhamSEM).
Basic idea: generate random data (or constrained random data, e.g. only positive) as covariances and see which model fits better in this universe of nonsense.
So in the opening model, using standard model selection approach, you might conclude that 2A is a better model than 1A. 2A has a lower AIC so it’s the best theory for generating the data, etc. But you’d have ignored that 2A lacks parsimony.
2A fits a wider range of data better – even nonsense.
Between these models, you might think the factor model is a better fit than the simplex model, but it lacks parsimony – much more so if the data are all positive covariances!
To show some of the complexities of considering parsimony, we investigate the factor structure of the Rosenberg Self-Esteem Scale.
Spoiler: fit indices interact with fit propensity.
The fifth Future of Government Disruptive Debate hosted by the World Bank tackles the issue of citizens’ trust in government. Together with a diverse group of high-profile practitioners, renowned experts, and thought leaders, I discuss how the natural state of affairs is corruption and the challenges government face in getting citizens to trust higher levels of cooperation.
My opening remarks can be found from 7:12 to 14:07 in the recording above. A rough summary of my talk can be found on my substack: https://muthukrishnalab.substack.com/p/trust-governance-and-cultural-evolution
The fifth Future of Government Disruptive Debate will tackle the issue of citizens’ trust in government. The Disruptive Debate series aims is to bring together a diverse group of high-profile practitioners, renowned experts and thought leaders to generate new knowledge and perspectives.
The issue of trust has been a frequent theme arising during the Disruptive Debate series. The panel addressed questions such as: Why is trust important for poverty reduction and shared prosperity? What is the relationship between inequality and trust? What can governments do to increase, or re-build, trust? How can citizens influence and hold governments to account? What has been the role of information, data and social media, particularly during COVID-19?
Some quick background: Religions bind people into communities with moral norms about what is right, good, & true. Ever notice that major world religions seem to have some broad stroke similarities like big families and being nice to neighbors? Why is that?
One hypothesis is that having those helped those religions grow in the competition with other religions. Not all religions in history share these features. The Shakers, for example, an offshoot of the Quakers, practiced celibacy not just for a priestly class, but for all.
The Shakers are no longer with us.
But religions also have plenty of differences, not only in explicitly religious beliefs, but in broader cultural values that affect national culture. Jesuits and Mainline Protestants, for example, historically increased levels of education. And Protestant values may help explain America’s traditionalism, individualism, and moralization of work. Religions are also shaped by national culture, taking on regional forms. Here’s a buff, Korean Jesus:
Some have also argued that “religion” is mostly a label or an identity, swamped by national culture – think nominal Christians. Or religion may just predict overtly religious beliefs, rituals, and moral attitudes.
For the cultural-group selection theory to work, major world religions should be “super-ethnic” identities, binding people beyond their ethnicity or national borders. That is, those who share a religion living in different countries should be more similar to those who don’t share the religion.
Using a new method for measuring cultural distance called the Cultural Fixation Index (CFst; read more about it here: https://michael.muthukrishna.com/beyond-weird-psychology-measuring-and-mapping-scales-of-cultural-and-psychological-distance/), we looked at cultural distance between major world religions in the World Values Survey. What did we find?
CFst are large enough to have competition between distinct cultural-groups of cultural traits, even if you remove overtly religious beliefs. The “People of the Book”—Christian, Muslim, and Jewish people—share cultural similarities. Christians are about as culturally similar to both Jewish and Muslim people as Americans are to Canadians or Australians are to Brits. But just as the United States is similarly geographically distant from Uruguay and Ukraine, but Uruguay and Ukraine are not geographically close to each other, Jewish and Muslim people are a similar cultural distance as people in the United States and the Philippines.
You can take a look at national cultural distance with this app: https://world.culturalytics.com/
As a side note, Buddhists are interesting. They look like Hindus, as fellow Dharmist, but also like Christians, Muslims & Jews.
But of course, these broad generalizations hide a lot of cultural clustering within countries. Fellow citizens more culturally similar than co-religionists in a different country, but foreigners who share a religion are more similar than those of a different religion. And that similarity is stronger if they’re highly religious.
And this broad generalization was true in our data even for places we didn’t expect. Like Muslims in India and Pakistan.
All of this holds true controlling for religious freedom, geographic, linguistic, & genetic distance.
We also looked at the interaction between national and religious culture, showing that non-American Christians are most similar to Americans. America is still a very Christian country and Christianity might therefore be considered the WEIRDest religion (using America as a proxy for WEIRD). That’s consistent with Joe Henrich’s hypothesis for the role of Christianity in creating WEIRD psychological and cultural traits: https://en.wikipedia.org/wiki/The_WEIRDest_People_in_the_World
And finally, non-Americans with no religious denomination are also similar to Americans without religious traits. That’s consistent with other work showing that the US looks like other secular, developed nations except when it comes to traditional religious values.
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.
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.
In an age of social media ’cancel culture’ might be defined as an orchestrated campaign that seeks to silence or end the careers of people whose thoughts or opinions deviate from a new set of political norms. So if this threat exists for anyone expressing an opinion online in 2021, what’s it like for scientists working in academia and publishing findings that might be deemed controversial?
In this edition of Analysis, I assess the impact of modern social justice movements on scientific research and development.
Is fear of personal or professional harm strengthening conformism or eviscerating robust intellectual debate? Can open-mindedness on controversial issues really exist in the scientific community? Or is rigorous public assessment of scientific findings helping to achieve better, more equitable and socially just outcomes?
So many great points I wish could have all been included from the interviewees who have found themselves in the firing line of current public discourse or who question the severity of this phenomenon and its political motives (in order of appearance):
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 am honored to be among this year’s SAGE Early Career Trajectory Award recipients. This Society for Personality and Social Psychology (SPSP) award recognizes scholars in the early stages of their professional careers that contribute to advancing the boundaries of personality and social psychology. Many thanks to my amazing mentors who have supported me over the years and continue to inspire me!
Ted Slingerland, M. Willis Monroe, and I were awarded a John Templeton Foundation grant for The Database of Religious History: “Exploring the Cultural Evolution of Religion Employing a Large-Scale, Quantitative-Qualitative Historical Database” ($4,792,151). The grant will take us through to 2023.
We will be hiring several new postdocs to expand the time depth, geographic range, and domains of data collection efforts. If you notice your area of expertise missing from our dataset, please reach out. Otherwise, stay tuned for job ads.
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!
We review interdisciplinary evolutionary psychology that takes seriously both our primate heritage and our uniquely cultural nature – a “cultural evolutionary psychology”. Why, how, when, and on which things do different humans work together?
Humans in all societies cooperate far more than other mammals. We’re more prosocial than nonhuman primates who often look like rational choice models (these models are like Hardy-Weinberg models – null models without the effect of evolving norms & other culture).
A more complete explanation needs to explain scale, intensity, and domain differences between societies-people cooperate on different things to different degrees. Need to explain the scaling up in the last 12k years. And that many mechanisms can support maladaptive behav.
Explanations like language, intelligence, & institutions are insufficient. We can use language to lie, our cognitive abilities to cheat, & institutions can be undermined by lower scales of cooperation. Where did these come from anyway? See the cultural brain hypothesis & the collective brain. Also summarized in this lecture:
Social norms and institutions – their origins and evolution is key to explaining the 4 features / puzzles of human cooperation mentioned before.
Some key concepts and behavioral experiments in cooperation.
Social norms shape cooperation, differ b/w societies, kids copy adults. Fairness is not the same everywhere – e.g. inequity aversion is not universally symmetric. We don’t like when things are unequal and we have less, but folks differ on unequal where they have more.
We review key mechanisms in broad strokes: kin-based, direct reciprocity, reputation, punishment, signaling. Origins of institutions. WEIRD intuitions are not a good guide – take partner choice for example.
So you have societies with different norms & sustained by different mechanisms of cooperation. Which ones spread? Competiton w/ sufficient resources can favor higher scales, but lower scales can undermine higher scales – corruption or autocracy or insurrection etc. Need alignment between levels.
The mechanisms of cooperation discussed are not alternatives to this competition. They are solutions to the free-rider problem with limits on scale and that can undermine one another. You also need to solve the equilibrium selection problem.
Social norms can create selection pressure on genes, they can self-domesticate. Institutions as connected and sometimes formalized social norms can create interdependence and fusion. They can align interests.
We end by revisiting the opening challenges. Check out the paper here:
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