3.3 million years of stone tool complexity suggests that cumulative culture began during the Middle Pleistocene.

Cumulative culture, the accumulation of modifications, innovations, and improvements over generations through social learning, is a key determinant of the behavioral diversity across Homo sapiens populations and their ability to adapt to varied ecological habitats. Generations of improvements, modifications, and lucky errors allow humans to use technologies and know-how well beyond what a single naive individual could invent independently within their lifetime. The human dependence on cumulative culture may have shaped the evolution of biological and behavioral traits in the hominin lineage, including brain size, body size, life history, sociality, subsistence, and ecological niche expansion. Yet, we do not know when, in the human career, our ancestors began to depend on cumulative culture. Here, we show that hominins likely relied on a derived form of cumulative culture by at least ~600 kya, a result in line with a growing body of existing evidence. We analyzed the complexity of stone tool manufacturing sequences over the last 3.3 My of the archaeological record. We then compare these to the achievable complexity without cumulative culture, which we estimate using nonhuman primate technologies and stone tool manufacturing experiments. We find that archaeological technologies become significantly more complex than expected in the absence of cumulative culture only after ~600 kya.

Indirect reciprocity undermines indirect reciprocity destabilizing large-scale cooperation.

Previous models suggest that indirect reciprocity (reputation) can stabilize large-scale human cooperation [K. Panchanathan, R. Boyd, Nature 432, 499-502 (2004)]. The logic behind these models and experiments [J. Gross et al., Sci. Adv. 9, eadd8289 (2023) and O. P. Hauser, A. Hendriks, D. G. Rand, M. A. Nowak, Sci. Rep. 6, 36079 (2016)] is that a strategy in which individuals conditionally aid others based on their reputation for engaging in costly cooperative behavior serves as a punishment that incentivizes large-scale cooperation without the second-order free-rider problem. However, these models and experiments fail to account for individuals belonging to multiple groups with reputations that can be in conflict. Here, we extend these models such that individuals belong to a smaller, "local" group embedded within a larger, "global" group. This introduces competing strategies for conditionally aiding others based on their cooperative behavior in the local or global group. Our analyses reveal that the reputation for cooperation in the smaller local group can undermine cooperation in the larger global group, even when the theoretical maximum payoffs are higher in the larger global group. This model reveals that indirect reciprocity alone is insufficient for stabilizing large-scale human cooperation because cooperation at one scale can be considered defection at another. These results deepen the puzzle of large-scale human cooperation.

History constrains the evolution of efficient color naming, enabling historical inference.

Color naming in natural languages is not arbitrary: It reflects efficient partitions of perceptual color space [T. Regier, P. Kay, N. Khetarpal, Proc. Natl. Acad. Sci. U.S.A. 104, 1436-1441 (2007)] modulated by the relative needs to communicate about different colors [C. Twomey, G. Roberts, D. Brainard, J. Plotkin, Proc. Natl. Acad. Sci. U.S.A. 118, e2109237118 (2021)]. These psychophysical and communicative constraints help explain why languages around the world have remarkably similar, but not identical, mappings of colors to color terms. Languages converge on a small set of efficient representations.But languages also evolve, and the number of terms in a color vocabulary may change over time. Here we show that history, i.e. the existence of an antecedent color vocabulary, acts as a nonadaptive constraint that biases the choice of efficient solution as a language transitions from a vocabulary of size [Formula: see text] to [Formula: see text] terms. Moreover, as efficient vocabularies evolve to include more terms they explore a smaller fraction of all possible efficient vocabularies compared to equally sized vocabularies constructed de novo. This path dependence of the cultural evolution of color naming presents an opportunity. Historical constraints can be used to reconstruct ancestral color vocabularies, allowing us to answer long-standing questions about the evolutionary sequences of color words, and enabling us to draw inferences from phylogenetic patterns of language change.

Formation of human kinship structures depending on population size and cultural mutation rate.

How does social complexity depend on population size and cultural transmission? Kinship structures in traditional societies provide a fundamental illustration, where cultural rules between clans determine people's marriage possibilities. Here, we propose a simple model of kinship interactions that considers kin and in-law cooperation and sexual rivalry. In this model, multiple societies compete. Societies consist of multiple families with different cultural traits and mating preferences. These values determine interactions and hence the growth rate of families and are transmitted to offspring with mutations. Through a multilevel evolutionary simulation, family traits and preferences are grouped into multiple clans with interclan mating preferences. It illustrates the emergence of kinship structures as the spontaneous formation of interdependent cultural associations. Emergent kinship structures are characterized by the cycle length of marriage exchange and the number of cycles in society. We numerically and analytically clarify their parameter dependence. The relative importance of cooperation versus rivalry determines whether attraction or repulsion exists between families. Different structures evolve as locally stable attractors. The probabilities of formation and collapse of complex structures depend on the number of families and the mutation rate, showing characteristic scaling relationships. It is now possible to explore macroscopic kinship structures based on microscopic interactions, together with their environmental dependence and the historical causality of their evolution. We propose the basic causal mechanism of the formation of typical human social structures by referring to ethnographic observations and concepts from statistical physics and multilevel evolution. Such interdisciplinary collaboration will unveil universal features in human societies.

Exposure to automation explains religious declines.

The global decline of religiosity represents one of the most significant societal shifts in recent history. After millennia of near-universal religious identification, the world is experiencing a regionally uneven trend toward secularization. We propose an explanation of this decline, which claims that automation-the development of robots and artificial intelligence (AI)-can partly explain modern religious declines. We build four unique datasets composed of more than 3 million individuals which show that robotics and AI exposure is linked to 21st-century religious declines across nations, metropolitan regions, and individual people. Key results hold controlling for other technological developments (e.g., electricity grid access and telecommunications development), socioeconomic indicators (e.g., wealth, residential mobility, and demographics), and factors implicated in previous theories of religious decline (e.g., individual choice norms). An experiment also supports our hypotheses. Our findings partly explain contemporary trends in religious decline and foreshadow where religiosity may wane in the future.

Universal interpretations of vocal music.

Despite the variability of music across cultures, some types of human songs share acoustic characteristics. For example, dance songs tend to be loud and rhythmic, and lullabies tend to be quiet and melodious. Human perceptual sensitivity to the behavioral contexts of songs, based on these musical features, suggests that basic properties of music are mutually intelligible, independent of linguistic or cultural content. Whether these effects reflect universal interpretations of vocal music, however, is unclear because prior studies focus almost exclusively on English-speaking participants, a group that is not representative of humans. Here, we report shared intuitions concerning the behavioral contexts of unfamiliar songs produced in unfamiliar languages, in participants living in Internet-connected industrialized societies (n = 5,516 native speakers of 28 languages) or smaller-scale societies with limited access to global media (n = 116 native speakers of three non-English languages). Participants listened to songs randomly selected from a representative sample of human vocal music, originally used in four behavioral contexts, and rated the degree to which they believed the song was used for each context. Listeners in both industrialized and smaller-scale societies inferred the contexts of dance songs, lullabies, and healing songs, but not love songs. Within and across cohorts, inferences were mutually consistent. Further, increased linguistic or geographical proximity between listeners and singers only minimally increased the accuracy of the inferences. These results demonstrate that the behavioral contexts of three common forms of music are mutually intelligible cross-culturally and imply that musical diversity, shaped by cultural evolution, is nonetheless grounded in some universal perceptual phenomena.

Multilevel cultural evolution: From new theory to practical applications.

Evolutionary science has led to many practical applications of genetic evolution but few practical uses of cultural evolution. This is because the entire study of evolution was gene centric for most of the 20th century, relegating the study and application of human cultural change to other disciplines. The formal study of human cultural evolution began in the 1970s and has matured to the point of deriving practical applications. We provide an overview of these developments and examples for the topic areas of complex systems science and engineering, economics and business, mental health and well-being, and global change efforts.

Large language models show human-like content biases in transmission chain experiments.

As the use of large language models (LLMs) grows, it is important to examine whether they exhibit biases in their output. Research in cultural evolution, using transmission chain experiments, demonstrates that humans have biases to attend to, remember, and transmit some types of content over others. Here, in five preregistered experiments using material from previous studies with human participants, we use the same, transmission chain-like methodology, and find that the LLM ChatGPT-3 shows biases analogous to humans for content that is gender-stereotype-consistent, social, negative, threat-related, and biologically counterintuitive, over other content. The presence of these biases in LLM output suggests that such content is widespread in its training data and could have consequential downstream effects, by magnifying preexisting human tendencies for cognitively appealing and not necessarily informative, or valuable, content.

Norm Dynamics: Interdisciplinary Perspectives on Social Norm Emergence, Persistence, and Change.

Social norms are the glue that holds society together, yet our knowledge of them remains heavily intellectually siloed. This article provides an interdisciplinary review of the emerging field of norm dynamics by integrating research across the social sciences through a cultural-evolutionary lens. After reviewing key distinctions in theory and method, we discuss research on norm psychology-the neural and cognitive underpinnings of social norm learning and acquisition. We then overview how norms emerge and spread through intergenerational transmission, social networks, and group-level ecological and historical factors. Next, we discuss multilevel factors that lead norms to persist, change, or erode over time. We also consider cultural mismatches that can arise when a changing environment leads once-beneficial norms to become maladaptive. Finally, we discuss potential future research directions and the implications of norm dynamics for theory and policy.

A global analysis of matches and mismatches between human genetic and linguistic histories.

Human history is written in both our genes and our languages. The extent to which our biological and linguistic histories are congruent has been the subject of considerable debate, with clear examples of both matches and mismatches. To disentangle the patterns of demographic and cultural transmission, we need a global systematic assessment of matches and mismatches. Here, we assemble a genomic database (GeLaTo, or Genes and Languages Together) specifically curated to investigate genetic and linguistic diversity worldwide. We find that most populations in GeLaTo that speak languages of the same language family (i.e., that descend from the same ancestor language) are also genetically highly similar. However, we also identify nearly 20% mismatches in populations genetically close to linguistically unrelated groups. These mismatches, which occur within the time depth of known linguistic relatedness up to about 10,000 y, are scattered around the world, suggesting that they are a regular outcome in human history. Most mismatches result from populations shifting to the language of a neighboring population that is genetically different because of independent demographic histories. In line with the regularity of such shifts, we find that only half of the language families in GeLaTo are genetically more cohesive than expected under spatial autocorrelations. Moreover, the genetic and linguistic divergence times of population pairs match only rarely, with Indo-European standing out as the family with most matches in our sample. Together, our database and findings pave the way for systematically disentangling demographic and cultural history and for quantifying processes of shifts in language and social identities on a global scale.

Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents.

How do societies learn and maintain social norms? Here we use multiagent reinforcement learning to investigate the learning dynamics of enforcement and compliance behaviors. Artificial agents populate a foraging environment and need to learn to avoid a poisonous berry. Agents learn to avoid eating poisonous berries better when doing so is taboo, meaning the behavior is punished by other agents. The taboo helps overcome a credit assignment problem in discovering delayed health effects. Critically, introducing an additional taboo, which results in punishment for eating a harmless berry, further improves overall returns. This "silly rule" counterintuitively has a positive effect because it gives agents more practice in learning rule enforcement. By probing what individual agents have learned, we demonstrate that normative behavior relies on a sequence of learned skills. Learning rule compliance builds upon prior learning of rule enforcement by other agents. Our results highlight the benefit of employing a multiagent reinforcement learning computational model focused on learning to implement complex actions.

Understanding the Role of Naive Learners in Cultural Change.

AbstractA change to a population's social network is a change to the substrate of cultural transmission, affecting behavioral diversity and adaptive cultural evolution. While features of network structure such as population size and density have been well studied, less is understood about the influence of social processes such as population turnover-or the repeated replacement of individuals by naive individuals. Experimental data have led to the hypothesis that naive learners can drive cultural evolution by better assessing the relative value of behaviors, although this hypothesis has been expressed only verbally. We conducted a formal exploration of this hypothesis using a generative model that concurrently simulated its two key ingredients: social transmission and reinforcement learning. We simulated competition between high- and low-reward behaviors while varying turnover magnitude and tempo. Variation in turnover influenced changes in the distributions of cultural behaviors, irrespective of initial knowledge-state conditions. We found optimal turnover regimes that amplified the production of higher reward behaviors through two key mechanisms: repertoire composition and enhanced valuation by agents that knew both behaviors. These effects depended on network and learning parameters. Our model provides formal theoretical support for, and predictions about, the hypothesis that naive learners can shape cultural change through their enhanced sampling ability. By moving from experimental data to theory, we illuminate an underdiscussed generative process that can lead to changes in cultural behavior, arising from an interaction between social dynamics and learning.

Language-like efficiency and structure in house finch song.

Communication needs to be complex enough to be functional while minimizing learning and production costs. Recent work suggests that the vocalizations and gestures of some songbirds, cetaceans and great apes may conform to linguistic laws that reflect this trade-off between efficiency and complexity. In studies of non-human communication, though, clustering signals into types cannot be done a priori, and decisions about the appropriate grain of analysis may affect statistical signals in the data. The aim of this study was to assess the evidence for language-like efficiency and structure in house finch (Haemorhous mexicanus) song across three levels of granularity in syllable clustering. The results show strong evidence for Zipf's rank-frequency law, Zipf's law of abbreviation and Menzerath's law. Additional analyses show that house finch songs have small-world structure, thought to reflect systematic structure in syntax, and the mutual information decay of sequences is consistent with a combination of Markovian and hierarchical processes. These statistical patterns are robust across three levels of granularity in syllable clustering, pointing to a limited form of scale invariance. In sum, it appears that house finch song has been shaped by pressure for efficiency, possibly to offset the costs of female preferences for complexity.

Phase synchronization between culture and climate forcing.

Over the history of humankind, cultural innovations have helped improve survival and adaptation to environmental stress. This has led to an overall increase in human population size, which in turn further contributed to cumulative cultural learning. During the Anthropocene, or arguably even earlier, this positive sociodemographic feedback has caused a strong decline in important resources that, coupled with projected future transgression of planetary boundaries, may potentially reverse the long-term trend in population growth. Here, we present a simple consumer/resource model that captures the coupled dynamics of stochastic cultural learning and transmission, population growth and resource depletion in a changing environment. The idealized stochastic mathematical model simulates boom/bust cycles between low-population subsistence, high-density resource exploitation and subsequent population decline. For slow resource recovery time scales and in the absence of climate forcing, the model predicts a long-term global population collapse. Including a simplified periodic climate forcing, we find that cultural innovation and population growth can couple with climatic forcing via nonlinear phase synchronization. We discuss the relevance of this finding in the context of cultural innovation, the anthropological record and long-term future resilience of our own predatory species.

Paradoxes in the coevolution of contagions and institutions.

Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups perceive a contagion as more worrisome, they can invest in improved policies and, if they maintain these policies long enough to have impact, lead to a reduction in endemicity. By looking at the interplay between the speed of institutions and the transmission rate of the contagions, we find rich coevolutionary dynamics that reflect the complexity of known biological and social contagions.

Cultural traits operating in senders are driving forces of cultural evolution.

We introduce a mathematical model of cultural evolution to study cultural traits that shape how individuals exchange information. Current theory focuses on traits that influence the reception of information (receiver traits), such as evaluating whether information represents the majority or stems from a trusted source. Our model shifts the focus from the receiver to the sender of cultural information and emphasizes the role of sender traits, such as communicability or persuasiveness. Here, we show that sender traits are probably a stronger driving force in cultural evolution than receiver traits. While receiver traits evolve to curb cultural transmission, sender traits can amplify it and fuel the self-organization of systems of mutually supporting cultural traits, including traits that cannot be maintained on their own. Such systems can reach arbitrary complexity, potentially explaining uniquely human practical and mental skills, goals, knowledge and creativity, independent of innate factors. Our model incorporates social and individual learning throughout the lifespan, thus connecting cultural evolutionary theory with developmental psychology. This approach provides fresh insights into the trait-individual duality, that is, how cultural transmission of single traits is influenced by individuals, who are each represented as an acquired system of cultural traits.

Janus faced: The co-evolution of war and peace in the human species.

The human species presents a paradox. No other species possesses the propensity to carry out coalitionary lethal attacks on adult conspecifics coupled with the inclination to establish peaceful relations with genetically unrelated groups. What explains this seemingly contradictory feature? Existing perspectives, the "deep roots" and "shallow roots" of war theses, fail to capture the plasticity of human intergroup behaviors, spanning from peaceful cooperation to warfare. By contrast, this article argues that peace and war have both deep roots, and they co-evolved through an incremental process over several million years. On the one hand, humans inherited the propensity for coalitionary lethal violence from their chimpanzee-like ancestor. Specifically, having first inherited the skills to engage in cooperative hunting, they gradually repurposed such capacity to execute coalitionary killings of adult conspecifics and subsequently enhanced it through tech`nological innovations like the use of weapons. On the other hand, they underwent a process of cumulative cultural evolution and, subsequently, of self-domestication which led to heightened cooperative communication and increased prosocial behavior within and between groups. The combination of these two biocultural evolutionary processes-coupled with feedback loop effects between self-domestication and Pleistocene environmental variability-considerably broadened the human intergroup behavioral repertoire, thereby producing the distinctive combination of conflictual and peaceful intergroup relations that characterizes our species. To substantiate this argument, the article synthesizes and integrates the findings from a variety of disciplines, leveraging evidence from evolutionary anthropology, primatology, archeology, paleo-genetics, and paleo-climatology.

Decoding the Dynamics of Cultural Change: A Cultural Evolution Approach to the Psychology of Acculturation.

PUBLIC ABSTRACT: Acculturation describes the cultural and psychological changes resulting from intercultural contact. Here, we use concepts from "cultural evolution" to better understand the processes of acculturation. Cultural evolution researchers view cultural change as an evolutionary process, allowing them to borrow tools and methods from biology. Cultural evolutionary mechanisms such as conformity (copying the numerical majority), anti-conformity (copying the numerical minority), prestige bias (copying famous individuals), payoff bias (copying successful people), and vertical cultural transmission (copying your parents) can cause people to adopt elements from other cultures and/or conserve their cultural heritage. We explore how these transmission mechanisms might create distinct acculturation strategies, shaping cultural change and diversity over the long-term. This theoretical integration can pave the way for a more sophisticated understanding of the pervasive cultural shifts occurring in many ethnically diverse societies, notably by identifying conditions that empower minority-group members, often marginalized, to significantly influence the majority group and society.

Cultural similarity among coreligionists within and between countries.

Cultural evolutionary theories suggest that world religions have consolidated beliefs, values, and practices within a superethnic cultural identity. It follows that affiliation with religious traditions would be reliably associated with global variation in cultural traits. To test this hypothesis, we measured cultural distance between religious groups within and between countries, using the Cultural Fixation Index ([Formula: see text]) applied to the World Values Survey (88 countries, n = 243,118). Individuals who shared a religious tradition and level of commitment to religion were more culturally similar, both within and across countries, than those with different affiliations and levels of religiosity, even after excluding overtly religious values. Moreover, distances between denominations within a world religion echoed shared historical descent. Nonreligious individuals across countries also shared cultural values, offering evidence for the cultural evolution of secularization. While nation-states were a stronger predictor of cultural traits than religious traditions, the cultural similarity of coreligionists remained robust, controlling for demographic characteristics, geographic and linguistic distances between groups, and government restriction on religion. Together, results reveal the pervasive cultural signature of religion and support the role of world religions in sustaining superordinate identities that transcend geographical boundaries.

Inequality, identity, and partisanship: How redistribution can stem the tide of mass polarization.

The form of political polarization where citizens develop strongly negative attitudes toward out-party members and policies has become increasingly prominent across many democracies. Economic hardship and social inequality, as well as intergroup and racial conflict, have been identified as important contributing factors to this phenomenon known as "affective polarization." Research shows that partisan animosities are exacerbated when these interests and identities become aligned with existing party cleavages. In this paper, we use a model of cultural evolution to study how these forces combine to generate and maintain affective political polarization. We show that economic events can drive both affective polarization and the sorting of group identities along party lines, which, in turn, can magnify the effects of underlying inequality between those groups. But, on a more optimistic note, we show that sufficiently high levels of wealth redistribution through the provision of public goods can counteract this feedback and limit the rise of polarization. We test some of our key theoretical predictions using survey data on intergroup polarization, sorting of racial groups, and affective polarization in the United States over the past 50 y.