Why copy others? Insights from the social learning strategies tournament

The dynamics of casual groups can keep free-riders at bay

Understanding the conditions for maintaining cooperation in groups of unrelated individuals despite the presence of non-cooperative members is a major research topic in contemporary biological, sociological, and economic theory. The N-person snowdrift game models the type of social dilemma where cooperative actions are costly, but there is a reward for performing them. We study this game in a scenario where players move between play groups following the casual group dynamics, where groups grow by recruiting isolates and shrink by losing individuals who then become isolates. This describes the size distribution of spontaneous human groups and also the formation of sleeping groups in monkeys. We consider three scenarios according to the probability of isolates joining a group. We find that for appropriate choices of the cost-benefit ratio of cooperation and the aggregation-disaggregation ratio in the formation of casual groups, free-riders can be completely eliminated from the population. If individuals are more attracted to large groups, we find that cooperators persist in the population even when the mean group size diverges. We also point out the remarkable similarity between the replicator equation approach to public goods games and the trait group formulation of structured demes.

Social demonstration of colour preference improves the learning of associated demonstrated actions

We studied how different types of social demonstration improve house sparrows' (Passer domesticus) success in solving a foraging task that requires both operant learning (opening covers) and discrimination learning (preferring covers of the rewarding colour). We provided learners with either paired demonstration (of both cover opening and colour preference), action-only demonstration (of opening white covers only), or no demonstration (a companion bird eating without covers). We found that sparrows failed to learn the two tasks with no demonstration, and learned them best with a paired demonstration. Interestingly, the action of cover opening was learned faster with paired rather than action-only demonstration despite being equally demonstrated in both. We also found that only with paired demonstration, the speed of operant (action) learning was related to the demonstrator's level of activity. Colour preference (i.e. discrimination learning) was eventually acquired by all sparrows that learned to open covers, even without social demonstration of colour preference. Thus, adding a demonstration of colour preference was actually more important for operant learning, possibly as a result of increasing the similarity between the demonstrated and the learned tasks, thereby increasing the learner's attention to the actions of the demonstrator. Giving more attention to individuals in similar settings may be an adaptive strategy directing social learners to focus on ecologically relevant behaviours and on tasks that are likely to be learned successfully.

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.

Environmental harshness does not affect the propensity for social learning in great tits, Parus major

According to the harsh environment hypothesis, natural selection should favour cognitive mechanisms to overcome environmental challenges. Tests of this hypothesis to date have largely focused on asocial learning and memory, thus failing to account for the spread of information via social means. Tests in specialized food-hoarding birds have shown strong support for the effects of environmental harshness on both asocial and social learning. Whether the hypothesis applies to non-specialist foraging species remains largely unexplored. We evaluated the relative importance of social learning across a known harshness gradient by testing generalist great tits, Parus major, from high (harsh)- and low (mild)-elevation populations in two social learning tasks. We showed that individuals use social learning to find food in both colour-associative and spatial foraging tasks and that individuals differed consistently in their use of social learning. However, we did not detect a difference in the use or speed of implementing socially observed information across the elevational gradient. Our results do not support predictions of the harsh environment hypothesis suggesting that context-dependent costs and benefits as well as plasticity in the use of social information may play an important role in the use of social learning across environments. Finally, this study adds to the accumulating evidence that the harsh environment hypothesis appears to have more pronounced effects on specialists compared to generalist species.

Signals of belonging: emergence of signalling norms as facilitators of trust and parochial cooperation

Mechanisms of social control reinforce norms that appear harmful or wasteful, such as mutilation practises or extensive body tattoos. We suggest such norms arise to serve as signals that distinguish between ingroup 'friends' and outgroup 'foes', facilitating parochial cooperation. Combining insights from research on signalling and parochial cooperation, we incorporate a trust game with signalling in an agent-based model to study the dynamics of signalling norm emergence in groups with conflicting interests. Our results show that costly signalling norms emerge from random acts of signalling in minority groups that benefit most from parochial cooperation. Majority groups are less likely to develop costly signalling norms. Yet, norms that prescribe sending costless group identity signals can easily emerge in groups of all sizes-albeit, at times, at the expense of minority group members. Further, the dynamics of signalling norm emergence differ across signal costs, relative group sizes, and levels of ingroup assortment. Our findings provide theoretical insights into norm evolution in contexts where groups develop identity markers in response to environmental challenges that put their interests at odds with the interests of other groups. Such contexts arise in zones of ethnic conflict or during contestations of existing power relations. This article is part of the theme issue 'Social norm change: drivers and consequences'.

Maintaining Transient Diversity Is a General Principle for Improving Collective Problem Solving

Humans regularly solve complex problems in cooperative teams. A wide range of mechanisms have been identified that improve the quality of solutions achieved by those teams on reaching consensus. We argue that many of these mechanisms work via increasing the transient diversity of solutions while the group attempts to reach a consensus. These mechanisms can operate at the level of individual psychology (e.g., behavioral inertia), interpersonal communication (e.g., transmission noise), or group structure (e.g., sparse social networks). Transient diversity can be increased by widening the search space of possible solutions or by slowing the diffusion of information and delaying consensus. All of these mechanisms increase the quality of the solution at the cost of increased time to reach it. We review specific mechanisms that facilitate transient diversity and synthesize evidence from both empirical studies and diverse formal models-including multiarmed bandits, NK landscapes, cumulative-innovation models, and evolutionary-transmission models. Apparent exceptions to this principle occur primarily when problems are sufficiently simple that they can be solved by mere trial and error or when the incentives of team members are insufficiently aligned. This work has implications for our understanding of collective intelligence, problem solving, innovation, and cumulative cultural evolution.

Observational learning of threat-related attentional bias

Attentional bias to threat has been almost exclusively examined after participants experienced repeated pairings between a conditioned stimulus (CS) and an aversive unconditioned stimulus (US). This study aimed to determine whether threat-related attentional capture can result from observational learning, when participants acquire knowledge of the aversive qualities of a stimulus without themselves experiencing aversive outcomes. Non-clinical young-adult participants (N = 38) first watched a video of an individual (the demonstrator) performing a Pavlovian conditioning task in which one colour was paired with shock (CS+) and another colour was neutral (CS-). They then carried out visual search for a shape-defined target. Oculomotor measures evidenced an attentional bias toward the CS+ colour, suggesting that threat-related attentional capture can ensue from observational learning. Exploratory analyses also revealed that this effect was positively correlated with empathy for the demonstrator. Our findings extend empirical and theoretical knowledge about threat-driven attention and provide valuable insights to better understand the formation of anxiety disorders.

Network structure shapes the impact of diversity in collective learning

It is widely believed that diversity arising from different skills enhances the performance of teams, and in particular, their ability to learn and innovate. However, diversity has also been associated with negative effects on the communication and coordination within collectives. Yet, despite the importance of diversity as a concept, we still lack a mechanistic understanding of how its impact is shaped by the underlying social network. To fill this gap, we model skill diversity within a simple model of collective learning and show that its effect on collective performance differs depending on the complexity of the task and the network density. In particular, we find that diversity consistently impairs performance in simple tasks. In contrast, in complex tasks, link density modifies the effect of diversity: while homogeneous populations outperform diverse ones in sparse networks, the opposite is true in dense networks, where diversity boosts collective performance. Our findings also provide insight on how to forge teams in an increasingly interconnected world: the more we are connected, the more we can benefit from diversity to solve complex problems.

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.

Resampling reduces bias amplification in experimental social networks

Large-scale social networks are thought to contribute to polarization by amplifying people's biases. However, the complexity of these technologies makes it difficult to identify the mechanisms responsible and evaluate mitigation strategies. Here we show under controlled laboratory conditions that transmission through social networks amplifies motivational biases on a simple artificial decision-making task. Participants in a large behavioural experiment showed increased rates of biased decision-making when part of a social network relative to asocial participants in 40 independently evolving populations. Drawing on ideas from Bayesian statistics, we identify a simple adjustment to content-selection algorithms that is predicted to mitigate bias amplification by generating samples of perspectives from within an individual's network that are more representative of the wider population. In two large experiments, this strategy was effective at reducing bias amplification while maintaining the benefits of information sharing. Simulations show that this algorithm can also be effective in more complex networks.

Learning few-shot imitation as cultural transmission

Cultural transmission is the domain-general social skill that allows agents to acquire and use information from each other in real-time with high fidelity and recall. It can be thought of as the process that perpetuates fit variants in cultural evolution. In humans, cultural evolution has led to the accumulation and refinement of skills, tools and knowledge across generations. We provide a method for generating cultural transmission in artificially intelligent agents, in the form of few-shot imitation. Our agents succeed at real-time imitation of a human in novel contexts without using any pre-collected human data. We identify a surprisingly simple set of ingredients sufficient for generating cultural transmission and develop an evaluation methodology for rigorously assessing it. This paves the way for cultural evolution to play an algorithmic role in the development of artificial general intelligence.

A normative theory of luck

Psychologists have identified heuristics and biases that can cause people to make assumptions about factors that contribute to the success of individuals and firms, whose outcomes may have actually resulted primarily from randomness. Yet the interpretation of these biases becomes ambiguous when they represent reasonable cognitive shortcuts that offer certain advantages. This paper addresses this ambiguity by presenting four versions (weak, semi-weak, semi-strong, strong) of a normative theory of luck that integrates insights from psychology with the chance model approach to predict the circumstances under which performance non-monotonicity occurs: higher performance may not only indicate greater luck, but also lower expected merit or quality. The semi-strong version is illustrated by examining the decoupling of citations of academic publications and their impact, illuminating when higher citations indicate lower quality. We conclude by discussing the broader implications of a normative theory of luck, emphasizing strategies to address situations where people mistake luck for skill.

Flexible social inference facilitates targeted social learning when rewards are not observable

Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that social inference capacities may help bridge this gap, allowing individuals to update their beliefs about others' underlying knowledge and success from observable trajectories of behaviour. We compared our social inference model against simpler heuristics in three studies of human behaviour in a collective-sensing task. Experiment 1 demonstrated that average performance improved as a function of group size at a rate greater than predicted by heuristic models. Experiment 2 introduced artificial agents to evaluate how individuals selectively rely on social information. Experiment 3 generalized these findings to a more complex reward landscape. Taken together, our findings provide insight into the relationship between individual social cognition and the flexibility of collective behaviour.

Social learning and memory

The adaptability of human populations to changing environments is often attributed to the human capacity for social learning, innovation, and culture. In rapidly changing environments, it has been shown that maintaining high levels of cultural variation is beneficial because it allows for efficient adaptation. However, in many theoretical models, a high level of cultural variation also implies that a large amount of useless and perhaps detrimental information must be maintained and used, leading to lower population fitness in general. Here, we begin to investigate this often conflicting relationship between adaptation and cultural variation. We explicitly allow for the interplay between social learning and environmental variability, alongside the capacity for "memory," i.e., the storage, retrieval, and forgetting of information. Here, memory allows individuals to retain unexpressed cultural variation, which does not directly impact adaptation. We show that this capacity for memory facilitates the evolution of social learning across a broader range of circumstances than previously thought. Results from this analysis may help to establish whether and when memory should be incorporated into cultural evolutionary models focused on questions of adaptation.

Monkeys who experience more feeding competition utilize social information to learn foraging skills faster

Animals must learn foraging skills to successfully survive and reproduce but the sources of interindividual variation in learning are poorly understood. For example, there is little consensus on the role motivation plays, even though it is a key factor impacting learning outcomes in humans. Here, we conduct a field experiment on a wild primate to investigate whether an individual's vulnerability to feeding competition impacts their motivation to learn a beneficial foraging technique. We provided a group of monkeys with a food reward (i.e., a half banana) that needed to be retrieved from a box. The monkeys discovered an efficient technique that consistently allowed them to retrieve the banana quickly, decreasing the risk of food loss to competitors. We found that individuals who frequently experienced feeding competition learned this efficient technique significantly faster than individuals who rarely foraged in the presence of a dominant competitor. They appeared to use social learning to learn faster as they were more attentive to the handling techniques others used and improved their foraging skills after opportunities to observe a skilled demonstrator. These findings support that an individual's vulnerability to feeding competition impacts their motivation to learn foraging skills that reduce food loss to competitors.

The form of uncertainty affects selection for social learning

Social learning is a critical adaptation for dealing with different forms of variability. Uncertainty is a severe form of variability where the space of possible decisions or probabilities of associated outcomes are unknown. We identified four theoretically important sources of uncertainty: temporal environmental variability; payoff ambiguity; selection-set size; and effective lifespan. When these combine, it is nearly impossible to fully learn about the environment. We develop an evolutionary agent-based model to test how each form of uncertainty affects the evolution of social learning. Agents perform one of several behaviours, modelled as a multi-armed bandit, to acquire payoffs. All agents learn about behavioural payoffs individually through an adaptive behaviour-choice model that uses a softmax decision rule. Use of vertical and oblique payoff-biased social learning evolved to serve as a scaffold for adaptive individual learning - they are not opposite strategies. Different types of uncertainty had varying effects. Temporal environmental variability suppressed social learning, whereas larger selection-set size promoted social learning, even when the environment changed frequently. Payoff ambiguity and lifespan interacted with other uncertainty parameters. This study begins to explain how social learning can predominate despite highly variable real-world environments when effective individual learning helps individuals recover from learning outdated social information.

Social Learning versus Individual Learning in the Division of Labour

Division of labour, or the differentiation of the individuals in a collective across tasks, is a fundamental aspect of social organisations, such as social insect colonies. It allows for efficient resource use and improves the chances of survival for the entire collective. The emergence of large inactive groups of individuals in insect colonies sometimes referred to as laziness, has been a puzzling and hotly debated division-of-labour phenomenon in recent years that is counter to the intuitive notion of effectiveness. It has previously been shown that inactivity can be explained as a by-product of social learning without the need to invoke an adaptive function. While highlighting an interesting and important possibility, this explanation is limited because it is not yet clear whether the relevant aspects of colony life are governed by social learning. In this paper, we explore the two fundamental types of behavioural adaptation that can lead to a division of labour, individual learning and social learning. We find that inactivity can just as well emerge from individual learning alone. We compare the behavioural dynamics in various environmental settings under the social and individual learning assumptions, respectively. We present individual-based simulations backed up by analytic theory, focusing on adaptive dynamics for the social paradigm and cross-learning for the individual paradigm. We find that individual learning can induce the same behavioural patterns previously observed for social learning. This is important for the study of the collective behaviour of social insects because individual learning is a firmly established paradigm of behaviour learning in their colonies. Beyond the study of inactivity, in particular, the insight that both modes of learning can lead to the same patterns of behaviour opens new pathways to approach the study of emergent patterns of collective behaviour from a more generalised perspective.

Superhuman artificial intelligence can improve human decision-making by increasing novelty

How will superhuman artificial intelligence (AI) affect human decision-making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move decisions made by professional Go players over the past 71 y (1950 to 2021). To address the first question, we use a superhuman AI program to estimate the quality of human decisions across time, generating 58 billion counterfactual game patterns and comparing the win rates of actual human decisions with those of counterfactual AI decisions. We find that humans began to make significantly better decisions following the advent of superhuman AI. We then examine human players' strategies across time and find that novel decisions (i.e., previously unobserved moves) occurred more frequently and became associated with higher decision quality after the advent of superhuman AI. Our findings suggest that the development of superhuman AI programs may have prompted human players to break away from traditional strategies and induced them to explore novel moves, which in turn may have improved their decision-making.

When should bees be flower constant? An agent-based model highlights the importance of social information and foraging conditions

Many bee species show flower constancy, that is, a tendency to visit flowers of one type during a foraging trip. Flower constancy is important for plant reproduction, but the benefits of constancy to bees is unclear. Social bees, which often use communication about food sources, show particularly strong flower constancy. We aimed to better understand the benefits of flower constancy in social bees and how these benefits depend on foraging conditions. We hypothesised that sharing social information increases the benefits of flower constancy because social foragers share information selectively about high-quality food sources, thereby reducing the need to sample alternatives. We developed an agent-based model that allowed us to simulate bee colonies with and without communication and flower constancy in different foraging environments. By varying key environmental parameters, such as food source numbers and reward size, we explored how the costs and benefits of flower constancy depend on the foraging landscape. Flower constancy alone performed poorly in all environments, while indiscriminate flower choice was often the most successful strategy. However, communication improved the performance of flower constant colonies considerably in most environments. This combination was particularly successful when high-quality food sources were abundant and competition was weak. Our findings help explain why social bees tend to be more flower constant than solitary bees and suggest that flower constancy can be an adaptive strategy in social bees. Simulations suggest that anthropogenic changes of foraging landscapes will have different effects on the foraging performance of bees that vary in flower constancy.

Beyond collective intelligence: Collective adaptation

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

In no uncertain terms: Group cohesion did not affect exploration and group decision making under low uncertainty

Group decision making under uncertainty often requires groups to balance exploration of their environment with exploitation of the seemingly best option. In order to succeed at this collective induction, groups need to merge the knowledge of all group members and combine goal-oriented and social motivations (i.e., group cohesion). This paper presents three studies that investigate whether more cohesive groups perform worse at collective induction tasks as they spend less time exploring possible options. Study 1 simulates group decision making with the ε-greedy algorithm in order to identify suitable manipulations of group cohesion and investigate how differing exploration lengths can affect outcomes of group decisions. Study 2 (N = 108, 18 groups á 6 participants) used an experimental manipulation of group cohesion in a simple card choice task to investigate how group cohesion might affect group decision making when only limited social information is available. Study 3 (N = 96, 16 groups á 6 participants) experimentally manipulated group cohesion and used the HoneyComb paradigm, a movement-based group experiment platform, to investigate which group processes would emerge during decision making and how these processes would affect the relationships between group cohesion, exploration length, and group decision making. Study 1 found that multiplicative cohesion rewards have detrimental effects on group decision making, while additive group rewards could ameliorate negative effects of the cohesion reward, especially when reported separately from task rewards. Additionally, exploration length was found to profoundly affect decision quality. Studies 2 and 3 showed that groups could identify the best reward option successfully, regardless of group cohesion manipulation. This effect is interpreted as a ceiling effect as the decision task was likely too easy to solve. Study 3 identified that spatial group cohesion on the playing field correlated with self-reported entitativity and leader-/followership emerged spontaneously in most groups and correlated with self-reported perceptions of leader-/followership in the game. We discuss advantages of simulation studies, possible adaptations to the ε-greedy algorithm, and methodological aspects of measuring behavioral group cohesion and leadership to inform empirical studies investigating group decision making under uncertainty.

Uncertainty in individual risk judgments associates with vulnerability and curtailed climate adaptation

Risk assessments are key for the effective management of potential environmental threats. Across probabilistic phenomena, climate change is an exemplar of paramount uncertainties. These uncertainties have been embraced in supporting governments' decisions; yet receive scarce attention when studying individual behavior. Analyzing a survey conducted in the USA, China, Indonesia, and the Netherlands (N=6242), we explore socio-economic, psychological, and behavioral differences between individuals who can subjectively assess risks, and those who are risk-uncertain. We find that risk-uncertain individuals are more likely to belong to societal subgroups classically considered as vulnerable, and have reduced capacities and intentions to adapt to hazards-specifically floods. The distinctions between risk-aware and risk-uncertain individuals indicate that ignoring differences in individuals' capacity to assess risks could amount to persistent vulnerability and undermine climate-resilience efforts. While we use floods emblematically, these finding have consequences for the standard practice of dropping or bootstrapping uncertain responses, irrespective of the hazard, with implications for environmental management.

Indigenous Knowledge: Revitalizing Everlasting Relationships between Alaska Natives and Sled Dogs to Promote Holistic Wellbeing

INTRODUCTION

Indigenous peoples have documented their culture's history in oral stories, revealing lessons about holistic relationships fostering perseverance. Despite vast differences in time, relationships and stories are equally important today. Athabascans retain their values, life skills, and wellness through cultural practices. Creating opportunities for youths to learn through reciprocal relationships increases wellness in Indigenous communities, highlighting the significance of community-developed programs that connect youths to their place and culture.

METHOD

Athabascan youths in rural Alaska get hands-on experience and Elder mentorship working with sled dogs in the Frank Attla Youth and Sled Dog Care-Mushing Program (FAYSDP). Through a community-based participatory research partnership with the community of Huslia and Jimmy Huntington School, we examined how FAYSDP affects youths, and how relationships within culture and land promote wellbeing. Fifteen middle and high-school youths shared their perspectives on how FAYSDP impacts them and their community using photovoice and digital storytelling. Nineteen adults contributed their perspectives in focus groups. We used emerging themes (inductive) and Athabascan cultural values and elements of social capital (deductive approaches) to analyze the qualitative data.

RESULTS

Findings illustrate how FAYSDP promotes wellbeing by empowering youths to apply what they learn to generate their own knowledge, while centering communities around culturally significant practices such as dog mushing. It connects youths to their home and their cultural values, using dogs as the driving force to bridge generations and foster youth wellness.

DISCUSSION

We discuss implications for community-based programs that engage Elders as teachers and the land as their classroom to promote youth holistic wellness.

The importance of thinking about the future in culture and cumulative cultural evolution

Thinking about possibilities plays a critical role in the choices humans make throughout their lives. Despite this, the influence of individuals' ability to consider what is possible on culture has been largely overlooked. We propose that the ability to reason about future possibilities or prospective cognition, has consequences for cultural change, possibly facilitating the process of cumulative cultural evolution. In particular, by considering potential future costs and benefits of specific behaviours, prospective cognition may lead to a more flexible use of cultural behaviours. In species with limited planning abilities, this may lead to the development of cultures that promote behaviours with future benefits, circumventing this limitation. Here, we examine these ideas from a comparative perspective, considering the relationship between human and nonhuman assessments of future possibilities and their cultural capacity to invent new solutions and improve them over time. Given the methodological difficulties of assessing prospective cognition across species, we focus on planning, for which we have the most data in other species. Elucidating the role of prospective cognition in culture will help us understand the variability in when and how we see culture expressed, informing ongoing debates, such as that surrounding which social learning mechanisms underlie culture. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.

The experimental evolution of human culture: flexibility, fidelity and environmental instability

The past 2 Myr have seen both unprecedented environmental instability and the evolution of the human capacity for complex culture. This, along with the observation that cultural evolution occurs faster than genetic evolution, has led to the suggestion that culture is an adaptation to an unstable environment. We test this hypothesis by examining the ability of human social learning to respond to environmental changes. We do this by inserting human participants (n = 4800) into evolutionary simulations with a changing environment while varying the social information available to individuals across five conditions. We find that human social learning shows some signs of adaptation to environmental instability, including critical social learning, the adoption of up-and-coming traits and, unexpectedly, contrariness. However, these are insufficient to avoid significant fitness declines when the environment changes, and many individuals are highly conformist, which exacerbates the fitness effects of environmental change. We conclude that human social learning reflects a compromise between the competing needs for flexibility to accommodate environmental change and fidelity to accurately transmit valuable cultural information.

A cultural evolutionary theory that explains both gradual and punctuated change

Cumulative cultural evolution (CCE) occurs among humans who may be presented with many similar options from which to choose, as well as many social influences and diverse environments. It is unknown what general principles underlie the wide range of CCE dynamics and whether they can all be explained by the same unified paradigm. Here, we present a scalable evolutionary model of discrete choice with social learning, based on a few behavioural science assumptions. This paradigm connects the degree of transparency in social learning to the human tendency to imitate others. Computer simulations and quantitative analysis show the interaction of three primary factors—information transparency, popularity bias and population size—drives the pace of CCE. The model predicts a stable rate of evolutionary change for modest degrees of popularity bias. As popularity bias grows, the transition from gradual to punctuated change occurs, with maladaptive subpopulations arising on their own. When the popularity bias gets too severe, CCE stops. This provides a consistent framework for explaining the rich and complex adaptive dynamics taking place in the real world, such as modern digital media.

Biological adaptations for cultural transmission?

According to several interlinked and influential lines of argument, human minds have been shaped by natural selection so as to include biological adaptations with the evolved, naturally selected function to facilitate the transmission of cultural knowledge. This 'cultural minds' hypothesis has proved highly influential, and if it is correct it is a major step forward in understanding how and why humans have survived and prospered in a hugely diverse range of ecologies. It can be contrasted with a 'social minds' hypothesis, according to which cultural transmission occurs as an outcome, but not the biologically evolved function, of social cognition the domain of which is relatively small-group interaction. Here, I critique the cultural minds hypothesis and I argue that the data favour the social minds perspective. Cultural phenomena can clearly emerge and persist over time without cognitive adaptations for cultural transmission. Overtly intentional communication plays an especially pivotal role.

Hybrid social learning in human-algorithm cultural transmission

Humans are impressive social learners. Researchers of cultural evolution have studied the many biases shaping cultural transmission by selecting who we copy from and what we copy. One hypothesis is that with the advent of superhuman algorithms a hybrid type of cultural transmission, namely from algorithms to humans, may have long-lasting effects on human culture. We suggest that algorithms might show (either by learning or by design) different behaviours, biases and problem-solving abilities than their human counterparts. In turn, algorithmic-human hybrid problem solving could foster better decisions in environments where diversity in problem-solving strategies is beneficial. This study asks whether algorithms with complementary biases to humans can boost performance in a carefully controlled planning task, and whether humans further transmit algorithmic behaviours to other humans. We conducted a large behavioural study and an agent-based simulation to test the performance of transmission chains with human and algorithmic players. We show that the algorithm boosts the performance of immediately following participants but this gain is quickly lost for participants further down the chain. Our findings suggest that algorithms can improve performance, but human bias may hinder algorithmic solutions from being preserved. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Hybrid social learning in human-algorithm cultural transmission

Humans are impressive social learners. Researchers of cultural evolution have studied the many biases shaping cultural transmission by selecting who we copy from and what we copy. One hypothesis is that with the advent of superhuman algorithms a hybrid type of cultural transmission, namely from algorithms to humans, may have long-lasting effects on human culture. We suggest that algorithms might show (either by learning or by design) different behaviours, biases and problem-solving abilities than their human counterparts. In turn, algorithmic-human hybrid problem solving could foster better decisions in environments where diversity in problem-solving strategies is beneficial. This study asks whether algorithms with complementary biases to humans can boost performance in a carefully controlled planning task, and whether humans further transmit algorithmic behaviours to other humans. We conducted a large behavioural study and an agent-based simulation to test the performance of transmission chains with human and algorithmic players. We show that the algorithm boosts the performance of immediately following participants but this gain is quickly lost for participants further down the chain. Our findings suggest that algorithms can improve performance, but human bias may hinder algorithmic solutions from being preserved. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Success-biased social learning in a one-consumer, two-resource model

Previous analyses have predicted that social learning should not evolve in a predator-prey system. Here we examine whether success-biased social learning, by which social learners copy successful demonstrators, allows social learning by foragers to evolve. We construct a one-predator, two-prey system in which foragers must learn how to feed on depletable prey populations in an environment where foraging information can be difficult to obtain individually. We analyze two models in which social learning is success-biased: in the first, individual learning does not depend on the resource dynamics, and in the second model it depends on the relative frequency of the resource. Unlike previous results, we find that social learning does not cause predators to over-harvest one type of prey over the other. Furthermore, increasing the probability of social learning increases the probability of learning a successful foraging behavior, especially when individually learned information tends to be inaccurate. Whereas social learning does not evolve among individual learners in the first model, the assumption of resource-dependent learning in the second model allows a mutant with an increased probability of social learning to spread through the forager population.

Sensitivity to Evidential Dependencies in Judgments Under Uncertainty

According to Bayesian models of judgment, testimony from independent informants has more evidential value than dependent testimony. Three experiments investigated learners' sensitivity to this distinction. Each experiment used a social version of the balls‐and‐urns task, in which participants judged which of two urns was the most likely source of evidence presented by multiple informants. Informants either provided independent testimony based solely on their own observations or dependent‐sequential testimony that considered the testimonies of previous informants. Although participants updated their beliefs with additional evidence, this updating was generally insensitive to evidential dependency (Experiments 1 and 2). A notable exception was when individuals were separated according to their beliefs about the relative value of independent and sequential evidence. Those who viewed independent evidence as having greater value subsequently gave more weight to independent testimony in the balls‐and‐urns task (Experiment 3), in line with the predictions of a Bayesian model. Our findings suggest that only a minority of individuals conform to Bayesian predictions in the relative weighting of independent and dependent evidence in judgments under uncertainty.

Social Prevalence Is Rationally Integrated in Belief Updating

People rely on social information to inform their beliefs. We ask whether and to what degree the perceived prevalence of a belief influences belief adoption. We present the results of two experiments that show how increases in a person’s estimated prevalence of a belief led to increased endorsement of said belief. Belief endorsement rose when impressions of the belief’s prevalence were increased and when initial beliefs were uncertain, as predicted by a Bayesian cue integration framework. Thus, people weigh social information rationally. An implication of these results is that social engagement metrics that prompt inflated prevalence estimates in users risk increasing the believability and adoption of viral misinformation posts.

Curiosity for information predicts wellbeing mediated by loneliness during COVID-19 pandemic

The COVID-19 pandemic confronted humans with high uncertainty and lockdowns, which severely disrupted people’s daily social and health lifestyles, enhanced loneliness, and reduced well-being. Curiosity and information-seeking are central to behavior, fostering well-being and adaptation in changing environments. They may be particularly important to maintain well-being during the pandemic. Here, we investigated which motives drive information-seeking, and whether and how curiosity and information-seeking related to well-being and mood (excitement, anxiety). Additionally, we tested whether daily diet contributed to this relationship during lockdown. Participants (N = 183) completed questionnaires measuring curiosity, information-seeking, social and mental health. Using a smartphone app, participants submitted their daily food intake and lifestyle ratings for a week. We found participants had highest motivation to seek positive (vs. negative) information, concerning themselves more than others. Both trait curiosity and information-seeking predicted higher well-being, mediated by loneliness. Trait curiosity also predicted well-being and excitement days later. Considering diet, participants with lower trait curiosity ate food containing more tyrosine (i.e., dopamine precursor). Furthermore, participants consuming food high in sugar reported higher anxiety, which was specifically found in participants with relatively low, but not high, trait curiosity. Taken together, curiosity and information-seeking may benefit well-being and mood in high uncertain and challenging times, by interacting with lifestyle measures (loneliness and nutrition).

Conformist social learning leads to self-organised prevention against adverse bias in risky decision making

Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majority's behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This 'collective behavioural rescue', emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences.

Impact of human capital and financial globalization on environmental degradation in OBOR countries: Critical role of national cultural orientations

As regional economic integration and climate change are among the most important phenomena influencing economic and social sustainability in the modern world, a huge volume of research is directed towards these topics nowadays. The aim of this study is to explore the impact of financial globalization and human capital on environmental degradation in One Belt One Road (OBOR) countries in a cultural context that is largely under-explored in spite of being immensely crucial for fulfilling the United Nations' agenda on climate change mitigation. Owing to the presence of vast cultural differences, we check if the national scores on "Power Distance Index" and "Uncertainty Avoidance" in these countries matter for the environment. To this end, we use the latest and annual data set comprising 31 OBOR countries from 1996 to 2018, and employ panel econometric techniques that effectively deal with the threat of endogeneity. Results show that human capital improves environment while financial globalization deteriorates it. Interestingly, high power distance and uncertainty avoidance can reverse the positive impact of human capital. Similarly, financial globalization is favorable for environment in countries with low power distance and uncertainty avoidance. The findings are robust to the use of alternative specifications. Theoretical underpinnings and implications are discussed arising from the interesting reversal of traditional impacts in different cultural scenarios. Specifically, we recommend a culture of entrepreneurship, innovation, and inclusivity, promoted through increased tolerance towards risk-taking and participative decision-making to reap the benefits of human capital and globalization in improving the environment. Our results have important implications for climate change mitigation endeavors in OBOR countries and understanding the cultural context in this regard. Additionally, our study opens a vast avenue for the related research work in the future.

Individual exploration and selective social learning: balancing exploration-exploitation trade-offs in collective foraging

Search requires balancing exploring for more options and exploiting the ones previously found. Individuals foraging in a group face another trade-off: whether to engage in social learning to exploit the solutions found by others or to solitarily search for unexplored solutions. Social learning can better exploit learned information and decrease the costs of finding new resources, but excessive social learning can lead to over-exploitation and too little exploration for new solutions. We study how these two trade-offs interact to influence search efficiency in a model of collective foraging under conditions of varying resource abundance, resource density and group size. We modelled individual search strategies as Lévy walks, where a power-law exponent (μ) controlled the trade-off between exploitative and explorative movements in individual search. We modulated the trade-off between individual search and social learning using a selectivity parameter that determined how agents responded to social cues in terms of distance and likely opportunity costs. Our results show that social learning is favoured in rich and clustered environments, but also that the benefits of exploiting social information are maximized by engaging in high levels of individual exploration. We show that selective use of social information can modulate the disadvantages of excessive social learning, especially in larger groups and when individual exploration is limited. Finally, we found that the optimal combination of individual exploration and social learning gave rise to trajectories with μ ≈ 2 and provide support for the general optimality of such patterns in search. Our work sheds light on the interplay between individual search and social learning, and has broader implications for collective search and problem-solving.

When does selection favor learning from the old? Social learning in age-structured populations

Culture and demography jointly facilitate flexible human adaptation, yet it still remains unclear how social learning operates in populations with age structure. Here, we present a mathematical model of the evolution of social learning in a population with different age classes. We investigate how demographic processes affect the adaptive value of culture, cultural adaptation and population growth, and identify the conditions that favor learning from older vs. younger individuals. We find that, even with age structure, social learning can evolve without increasing population fitness, i.e., “Rogers’ paradox” still holds. However, a process of “demographic filtering”, together with cultural transmission, can generate cumulative improvements in adaptation levels. We further show that older age classes have higher proportions of adaptive behavior when the environment is stable and adaptive behavior is hard to acquire but important to survival. Through individual-based simulations comparing temporal and spatial variability in the environment, we find a “copy-the-old”-strategy only evolves when social learning is erroneous and the opposite “copy-the-young”-strategy can function as a compromise between individual and social information use. Our results reveal that age structure substantially changes how culture evolves and provide principled empirical expectations about age-biased social learning and the role of demography in cultural adaptation.

Opposition to voluntary and mandated COVID-19 vaccination as a dynamic process: Evidence and policy implications of changing beliefs

The challenge of securing adherence to public health policies is compounded when an emerging threat and a set of unprecedented remedies are not fully understood among the general public. The evolution of citizens’ attitudes toward vaccination during the COVID-19 pandemic offers psychologically and sociologically grounded insights that enrich the conventional incentives- and constraints-based approach to policy design. We thus contribute to a behavioral science of policy compliance during public health emergencies of the kind that we may increasingly face in the future. From early in the pandemic, we have tracked the same individuals, providing a lens into the conditions under which people’s attitudes toward voluntary and mandated vaccinations change, providing essential information for COVID-19 policy not available from cross-section data.

COVID-19 vaccination rates slowed in many countries during the second half of 2021, along with the emergence of vocal opposition, particularly to mandated vaccinations. Who are those resisting vaccination? Under what conditions do they change their minds? Our three-wave representative panel survey from Germany allows us to estimate the dynamics of vaccine opposition, providing the following answers. Without mandates, it may be difficult to reach and to sustain the near-universal level of repeated vaccinations apparently required to contain the Delta, Omicron, and likely subsequent variants. But mandates substantially increase opposition to vaccination. We find that few were opposed to voluntary vaccination in all three waves of the survey. They are just 3.3% of our panel, a number that we demonstrate is unlikely to be the result of response error. In contrast, the fraction consistently opposed to enforced vaccinations is 16.5%. Under both policies, those consistently opposed and those switching from opposition to supporting vaccination are sociodemographically virtually indistinguishable from other Germans. Thus, the mechanisms accounting for the dynamics of vaccine attitudes may apply generally across societal groups. What differentiates them from others are their beliefs about vaccination effectiveness, their trust in public institutions, and whether they perceive enforced vaccination as a restriction on their freedom. We find that changing these beliefs is both possible and necessary to increase vaccine willingness, even in the case of mandates. An inference is that well-designed policies of persuasion and enforcement will be complementary, not alternatives.

Wahab N. Investigating the level and determinants of hibah knowledge: a study among Muslims in Kedah, Malaysia

Purpose

This paper aims to explore the level of hibah knowledge among Muslims in Kedah and investigate its determinants, consisting of education level, education stream, religiosity, social influence and social media.

Design/methodology/approach

This study is quantitative in nature. Questionnaires were distributed to collect data from Muslims in Alor Setar, Kedah. In total, 195 questionnaires were collected and data were analyzed using descriptive analysis, correlation analysis and multiple regression analysis.

Findings

The study finds that Muslims in Alor Setar, Kedah have good knowledge of hibah. Further, education stream, religiosity, social influence and social media were identified as significant factors that influence their knowledge of hibah.

Research limitations/implications

The first limitation is its narrow focus in surveying Muslims only in Alor Setar, Kedah. The second limitation is the limited number of determinants used in investigating hibah knowledge among Muslims and the techniques used in analyzing the data. Despite these limitations, the study’s findings provide invaluable insights into the factors influencing hibah knowledge among Muslims in Alor Setar, Kedah.

Practical implications

This study provides insights regarding the significant personal factors and environmental factors to increase Muslims’ knowledge of hibah. The link between the Islamic education stream and hibah knowledge provides a clear indication that Islamic education can curb the economic problems caused by the substantial amounts of frozen and unclaimed assets in Malaysia. A significant relationship between the environmental factors (social influence and social media) and hibah knowledge also implies that the government and private agencies related to Islamic estate planning and management may use these significant determinants as part of the marketing strategy to increase the usage of hibah as an alternative tool for estate planning.

Originality/value

This study contributes to a better understanding of Muslims’ knowledge about hibah. The government and related agencies in Islamic estate planning and management can now gain better insights into Muslims’ level of knowledge about hibah and the factors influencing their knowledge of hibah as an effective tool for Islamic estate planning and management. Hence, more effective strategies can be recommended to enhance the knowledge of Muslims on hibah. The findings of this study should be of value to the government in its effort to address the increasing number of frozen estates in Malaysia.

Meta-control of social learning strategies

Social learning, copying other’s behavior without actual experience, offers a cost-effective means of knowledge acquisition. However, it raises the fundamental question of which individuals have reliable information: successful individuals versus the majority. The former and the latter are known respectively as success-based and conformist social learning strategies. We show here that while the success-based strategy fully exploits the benign environment of low uncertainly, it fails in uncertain environments. On the other hand, the conformist strategy can effectively mitigate this adverse effect. Based on these findings, we hypothesized that meta-control of individual and social learning strategies provides effective and sample-efficient learning in volatile and uncertain environments. Simulations on a set of environments with various levels of volatility and uncertainty confirmed our hypothesis. The results imply that meta-control of social learning affords agents the leverage to resolve environmental uncertainty with minimal exploration cost, by exploiting others’ learning as an external knowledge base.

Which individuals have reliable information: successful individuals or the majority? Seeking a suitable compromise between individual and social learning is crucial for optimum learning in a population. Motivated by the recent findings in neuroscience showing that the brain can arbitrate between different learning strategies, termed meta-control, we propose a meta-control approach in social learning context. First, we show that environmental uncertainty is a crucial predictor of the performance of the individual and two social learning strategies: success-based and conformist. Our meta social learning model uses environmental uncertainty to find a compromise between these two strategies. In simulations on a set of environments with various levels of volatility and uncertainty, we demonstrate that our model outperforms other meta-social learning approaches. In the subsequent evolutionary analysis, we show that our model dominated others in survival rate. Our work provides a new account of the trade-offs between individual, success-based, and conformist learning strategies in multi-agent settings. Critically, our work unveils an optimal social learning strategy to resolve environmental uncertainty with minimal exploration cost.

Distributed Adaptations: Can a Species Be Adapted While No Single Individual Carries the Adaptation?

Species’ adaptation to their environments occurs via a range of mechanisms of adaptation. These include genetic adaptations as well as non-traditional inheritance mechanisms such as learned behaviors, niche construction, epigenetics, horizontal gene transfer, and alteration of the composition of a host’s associated microbiome. We propose to supplement these with another modality of eco-evolutionary dynamics: cases in which adaptation to the environment occurs via what may be called a “distributed adaptation,” in which the adaptation is not conferred via something carried by an individual of the adapted species (as with genes, behavior, or associated microbes), but by some structural or compositional aspect of the population. Put differently, the adaptively relevant information cannot be reduced to information possessed by a single individual, whether genetic or otherwise. Rather, the adaptively relevant information is distributed, and is found strictly at the population level. While human culture is presumably such a case, as may be cases found in social insects, we want to suggest that there are other cases that belong to this category and to explore its evolutionary implications. In particular, we discuss the factors that affect whether adaptive information is stored in a distributed way, to what degree, and what kinds of adaptive information are most likely to be found in this modality of adaptation.

Complex foraging behaviours in wild birds emerge from social learning and recombination of components

Recent well-documented cases of cultural evolution towards increasing efficiency in non-human animals have led some authors to propose that other animals are also capable of cumulative cultural evolution, where traits become more refined and/or complex over time. Yet few comparative examples exist of traits increasing in complexity, and experimental tests remain scarce. In a previous study, we introduced a foraging innovation into replicate subpopulations of great tits, the 'sliding-door puzzle'. Here, we track diffusion of a second 'dial puzzle', before introducing a two-step puzzle that combines both actions. We mapped social networks across two generations to ask if individuals could: (1) recombine socially-learned traits and (2) socially transmit a two-step trait. Our results show birds could recombine skills into more complex foraging behaviours, and naïve birds across both generations could learn the two-step trait. However, closer interrogation revealed that acquisition was not achieved entirely through social learning-rather, birds socially learned components before reconstructing full solutions asocially. As a consequence, singular cultural traditions failed to emerge, although subpopulations of birds shared preferences for a subset of behavioural variants. Our results show that while tits can socially learn complex foraging behaviours, these may need to be scaffolded by rewarding each component. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

A cognitive-evolutionary model for the evolution of teaching

Mechanisms for social learning have rightly been the focus of much work in cultural evolution. But mechanisms for teaching-mechanisms that determine what information is available for learners to learn in the first place-are equally important to cultural evolution, especially in the case of humans. Here, we propose a simple model of teaching in the context of skill transmission. Our model derives the evolutionary cost and benefit of teaching by explicitly representing cognitive aspects of skill transmission as a dual-inheritance process. We then show that teaching cannot evolve when its direct cost is too high. We also show that there is an "explain-exploit" trade-off inherent to teaching: when payoffs from sharing information are not constant, there can be an indirect cost to teaching. This gives rise to an opportunity cost that goes beyond any direct cost that it may also entail. Finally, we show that evolution limits the strength of teaching provided that the direct cost of teaching is an increasing function of teaching effort. We then discuss how these factors might explain why teaching mechanisms are self-limiting, suggesting that such mechanisms may nevertheless play an important role in the evolution of cumulative culture in humans.

How social learning shapes the efficacy of preventative health behaviors in an outbreak

The global pandemic of COVID-19 revealed the dynamic heterogeneity in how individuals respond to infection risks, government orders, and community-specific social norms. Here we demonstrate how both individual observation and social learning are likely to shape behavioral, and therefore epidemiological, dynamics over time. Efforts to delay and reduce infections can compromise their own success, especially when disease risk and social learning interact within sub-populations, as when people observe others who are (a) infected and/or (b) socially distancing to protect themselves from infection. Simulating socially-learning agents who observe effects of a contagious virus, our modelling results are consistent with with 2020 data on mask-wearing in the U.S. and also concur with general observations of cohort induced differences in reactions to public health recommendations. We show how shifting reliance on types of learning affect the course of an outbreak, and could therefore factor into policy-based interventions incorporating age-based cohort differences in response behavior.

Evolution of Social Learning with Payoff and Content Bias

There has been much theoretical work aimed at understanding the evolution of social learning; and in most of it, individual and social learning are treated as distinct processes. A number of authors have argued that this approach is faulty because the same psychological mechanisms underpin social and individual learning. In previous work, we analyzed a simple model in which both individual and social learning are the result of a single learning process. Here, we extend this approach by showing how payoff and content biases evolve. We show that payoff bias leads to higher average fitness when environments are noisy and change rapidly. Content bias always evolves when the expected fitness benefits of alternative traits differ.

The Impact of Meta-Induction: From Skepticism to Optimality

In the first section, five major attempts to solve the problem of induction and their failures are discussed. In the second section, an account of meta-induction is introduced. It offers a novel solution to the problem of induction, based on mathematical theorems about the predictive optimality of attractivity-weighted meta-induction. In the third section, how the a priori justification of meta-induction provides a non-circular a posteriori justification of object-induction, based on its superior track record, is explained. In the fourth section, four important extensions and refinements of the method of meta-induction are presented. The final section, summarizes the major impacts of the program of meta-induction for epistemology, the philosophy of science and cognitive science.