Underappreciated features of cultural evolution

A neural network model for the evolution of reconstructive social learning

Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transmitted information must be reconstructed by the learner, based on the learner's previous knowledge and cognition. To represent the reconstructive nature of social learning, we present a modelling framework that incorporates the evolution of a neural network and a simple yet biologically realistic learning mechanism. The framework encompasses various forms of individual and social learning and allows the investigation of their interplay. Individual-based simulations reveal that an effective neural network structure rapidly evolves, leading to adaptive inborn behaviour in static environments, pure individual learning in highly variable environments, and a combination of individual and social learning in environments of intermediate stability. However, the evolutionary outcome depends strongly on the type of social learning (social guidance versus social instruction) and the order of individual and social learning. Moreover, the evolutionary dynamics of social learning can be surprisingly complex, with replicate simulations converging to alternative outcomes. We discuss the relevance of our modelling framework for cultural evolution and suggest future avenues of research.

Is Culture Learned? The Neglected Role of Evoking Events

Although no one disputes that the transmission of culture depends on social learning, a capacity that has enabled humans, unlike other animals, to modify cultural practices across generations, this review argues that cultural change can also be evoked by environmental events leading to an alteration in the configuration of an habitual behavioural repertoire. An evoked mechanism allows latent or normally suppressed behaviour to emerge. Cannibalism and warfare are put forward as examples. Evoked mechanisms have largely been ignored by one of the few attempts to reconcile biology and culture, namely cumulative cultural evolution (CCE). This review endorses CCE's aim of developing a biocultural conceptual framework but criticises this model for failing to produce a credible analysis of culture into 'units' or 'variants'. The critique of CCE is situated within a discussion of the long-standing separation within academia of science and arts disciplines, each focusing at different levels of analysis and with different aims. It is suggested that the main obstacle to developing a biocultural framework can be attributed to an incompatibility between nomothetic and idiographic research methods, the former being typical of the biological sciences, the latter of the arts. A successful biocultural conceptual framework would therefore have to accommodate the particular and the general. It is suggested that progress in this direction would be made if agreement could be reached on ways of observing or inferring behaviours rather than pursuing an analysis in terms of hypothetical constructs such as mental representations or units of 'cultural information'.

The evolutionary consequences of learning under competition

Learning is a taxonomically widespread process by which animals change their behavioural responses to stimuli as a result of experience. In this way, it plays a crucial role in the development of individual behaviour and underpins substantial phenotypic variation within populations. Nevertheless, the impact of learning in social contexts on evolutionary change is not well understood. Here, we develop game theoretical models of competition for resources in small groups (e.g. producer-scrounger and hawk-dove games) in which actions are controlled by reinforcement learning and show that biases in the subjective valuation of different actions readily evolve. Moreover, in many cases, the convergence stable levels of bias exist at fitness minima and therefore lead to disruptive selection on learning rules and, potentially, to the evolution of genetic polymorphisms. Thus, we show how reinforcement learning in social contexts can be a driver of evolutionary diversification. In addition, we consider the evolution of ability in our games, showing that learning can also drive disruptive selection on the ability to perform a task.

Unpredictable benefits of social information can lead to the evolution of individual differences in social learning

Human ecological success is often attributed to our capacity for social learning, which facilitates the spread of adaptive behaviours through populations. All humans rely on social learning to acquire culture, but there is substantial variation across societies, between individuals and over developmental time. However, it is unclear why these differences exist. Here, we present an evolutionary model showing that individual variation in social learning can emerge if the benefits of social learning are unpredictable. Unpredictability selects for flexible developmental programmes that allow individuals to update their reliance on social learning based on previous experiences. This developmental flexibility, in turn, causes some individuals in a population to end up consistently relying more heavily on social learning than others. We demonstrate this core evolutionary mechanism across three scenarios of increasing complexity, investigating the impact of different sources of uncertainty about the usefulness of social learning. Our results show how evolution can shape how individuals learn to learn from others, with potentially profound effects on cultural diversity.

Evolution of reciprocity with limited payoff memory

Direct reciprocity is a mechanism for the evolution of cooperation in repeated social interactions. According to the literature, individuals naturally learn to adopt conditionally cooperative strategies if they have multiple encounters with their partner. Corresponding models have greatly facilitated our understanding of cooperation, yet they often make strong assumptions on how individuals remember and process payoff information. For example, when strategies are updated through social learning, it is commonly assumed that individuals compare their average payoffs. This would require them to compute (or remember) their payoffs against everyone else in the population. To understand how more realistic constraints influence direct reciprocity, we consider the evolution of conditional behaviours when individuals learn based on more recent experiences. Even in the most extreme case that they only take into account their very last interaction, we find that cooperation can still evolve. However, such individuals adopt less generous strategies, and they cooperate less often than in the classical setup with average payoffs. Interestingly, once individuals remember the payoffs of two or three recent interactions, cooperation rates quickly approach the classical limit. These findings contribute to a literature that explores which kind of cognitive capabilities are required for reciprocal cooperation. While our results suggest that some rudimentary form of payoff memory is necessary, it suffices to remember a few interactions.

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.

Cultural evolution: A review of theoretical challenges

The rapid growth of cultural evolutionary science, its expansion into numerous fields, its use of diverse methods, and several conceptual problems have outpaced corollary developments in theory and philosophy of science. This has led to concern, exemplified in results from a recent survey conducted with members of the Cultural Evolution Society, that the field lacks 'knowledge synthesis', is poorly supported by 'theory', has an ambiguous relation to biological evolution and uses key terms (e.g. 'culture', 'social learning', 'cumulative culture') in ways that hamper operationalization in models, experiments and field studies. Although numerous review papers in the field represent and categorize its empirical findings, the field's theoretical challenges receive less critical attention even though challenges of a theoretical or conceptual nature underlie most of the problems identified by Cultural Evolution Society members. Guided by the heterogeneous 'grand challenges' emergent in this survey, this paper restates those challenges and adopts an organizational style requisite to discussion of them. The paper's goal is to contribute to increasing conceptual clarity and theoretical discernment around the most pressing challenges facing the field of cultural evolutionary science. It will be of most interest to cultural evolutionary scientists, theoreticians, philosophers of science and interdisciplinary researchers.

Earth Systems to Anthropocene Systems: An Evolutionary, System-of-Systems, Convergence Paradigm for Interdependent Societal Challenges

Humans have made profound changes to the Earth. The resulting societal challenges of the Anthropocene (e.g., climate change and impacts, renewable energy, adaptive infrastructure, disasters, pandemics, food insecurity, and biodiversity loss) are complex and systemic, with causes, interactions, and consequences that cascade across a globally connected system of systems. In this Critical Review, we turn to our "origin story" for insight, briefly tracing the formation of the Universe and the Earth, the emergence of life, the evolution of multicellular organisms, mammals, primates, and humans, as well as the more recent societal transitions involving agriculture, urbanization, industrialization, and computerization. Focusing on the evolution of the Earth, genetic evolution, the evolution of the brain, and cultural evolution, which includes technological evolution, we identify a nested evolutionary sequence of geophysical, biophysical, sociocultural, and sociotechnical systems, emphasizing the causal mechanisms that first formed, and then transformed, Earth systems into Anthropocene systems. Describing how the Anthropocene systems coevolved, and briefly illustrating how the ensuing societal challenges became tightly integrated across multiple spatial, temporal, and organizational scales, we conclude by proposing an evolutionary, system-of-systems, convergence paradigm for the entire family of interdependent societal challenges of the Anthropocene.

What Makes Inventions Become Traditions?

Although anthropology was the first academic discipline to investigate cultural change, many other disciplines have made noteworthy contributions to understanding what influences the adoption of new behaviors. Drawing on a broad, interdisciplinary literature covering both humans and nonhumans, we examine ( a) which features of behavioral traits make them more transmissible, ( b) which individual characteristics of inventors promote copying of their inventions, ( c) which characteristics of individuals make them more prone to adopting new behaviors, ( d) which characteristics of dyadic relationships promote cultural transmission, ( e) which properties of groups (e.g., network structures) promote transmission of traits, and ( f) which characteristics of groups promote retention, rather than extinction, of cultural traits. One of anthropology's strengths is its readiness to adopt and improve theories and methods from other disciplines, integrating them into a more holistic approach; hence, we identify approaches that might be particularly useful to biological and cultural anthropologists, and knowledge gaps that should be filled.

Tempo and Mode in Cultural Macroevolution

Evolutionary scientists studying social and cultural evolution have proposed a multitude of mechanisms by which cultural change can be effected. In this article we discuss two influential ideas from the theory of biological evolution that can inform this debate: the contrast between the micro- and macro-evolution, and the distinction between the tempo and mode of evolution. We add the empirical depth to these ideas by summarizing recent results from the analyses of data on past societies in Seshat: Global History Databank. Our review of these results suggests that the tempo (rates of change, including their acceleration and deceleration) of cultural macroevolution is characterized by periods of apparent stasis interspersed by rapid change. Furthermore, when we focus on large-scale changes in cultural traits of whole groups, the most important macroevolutionary mode involves inter-polity interactions, including competition and warfare, but also cultural exchange and selective imitation; mechanisms that are key components of cultural multilevel selection (CMLS) theory.

The evolution of social learning as phenotypic cue integration

Most analyses of the origins of cultural evolution focus on when and where social learning prevails over individual learning, overlooking the fact that there are other developmental inputs that influence phenotypic fit to the selective environment. This raises the question of how the presence of other cue 'channels' affects the scope for social learning. Here, we present a model that considers the simultaneous evolution of (i) multiple forms of social learning (involving vertical or horizontal learning based on either prestige or conformity biases) within the broader context of other evolving inputs on phenotype determination, including (ii) heritable epigenetic factors, (iii) individual learning, (iv) environmental and cascading maternal effects, (v) conservative bet-hedging, and (vi) genetic cues. In fluctuating environments that are autocorrelated (and hence predictable), we find that social learning from members of the same generation (horizontal social learning) explains the large majority of phenotypic variation, whereas other cues are much less important. Moreover, social learning based on prestige biases typically prevails in positively autocorrelated environments, whereas conformity biases prevail in negatively autocorrelated environments. Only when environments are unpredictable or horizontal social learning is characterized by an intrinsically low information content, other cues such as conservative bet-hedging or vertical prestige biases prevail. This article is part of the theme issue 'Foundations of cultural evolution'.