Public health

Public health initiatives are sometimes at odds with local culture and traditions (Cloward, Reference Cloward2016). Policy to improve public health may thus be subject to a backlash and non-compliance by at least some parts of the population. Female genital cutting (FGC) is one such example (World Health Organisation, 2008). The conflict is that from the perspective of universal human rights, FGC is harmful to the health and well-being of women but legislation to ban it would interfere with local cultural traditions.

FGC is still pervasive in many countries. For example, in Egypt, UNICEF estimates suggest that 87% of females between 15 and 49 years of age are cut (based on data from 2004 to 2015; UNICEF, 2016). Current approaches to eradicate FGC practices often fail. In some cases, exogenous attempts to change behaviour are perceived as intrusions that impose out-group values, leading to a backlash in the local population (Shell-Duncan & Hernlund, Reference Shell-Duncan and Hernlund2000; Gruenbaum, Reference Gruenbaum2015; Camilotti, Reference Camilotti2016; Vogt et al., Reference Vogt, Mohmmed Zaid, El Fadil Ahmed, Fehr and Efferson2016). That is, when attempts to reduce FGC are perceived as external, FGC rates can increase because not cutting girls is seen as Westernization and cutting girls becomes an ingroup ethnic marker (Cloward, Reference Cloward2016). Resolving the conflict between cultural sensitivity and female public health remains a challenge.

Policy interventions in this realm are often informed by the hypothesis that FGC, similar to foot binding, involves coordination incentives for families (Mackie, Reference Mackie1996; Efferson et al., Reference Efferson, Vogt, Elhadi, Ahmed and Fehr2015). That is, families with sons want cut wives because FGC is perceived as a sign of fidelity, tradition and becoming a good mother. And so, families with daughters choose to cut their daughters to increase the chances of finding a good spouse, sometimes regardless of personal preferences. In a population where families with sons favour uncut wives, families with daughters may choose to coordinate their decision and not cut their daughters (Cloward, Reference Cloward2016). How can a policymaker switch a population from the maladaptive (cutting) to the adaptive (not cutting) equilibrium?

One tantalizing possibility is behavioural change through endogenous spillovers by affecting a social tipping point (Nyborg et al., Reference Nyborg, Anderies, Dannenberg, Lindahl, Schill, Schluter, Adger, Arrow, Barrett, Carpenter, Chapin, Crepin, Daily, Ehrlich, Folke, Jager, Kautsky, Levin, Madsen, Polasky, Scheffer, Walker, Weber, Wilen, Xepapadeas and de Zeeuw2016; Andreoni et al., Reference Andreoni, Nikiforakis and Siegenthaler2021). That is, could a policymaker run a minimal intervention with selective targets that then starts a chain reaction within the population tipping them from a cut equilibrium to an uncut equilibrium? Here, the policymaker can focus attention and resources on persuading just enough of the right people until the social tipping point is reached, and then the endogenous social influence mechanisms, such as conformity take over with people coordinating around the new social norm.

Formalizing this policy possibility, Efferson et al. (Reference Efferson, Vogt and Fehr2020) developed a cultural evolutionary model informed by their previous empirical research (Efferson et al., Reference Efferson, Vogt, Elhadi, Ahmed and Fehr2015; Vogt et al., Reference Vogt, Mohmmed Zaid, El Fadil Ahmed, Fehr and Efferson2016, Reference Vogt, Efferson and Fehr2017), that captures the cultural evolutionary dynamics of harmful traditions. They model how behaviour spreads in a population via social influence after the population has been shocked by an external policy intervention. They show that the effectiveness of the policy, both in its size and target, depends on the distribution of attitudes in the population. An intervention will have a direct effect and an indirect effect (see Figure 2).

Figure 2. The direct and indirect effect of an intervention (adapted from Schimmelpfennig et al. (Reference Schimmelpfennig, Vogt, Ehret and Efferson2021)).

Perhaps counterintuitively, the results show that in a scenario where many in the population are resistant to the policy, policy makers can maximize the total effect of their policy by targeting not those most likely to change, but those most resistant to the policy (Efferson et al., Reference Efferson, Vogt and Fehr2020; Schimmelpfennig et al., Reference Schimmelpfennig, Vogt, Ehret and Efferson2021). Convincing those resistant to change through an intervention – perhaps one that exploits social learning biases (Kendal et al., Reference Kendal, Boogert, Rendell, Laland, Webster and Jones2018) – leaves the comparably ‘easy’ cases for the endogenous spillovers via social learning.

Efferson et al. argue that in scenarios where attitudes cannot be estimated, for example, because of concerns around social desirability of the response data (Krumpal, Reference Krumpal2013), policymakers may instead opt to target a random sample, such as through ‘edutainment’ (Vogt et al., Reference Vogt, Mohmmed Zaid, El Fadil Ahmed, Fehr and Efferson2016), rather than the most compliant, which may otherwise lead to polarization. This work may complement other behavioural and evolutionary approaches to public health (Gibson & Mace, Reference Gibson and Mace2006; Lawson et al., Reference Lawson, James, Ngadaya, Ngowi, Mfinanga and Mulder2015; Wells et al., Reference Wells, Nesse, Sear, Johnstone and Stearns2017; Arnot et al., Reference Arnot, Brandl, Campbell, Chen, Du, Dyble, Emmott, Ge, Kretschmer, Mace, Micheletti, Nila, Peacey, Salali and Zhang2020; Gelfand et al., Reference Gelfand, Li, Stamkou, Pieper, Denison, Fernandez, Choi, Chatman, Jackson and Dimant2022), representing the cutting-edge of integration of cultural evolutionary theory and policy interventions, whose success and value will be known over the coming decade.

Corruption

A common assumption is that corruption is a vice and cooperation is a virtue. Corruption harms economic development and creates barriers and inefficiencies to competition in a free market. Interventions and media campaigns, often unsuccessfully, focus on portraying corruption as malicious, harmful and unnatural. Cooperation, on the other hand, supports economic development and forms the backbone of democratic societies. But cooperation is no virtue in itself. Advances in technology and world wars, flourishing societies and genocides, our greatest achievements and our worst atrocities all require large-scale cooperation (Axelrod & Hamilton, Reference Axelrod and Hamilton1981; Henrich & Muthukrishna, Reference Henrich and Muthukrishna2021). From a cultural evolutionary perspective, corruption is also a cooperative act (Murray et al., Reference Murray, Frijters and Vorster2017; Muthukrishna et al., Reference Muthukrishna, Francois, Pourahmadi and Henrich2017).

It's natural to want to help relatives – well explained by theories of inclusive fitness – but doing so at the expense of impartial institutions is nepotism. It's natural to want to help friends, friends of friends or those in an exchange of some sort – well explained by theories of reciprocal altruism, direct and indirect reciprocity (see Yoeli et al. (Reference Yoeli, Hoffman, Rand and Nowak2013) for applications) – but doing so at the expense of impartial institutions is cronyism. Reducing corruption requires undermining lower scales of cooperation or aligning them with higher scales such that what's good for family and friends is also good for everyone else. Transparency alone can backfire when norms support lower scales of cooperation (such as expectations for favouring friends or family (Abbink, Reference Abbink and Rose-Ackerman2006; Murray & Frijters, Reference Murray and Frijters2016; Muthukrishna et al., Reference Muthukrishna, Francois, Pourahmadi and Henrich2017)). Similarly, theoretical work shows that the effectiveness of centralized punishment to combat corruption can break down when some actors can bribe the central authorities (Abdallah et al., Reference Abdallah, Sayed, Rahwan, LeVeck, Cebrian, Rutherford and Fowler2014). Indeed, many empirically derived anti-corruption strategies (e.g. Klitgaard et al., Reference Klitgaard, MacLean Abaroa and Parris2000), implicitly change incentives and or move people around to disrupt these cooperative ties.

An example of how smaller scales of cooperation were undermined and norms around kin-based small-scale cooperation have changed to support states is the Catholic Church's change to traditional large kin-network family structures through policies such as banning cousin marriage. This centuries-long program decreased the power of larger family clans, laying the foundations for large-scale societies supported by impartial institutions and what we now call WEIRD-psychology (e.g. individualism) (Schulz et al., Reference Schulz, Bahrami-Rad, Beauchamp and Henrich2019; Henrich, Reference Henrich2020). Places, where these kin ties remain, are dominated by tribalism, increased corruption and more fragile democratic institutions (Akbari et al., Reference Akbari, Bahrami-Rad and Kimbrough2019).

Developing policies that disrupt lower scales of cooperation and waiting half a millennium is not likely to sway policymakers, but the same principle can be applied with more immediate results. One prominent problem in WEIRD countries is the ‘revolving door’, whereby individuals seamlessly move between government and private sector positions. Blanes i Vidal et al. (Reference Blanes i Vidal, Draca and Fons-Rosen2012) reveal that 56% of the revenue by private lobbying firms in the USA between 1998 and 2008 can be attributed to lobbyists with previous federal government experience. Furthermore, 34 of the 50 top lobbyists in Washington have previous federal government experience (Eisler, Reference Eisler2007). The prospect of future employment in the private sector may influence the behaviour of public servants (deHaan et al., Reference deHaan, Kedia, Koh and Rajgopal2015), to increase their employability. Banning the revolving door, or at least setting a long minimum time between switching from the public to private sector, may help to undermine such lower scales of cooperation (e.g. the ‘cooling-down’ period for members of the European Commission has been increased from 12 months in 1999, to 18 months in 2011 and to 24 months in 2016, after former President of the Commission Barosso joined Goldman Sachs, shortly after he had left office (Luechinger & Moser, Reference Luechinger and Moser2020)).

Corruption is by no means restricted to the developing world, but plagues societies with less robust democratic institutions and norms. Indeed, corruption may have a greater absolute cost in the developed world, but a greater relative cost in the developing world (Muthukrishna, Reference Muthukrishna2017; Muthukrishna et al., Reference Muthukrishna, Francois, Pourahmadi and Henrich2017; Henrich & Muthukrishna, Reference Henrich and Muthukrishna2021). Undermining informal tribal institutions is a difficult challenge for the same reasons that it's difficult to stop FGC. Aligning the societal institutions with local structures may be a less ambitious, more practical and effective approach. For example, a recent study in the Democratic Republic of Congo found that giving local chiefs the authority to collect state taxes increased property tax compliance by 3.3% (Balan et al., Reference Balan, Bergeron, Tourek and Weigel2022). Although the chief still collected bribes, they were able to use local knowledge of whom to target with tax enforcement and thus increased the overall tax revenue by 43%. Their local knowledge allowed them to target high-income individuals reversing the inefficient and unfair, but common practice of targeting the more easily auditable lower-income bracket. For example, in the USA, people earning less than $25,000 are at least three times more likely to be audited than partnership firms (Sorkin et al., Reference Sorkin, Karaian, Kessler, de la Merced, Hirsch and Livni2021). Teaming up with bribe-collecting chiefs may not be the first choice for current approaches in public policy, but is a step in the right direction and sensible from a cultural evolutionary approach, combining and aligning different scales of cooperation. Moreover, it allows us to move a society to an adjacent possible in the cultural space, where planned policies can continue to put a society on a path to a more efficient equilibrium (Muthukrishna & Henrich, Reference Muthukrishna and Henrich2016; Muthukrishna et al., Reference Muthukrishna, Henrich and Slingerland2021; Nunn, Reference Nunn, Bisin and Federico2021).

Successful democratic institutions

Formal institutions can be thought of as hardened culture – written down to allow for easier coordination and application. But no institution can anticipate all possible behaviours. Thus successful institutions rest on necessary cultural norms. But unlike the explicit institutions, these norms are largely invisible to those who have implicitly internalized them since they were children. Therefore, foreign policymakers exporting successful WEIRD institutions, such as liberal democracies, have systematic blindspots that lead them to unknowingly ignore the invisible cultural pillars that support institutions.

Giuliano and Nunn's (Reference Giuliano and Nunn2013) analyses reveal that where democratic institutions have been successfully transplanted are places where proto-democratic institutions (and presumably the requisite norms) already existed. They also offer an example of how cultural evolutionary behavioural science can be informed by historical data, building the Ancestral Characteristics Database (Giuliano & Nunn, Reference Giuliano and Nunn2018) using data from the Ethnographic Atlas (Murdock, Reference Murdock1967), Ethnologue (Lewis, Reference Lewis2009) and Landscan 2000 (Dobson et al., Reference Dobson, Bright, Coleman, Durfee and Worley2000). There is a historical path dependence of traditional local democracies on the beliefs and attitudes towards today's political institutions, robust to European influence and quality of land for agriculture among other controls.

As a contrasting example, the recent high-profile failure to implement liberal democratic institutions in Afghanistan can be at least partially blamed on differences in norms around rule of law and impartial rules applied impartially to all people. Afghanistan is high on strong kin-based cooperation; people rely on their kin for survival through support and favours, even marrying among their extended family (the rate of cousin marriage in Afghanistan is 46%; Saify & Saadat, Reference Saify and Saadat2012). Kin-based obligations undermine the kind of impartial institutions that liberal democracies are familiar with. Moreover, the exogenous laws borrowed from other cultures may be rejected by parts of the population with strong prior beliefs, such as those grounded in Islamic sharia law. A Pew survey (2013) suggests that 99% of Afghans favour making Sharia the official law of the land, 81% of Afghans favour corporal punishment (like lashings) for theft, 85% favour stoning as the punishment for adultery and 79% favour a death penalty for leaving Islam. It is important to consider how these numbers are affected by the timing of the survey, representativeness of the respondents and response biases, but it is critical to have at least some measure of such norms rather than relying on assumptions about human behaviour drawn from a WEIRD life experience. Such norms are critical to predicting whether an institution or policy will succeed and assumptions about what people want (e.g. freedom of speech, freedom in behaviour, impartial rules, rule of law, secular society, etc.) based on WEIRD life experience cannot be assumed to be human universals. Without appropriate cultural pillars, institutions such as democracy collapse.

Finally, institutions interact with norms, mutually shaping one another. In 2011, the Supreme Court of the Canadian province of British Columbia ruled that the prohibition against polygamy was constitutionally valid. The case was in part decided by cultural evolutionary scientists, Joseph Henrich's primary expert witness on the role that monogamy has had in stabilizing society by solving the problem of young males who can not find a wife (Henrich et al., Reference Henrich, Boyd and Richerson2012). Henrich argued that ‘monogamy seems to direct male motivations in ways that create lower crime rates, greater wealth (GDP) per capita and better outcomes for children’. In contrast, polygamy leads to a surplus of unmarried men, that may engage in high-risk strategies or criminal activities to secure sufficient resources to find a mate (BC Supreme Court, 2010; Bucci, Reference Bucci2010). Indeed, China's one-child policy combined with a cultural son preference temporarily led to a doubling of ‘surplus men’. An analysis by Edlund et al. (Reference Edlund, Li, Yi and Zhang2013) suggested that for every 1% increase in male bias in the sex ratio, property and violent crimes rise by 3%. Similar data can be found in India (Drèze & Khera, Reference Drèze and Khera2000), where male-biased sex ratios are associated with murder rates across districts. The British Columbian Supreme Court decision is an example of how institutions can be used to constrain and reinforce cultural practices that would otherwise undermine these institutions, and a policy decision informed by cultural evolutionary research.

Sustainable development

Taking a cultural evolutionary approach to sustainable development, Waring et al. (Reference Waring, Kline, Brooks, Goff, Gowdy, Janssen, Smaldino and Jacquet2015, Reference Waring, Goff and Smaldino2017) identify four factors that academics and policymakers need to better understand to accomplish sustainability policy goals. First, policy needs to be informed by knowledge about the emergence and persistence of social-ecological states – how social and ecological factors relate and interact. Second, they need to account for endogenous cultural change (Berger et al., Reference Berger, Efferson and Vogt2021; Constantino et al., Reference Constantino, Sparkman, Kraft-Todd, Bicchieri, Centola, Shell-Duncan, Vogt and Weber2022). Third, they need to incorporate cooperation dynamics. And fourth, they need to address the complexities of social-ecological interactions over multiple levels (Waring et al., Reference Waring, Kline, Brooks, Goff, Gowdy, Janssen, Smaldino and Jacquet2015).

Using this approach, they derive several principles that can guide policy implementation. These principles include targeting the appropriate level of selection (e.g. targeting group vs targeting individual), changing the level of selection pressure (e.g. change incentive structure to group-level payoffs), shifting trait variation across levels (between-group vs within-group variation in cultural traits), leveraging the evolution of cooperation (e.g. creating infrastructure that allows for repeated interactions, reputational mechanisms and peer punishments to increase prosociality) and avoiding ethnocentric solutions (e.g. counter the tendency for policies driven by social identity of groups). Waring's work is an example of the broader contribution of evolutionary anthropology to public policy (Alvard, Reference Alvard1998; Gibson & Lawson, Reference Gibson, Lawson, Gibson and Lawson2014).

Summary

As the diverse domains above illustrate, cultural evolutionary public policy sometimes suggests ways of solving a problem. But a cultural evolutionary approach also fundamentally shifts the approach itself for how to go about designing a solution – a solution is not always designed. An invisible cultural pillar of economic-derived public policy is the assumption of a great planner or policymaker. This approach is akin to an intelligent designer's view of culture and institutions. We can contrast this with genetic evolution's blind watchmaker and cultural evolution's visually impaired watchmaker. Not designing but instead evolving good solutions through efficient selection between different approaches designed with partial causal models of the world (Muthukrishna & Henrich, Reference Muthukrishna and Henrich2016; Schimmelpfennig et al., Reference Schimmelpfennig, Razek, Schnell and Muthukrishna2022). A cultural evolutionary public policy is not simply about designing efficient institutions but designing efficiently evolving institutions.

The challenge of understanding ultimate causes for application

Discovering ultimate causes of a behaviour is an important goal for the social sciences, though the focus is often on proximate explanations (Tinbergen, Reference Tinbergen1963; Mesoudi, Reference Mesoudi2009, Reference Mesoudi2016). Ultimate causes offer a more ‘upstream’ policy lever since proximate causes may be replaced by a different proximate cause if the ultimate cause remains. As Pirsig (Reference Pirsig2006) put it, if a factory is torn down, but the reasons for the factory persist, a new factory will take its place.

For example, consider gender roles and gender inequality in societies. A proximate explanation may focus on attitudes, preferences, beliefs or ideologies. At a proximate level, one could explain gender inequality as a product of men perceiving themselves as superior. This may lead to policies, such as implicit bias training (Forscher et al., Reference Forscher, Lai, Axt, Ebersole, Herman, Devine and Nosek2019; Pritlove et al., Reference Pritlove, Juando-Prats, Ala-leppilampi and Parsons2019), but ignores the underlying causes for the attitudes, preferences, beliefs, ideologies and subsequent behaviours.

Discovering these underlying causes requires considering the cultural evolution of gendered perceptions and norms. Two influential hypotheses in this field stem from historical economics. Research by Alesina et al. (Reference Alesina, Giuliano and Nunn2013) reveals that current-day gender norms covary with historical cultures, for example, traditional agricultural practices (Lonati, Reference Lonati2020). Specifically, areas with higher intensity in the use of the plough (causally exogenously identified by land suitability to the plough) have less gender-equal norms – a product of the plough requiring greater physical strength than the hoe giving males a comparative advantage and leading to a larger sex-based division of labour. These attitudes persist even after plough-based agriculture is replaced by machines and can be measured in attitudes towards gender roles and behaviour in the participation of women in the workplace, politics and entrepreneurship. Moreover, these effects are measurable in second-generation immigrants that are not born in these regions but have family ties. In this case, these norms lead to other norms and infrastructure that reinforce gender inequality. In turn, these differences may be mitigated by policies that target not just gender norms, but the broader set of cultural norms and institutional infrastructure that reduce the unequal cost of childbearing and rearing borne by women (Kleven et al., Reference Kleven, Landais, Posch, Steinhauer and Zweimüller2019, Reference Kleven, Landais and Søgaard2021).

Considering this ultimate level of explanation is critical to designing culturally aware public policies. In 2005, India passed a law requiring equal female inheritance. This in turn, led to increases in parallel cousin marriage and decreases in female labour force participation (Bahrami-Rad, Reference Bahrami-Rad2021). This well-intentioned policy is a powerful illustration that people may not respond to incentives in a way that policy makers expect. Cultural evolution can offer an ultimate-level explanation for problems that get to root causes. In doing that, it can provide new solutions to problems that are often dealt with at a proximate level.

As another example, the paradox of diversity refers to the inherent trade-off between cultural trait diversity's potential for recombinatorial innovation and division created by communication and coordination challenges (Muthukrishna, Reference Muthukrishna2020b). Considering evolvability in cultural evolution offers a framework for resolving the paradox of diversity (Schimmelpfennig et al., Reference Schimmelpfennig, Razek, Schnell and Muthukrishna2022), moving the focus from norms and biases to factors such as zero-sum perceptions and reality in intergroup competition (Schimmelpfennig & Muthukrishna, Reference Schimmelpfennig and Muthukrishna2021). Understanding ultimate causes offer new policy levers for tackling long-standing problems.

The challenge of knowing how context matters?

Context matters in behavioural science (Michie et al., Reference Michie, van Stralen and West2011; Dolan et al., Reference Dolan, Hallsworth, Halpern, King, Metcalfe and Vlaev2012; World Bank Group, 2015). But how does it matter? Consider research on dishonesty. Experiments reveal that a simple change in framing can lead honest citizens to behave like dishonest bankers (Cohn et al., Reference Cohn, Fehr and Maréchal2014). Professionals from a Swiss bank participated in a game to measure honest behaviour. They privately rolled a die a few times and afterwards reported to the experimenter how many times they rolled an even number (for each even number the participant received a payoff). Since the die roll was private, at an individual level, it was impossible to know if participants were being dishonest or were just lucky, but at a group level, researchers could measure the degree of dishonesty based on deviations from the expected distribution of even numbers. The main treatment manipulated the context, by either priming a professional (e.g. talking about their job before the task) or a personal context (e.g. talking about hobbies). The researchers found that bankers primed for the professional context were significantly more dishonest, reporting 58.6% even dice rolls (50% would be expected on a six-sided dice). One conclusion would be that the financial sector attracts dishonest people, but the bankers in the control group primed with a personal context did not significantly deviate from the expected frequency of even dice rolls (they reported 51.8%). These results suggest the importance of context and culture rather than types of people for creating dishonest behaviour (Cohn et al., Reference Cohn, Fehr and Maréchal2014). But the conclusions are more complicated – the same prime may create different behaviours in different cultural contexts (Cohn et al., Reference Cohn, Fehr and Maréchal2019; Rahwan et al., Reference Rahwan, Yoeli and Fasolo2019) or in-person vs online (Cohn et al., Reference Cohn, Gesche and Maréchal2022). Participants are more dishonest (i.e. report more successful dice rolls than expected) when embedded in a digital context (i.e. when reporting results to a chatbot), compared to communicating their dice rolls to a human.

A question policymakers need answers to is how context matters for the effectiveness of their policies. Cultural differences are low-hanging fruit – the evidence for the impact of cultural differences on the replicability and generalizability of research in social science has grown in the past decade (Henrich et al., Reference Henrich, Heine and Norenzayan2010b; Apicella et al., Reference Apicella, Norenzayan and Henrich2020; Henrich, Reference Henrich2020). Advancements in the measurement of cultural differences offer new tools for policymakers. Muthukrishna et al. (Reference Muthukrishna, Bell, Henrich, Curtin, Gedranovich, Mcinerney and Thue2020) developed a cultural distance CFst scale revealing how cultural distance from the United States – which may serve as a proxy for a ‘WEIRD scale’ – predicts other cultural differences, from individualism to personality, prosociality and honesty. Beyond documenting such differences, other research reveals the origins of differences in personality (Gurven et al., Reference Gurven, von Rueden, Massenkoff, Kaplan and Vie2013; Smaldino, Reference Smaldino2019), normative behaviours and prosociality (Henrich et al., Reference Henrich, Boyd, Bowles, Camerer, Fehr, Gintis and McElreath2001; Santos et al., Reference Santos, Varnum and Grossmann2017; Muthukrishna & Schaller, Reference Muthukrishna and Schaller2020), and more broadly, in how our brain processes visual information (Dehaene et al., Reference Dehaene, Pegado, Braga, Ventura and Nunes Filho2010; Han et al., Reference Han, Northoff, Vogeley, Wexler, Kitayama and Varnum2013). These differences are increasingly important in interpreting research findings and possible heterogeneous treatment effects (IJzerman et al., Reference IJzerman, Lewis, Przybylski, Weinstein, DeBruine, Ritchie, Vazire, Forscher, Morey, Ivory and Anvari2020; Bryan et al., Reference Bryan, Tipton and Yeager2021; Sunstein, Reference Sunstein2021).

The challenge of traditions and historical path dependencies

Societies do not emerge spontaneously, but evolve over decades and centuries – they are shaped by history (Henrich, Reference Henrich2020; Muthukrishna et al., Reference Muthukrishna, Henrich and Slingerland2021; Uchiyama et al., Reference Uchiyama, Spicer and Muthukrishna2021). Genetic drift may play an important role in how societies develop, but the effect of cultural evolution is much larger (Bell et al., Reference Bell, Richerson and McElreath2009; Uchiyama et al., Reference Uchiyama, Spicer and Muthukrishna2021). Thus, cultural evolutionary public policy can use history to identify the ultimate causes of present-day psychology (Muthukrishna et al., Reference Muthukrishna, Henrich and Slingerland2021). This historical psychology matters for present-day policy interventions.

One dark example of historical path dependency is the effects of ‘Tuskegee Study’ on trust in public health services. The Tuskegee Study was a longitudinal study in the USA between the 1930s and 1970s. Researchers wanted to better understand the health consequences of untreated syphilis. The participants, African Americans who had contracted Syphilis, were assigned to not receive available treatments against the disease. Worse still, participants were not informed about the nature of the experiment. Over 100 died as a result and many family members also contracted the disease. These historical events contribute to the mistrust of medical communities and public health in present-day African American communities (Thomas & Quinn, Reference Thomas and Quinn1991; Corbie-Smith, Reference Corbie-Smith1999; Corbie-Smith et al., Reference Corbie-Smith, Thomas, Williams and Moody-Ayers1999). In an influential study, Alsan and Wanamaker (Reference Alsan and Wanamaker2018) offer support for this claim with an identification strategy using publicly available data. Using and interacted difference-in-difference-in-differences model, that compared older black men to other demographic groups before and after the disclosure of the study in 1972 (Alsan & Wanamaker, Reference Alsan and Wanamaker2018). Their results reveal that exposure to the disclosure of the event is correlated with increases in medical mistrust and decreases in both outpatient and inpatient physician interactions for older black men. As a consequence, life expectancy fell by up to 1.5 years in response to the exposure. Although improving, health outcomes are still comparably worse for African American families, a tragedy reinforced by data from the COVID-19 pandemic (Price-Haywood et al., Reference Price-Haywood, Burton, Fort and Seoane2020). Similar decreases in medical mistrust have been attributed to medical campaigns in colonial Africa (Lowes & Montero, Reference Lowes and Montero2021) and a CIA-staged vaccination campaign in Pakistan (Martinez-Bravo & Stegmann, Reference Martinez-Bravo and Stegmann2022). A better understanding of historical psychology is thus an important part of cultural evolutionary behavioural science.

The challenge of modern technologies and online interactions

Getting into a stranger's car or spending the night in their empty home was once dangerous and ill-advised. Today it's commonplace thanks to companies like Uber and Airbnb. These platforms facilitate cooperation by brokering reputational information (Muthukrishna, Reference Muthukrishna2021). Online reviews and ratings are an institutionally mediated form of indirect reciprocity and an example of cultural evolution interacting with modern technologies and online interactions. These institutions securitize and centralize trust, allowing us to scale up reputational cooperation through trust in the institution rather than several independent sources of reputational information. But that reputational information is not always present, and we can not trust everything we find online.

Misinformation is less about information and more about trust. The cultural cues we would normally use to distinguish truth from falsehoods are often missing online perhaps making us more susceptible to believing misinformation. Cultural evolution reveals that we learn what is right and true not through a deep causal understanding of information, but through trust in whom we receive the information. We believe that the world is round and rotating around the sun in violation of our everyday experience because we trust those who told us and live in a world where everyone we trust also holds this belief. We believe that a virus caused the COVID-19 pandemic, and an mRNA vaccine can help mitigate it, not because we really understand germ theory or exactly what messenger RNA is or does, but because of whom we trust. Trust that the sources of information are knowledgeable, prestigious, sincere, and in the same cooperative group, such that actions are for our mutual benefit. But information on the Internet often lacks the signals we have evolved to pay attention to, such as cues of prestige, sincerity displays or credibility enhancing displays (CREDS) (Chudek et al., Reference Chudek, Muthukrishna, Henrich and Buss2015; Henrich, Reference Henrich2016). Misinformation can undermine the foundations of our societies and so incorporating our understanding of our cultural learning psychology into the design of digital infrastructure is an important direction for applied behavioural science.

Incentive structures for leaders and stakeholders

In principle, a scientist's key concern is getting the science right and in practice, an additional concern is being able to publish the science. It is critical to get the science right and have the support of peers via peer review. Overselling or getting the science wrong undermines trust in science and scientists. But for politicians and policy stakeholders the right science supported by peer-reviewed publications is barely the first step.

Politicians and policy stakeholders often have competing motivations and additional challenges. For example, a new approach may seem risky to career civil servants with little incentive to innovate and many incentives to not fail to ensure the next promotion in their career. A politician must be able to sell a new approach within their own party and to their broader constituency who may not fully understand the science. And mediating the relationship between science, politics, the public and the media.

Thus, although science communication, managing media and nurturing relationships with politicians and policymakers may not seem like a scientist's job, these are critical to successful behavioural science in public policy, even more so when dealing with a cutting-edge approach such as cultural evolutionary behavioural science. As cultural evolution would suggest, reputation and trust are critical. Scientific methods, such as experimentation and randomization, are poorly understood and sometimes aversive to some parts of society, perhaps in politics too. Meyer et al. (Reference Meyer, Heck, Holtzman, Anderson, Cai, Watts and Chabris2019), for example, find that people are often averse to randomization, especially where health is involved. This aversion is true even when people have similar ratings for the options (Heck et al., Reference Heck, Chabris, Watts and Meyer2020). A parallel aversion seems to exist for decisions made by algorithms (Dietvorst et al., Reference Dietvorst, Simmons and Massey2018). These methods are banal for scientists, but of concern to stakeholders for whom public reactions are paramount to their success. Thus, the success of cultural evolutionary behavioural science in public policy is contingent on overcoming these non-scientific barriers. In any case, informed consent is critical to the ethical application of behavioural science.

Ethics

The ethics of nudging and behavioural science interventions are actively debated and discussed in the discipline. Even if cultural evolutionary approaches to behavioural science are effective, they may not be socially desirable or perceived to be ethical. In general, questions remain about whether it is ethical for researchers and policymakers to experiment with the public and manipulate behavioural change. These questions are perhaps even more pertinent for cultural evolutionary scientists dealing with what amounts to scaled cultural change.

These debates are not new and interventions continue by those who argue that if a policy goal is socially desirable and the freedom of choice is not restricted, the intervention is ethical (Thaler & Sunstein, Reference Thaler and Sunstein2003). Lades and Delaney (Reference Lades and Delaney2020) offer a more specific framework that goes beyond the question of choice restriction – FORGOOD (Table 1).

Table 1. FORGOOD ethics framework for nudging and behavioural sciences based on Lades and Delaney (Reference Lades and Delaney2020).

This framework equally applies to cultural evolutionary public policy, but there are additional concerns for cultural interventions. Here are a few:

1. 1. It may be preferable and more ethical to aim for endogenous norm and behaviour change driven by existing variation and selective social learning and social influence (Efferson et al., Reference Efferson, Vogt and Fehr2020).

2. 2. Additional caution is required where cultural evolutionary processes can initiate long-enduring path dependencies. This is especially important as well-intended interventions can change adaptive cultural practices that seem maladaptive from the outside. For example, the Asian Development Bank changed the irrigation of rice fields in Bali which was, until then, dominated by cultural practices in which all rice farmers would irrigate their fields at the same time during a ceremony (Lansing, Reference Lansing2009). This traditional practice left little room for pests to develop, as all fields were flooded at the same time. After the implementation of the new uncoordinated irrigation practice, pests flourished, leading to large losses in harvests. Similarly, transhumant pastoralism, which is often viewed as an archaic form of livestock farming (Mattee, Reference Mattee2006), may be adapted to the local circumstances, allowing livestock to flexibly move according to the environmental circumstances (FAO, 2018).

3. 3. All policies are likely to affect the process of cultural evolution by changing the information landscape or the models from whom information flows. Cultural evolutionary scientists can and should be more aware and cautious of these effects. Managing cultural evolution can itself be an effective method for enhancing the ability of groups to evolve new solutions.

Overall, cultural evolutionary researchers should also be more acutely aware that societies are made up of embedded and overlapping distributions of beliefs, behaviours and other cultural traits and thus should be more acutely aware of the effects of possibilities created by this diversity.

Diverse populations

Behavioural experiments often assume homogenous populations, but recognizing, measuring and developing interventions that incorporate the reality of heterogeneity can be an effective strategy (Bryan et al., Reference Bryan, Tipton and Yeager2021; Sunstein, Reference Sunstein2021).

Heterogeneity in beliefs and behaviours complicates the large-scale adoption of new policies (Muthukrishna et al., Reference Muthukrishna, Francois, Pourahmadi and Henrich2017; Efferson et al., Reference Efferson, Vogt and Fehr2020). Different people can react in different ways to the same intervention and these differences may even have unintended effects with negative behavioural spillovers (Efferson et al., Reference Efferson, Vogt and Fehr2020; Schimmelpfennig et al., Reference Schimmelpfennig, Vogt, Ehret and Efferson2021; Ehret et al., Reference Ehret, Constantino, Weber, Efferson and Vogt2022). As more and more culturally distant humans live side by side, an individual-level approach to nudging becomes less tenable and even harmful. For example, targeting the wrong part of a society without prior measurement can lead to reactance. This may explain why an intervention to reduce FGC in Kenya actually increased the cultural practice (Thomas, Reference Thomas, Shell-Duncan and Hernlund2000).

Impact evaluation

Measuring the impact of a public program is a cornerstone of an evidence-based approach to policy. Impact evaluation of cultural evolutionary public policy is likely to encounter two key challenges:

1. 1. Data collection is difficult and unattractive to many stakeholders: Cultural evolutionary behavioural science requires large datasets that can detect contextual factors and cultural differences within populations. Sampling data in a population is often difficult, expensive and creates no immediate payoff for policymakers. Furthermore, measurements will often feature selection biases, as relatively amenable subjects self-select into the sample (Berk, Reference Berk1983; Heckman, Reference Heckman1990), or provide socially desirable responses (Krumpal, Reference Krumpal2013). More efficient methods of data collection, such as random sampling, may be more likely to be implemented.

2. 2. Evaluating out of sample and across time: Cultural evolution can play out over long periods, but the time horizon of policies and politicians is often driven by shorter cycles of elections and media attention. Moreover, public programmes directed at a subset of a population are likely to have effects beyond the group targeted by the policy. Thus, the impact assessment of the policy must continue over a period of time and go beyond the targeted population to detect possible spillovers.

Despite these challenges, impact evaluation is critical to not just applied cultural evolutionary behavioural science, but the basic science of cultural evolution.