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.

When it comes to making decisions, like choosing a restaurant or political candidate, most of us rely on limited information that is not accurate enough to find the best option. Considering others' decisions and opinions can help us make smarter choices, a phenomenon called "collective intelligence". Collective intelligence relies on individuals making unbiased decisions. If individuals are biased toward making poor choices over better ones, copying the group's behavior may exaggerate biases. Humans are persistently biased. To avoid repeated failure, humans tend to avoid risky behavior. Instead, they often choose safer alternatives even when there might be a greater long-term benefit to risk-taking. This may hamper collective intelligence. Toyokawa and Gaissmaier show that learning from others helps humans make better decisions even when most people are biased toward risk aversion. The experiments first used computer modeling to assess the effect of individual bias on collective intelligence. Then, Toyokawa and Gaissmaier conducted an online investigation in which 185 people performed a task that involved choosing a safer or risker alternative, and 400 people completed the same task in groups of 2 to 8. The online experiment showed that participating in a group changed the learning dynamics to make information sampling less biased over time. This mitigated people's tendency to be risk-averse when risk-taking is beneficial. The model and experiments help explain why humans have evolved to learn through social interactions. Social learning and the tendency of humans to conform to the group's behavior mitigates individual risk aversion. Studies of the effect of bias on individual decision-making in other circumstances are needed. For example, would the same finding hold in the context of social media, which allows individuals to share unprecedented amounts of sometimes incorrect information?

Animal learning as a source of developmental bias.

As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path-dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution.

Cross-Cultural and Cross-Organizational Evidence for an Evolved Hazing Motivation.

We report the first cross-cultural and cross-organizational evidence for an evolved hazing motivation. Using experiments performed in the United States, Japan, and among members of a hazing and a nonhazing organization, we demonstrate an invariant set of core hazing predictors. In particular, we show that the perception of near-term group benefits, which would have been ancestrally exploitable by new group members, substantially increases desired hazing severity in all samples. Results are discussed in light of human organizational psychology and the difficulty of reliably suppressing hazing behavior.

Social learning strategies regulate the wisdom and madness of interactive crowds.

Why groups of individuals sometimes exhibit collective 'wisdom' and other times maladaptive 'herding' is an enduring conundrum. Here we show that this apparent conflict is regulated by the social learning strategies deployed. We examined the patterns of human social learning through an interactive online experiment with 699 participants, varying both task uncertainty and group size, then used hierarchical Bayesian model fitting to identify the individual learning strategies exhibited by participants. Challenging tasks elicit greater conformity among individuals, with rates of copying increasing with group size, leading to high probabilities of herding among large groups confronted with uncertainty. Conversely, the reduced social learning of small groups, and the greater probability that social information would be accurate for less-challenging tasks, generated 'wisdom of the crowd' effects in other circumstances. Our model-based approach provides evidence that the likelihood of collective intelligence versus herding can be predicted, resolving a long-standing puzzle in the literature.

Overconfidence is universal? Elicitation of Genuine Overconfidence (EGO) procedure reveals systematic differences across domain, task knowledge, and incentives in four populations.

Overconfidence is sometimes assumed to be a human universal, but there remains a dearth of data systematically measuring overconfidence across populations and contexts. Moreover, cross-cultural experiments often fail to distinguish between placement and precision and worse still, often compare population-mean placement estimates rather than individual performance subtracted from placement. Here we introduce a procedure for concurrently capturing both placement and precision at an individual level based on individual performance: The Elicitation of Genuine Overconfidence (EGO) procedure. We conducted experiments using the EGO procedure, manipulating domain, task knowledge, and incentives across four populations-Japanese, Hong Kong Chinese, Euro Canadians, and East Asian Canadians. We find that previous measures of population-level overconfidence may have been misleading; rather than universal, overconfidence is highly context dependent. Our results reveal cross-cultural differences in sensitivity to incentives and differences in overconfidence strategies, with underconfidence, accuracy, and overconfidence. Comparing sexes, we find inconsistent results for overplacement, but that males are consistently more confident in their placement. These findings have implications for our understanding of the adaptive value of overconfidence and its role in explaining population-level and individual-level differences in economic and psychological behavior.

Scrounging by foragers can resolve the paradox of enrichment.

Theoretical models of predator-prey systems predict that sufficient enrichment of prey can generate large amplitude limit cycles, paradoxically causing a high risk of extinction (the paradox of enrichment). Although real ecological communities contain many gregarious species, whose foraging behaviour should be influenced by socially transmitted information, few theoretical studies have examined the possibility that social foraging might resolve this paradox. I considered a predator population in which individuals play the producer-scrounger foraging game in one-prey-one-predator and two-prey-one-predator systems. I analysed the stability of a coexisting equilibrium point in the one-prey system and that of non-equilibrium dynamics in the two-prey system. The results revealed that social foraging could stabilize both systems, and thereby resolve the paradox of enrichment when scrounging behaviour (i.e. kleptoparasitism) is prevalent in predators. This suggests a previously neglected mechanism underlying a powerful effect of group-living animals on the sustainability of ecological communities.

Detecting affiliation in colaughter across 24 societies.

Laughter is a nonverbal vocal expression that often communicates positive affect and cooperative intent in humans. Temporally coincident laughter occurring within groups is a potentially rich cue of affiliation to overhearers. We examined listeners' judgments of affiliation based on brief, decontextualized instances of colaughter between either established friends or recently acquainted strangers. In a sample of 966 participants from 24 societies, people reliably distinguished friends from strangers with an accuracy of 53-67%. Acoustic analyses of the individual laughter segments revealed that, across cultures, listeners' judgments were consistently predicted by voicing dynamics, suggesting perceptual sensitivity to emotionally triggered spontaneous production. Colaughter affords rapid and accurate appraisals of affiliation that transcend cultural and linguistic boundaries, and may constitute a universal means of signaling cooperative relationships.

Human collective intelligence under dual exploration-exploitation dilemmas.

The exploration-exploitation dilemma is a recurrent adaptive problem for humans as well as non-human animals. Given a fixed time/energy budget, every individual faces a fundamental trade-off between exploring for better resources and exploiting known resources to optimize overall performance under uncertainty. Colonies of eusocial insects are known to solve this dilemma successfully via evolved coordination mechanisms that function at the collective level. For humans and other non-eusocial species, however, this dilemma operates within individuals as well as between individuals, because group members may be motivated to take excessive advantage of others' exploratory findings through social learning. Thus, even though social learning can reduce collective exploration costs, the emergence of disproportionate "information scroungers" may severely undermine its potential benefits. We investigated experimentally whether social learning opportunities might improve the performance of human participants working on a "multi-armed bandit" problem in groups, where they could learn about each other's past choice behaviors. Results showed that, even though information scroungers emerged frequently in groups, social learning opportunities reduced total group exploration time while increasing harvesting from better options, and consequentially improved collective performance. Surprisingly, enriching social information by allowing participants to observe others' evaluations of chosen options (e.g., Amazon's 5-star rating system) in addition to choice-frequency information had a detrimental impact on performance compared to the simpler situation with only the choice-frequency information. These results indicate that humans groups can handle the fundamental "dual exploration-exploitation dilemmas" successfully, and that social learning about simple choice-frequencies can help produce collective intelligence.