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Abstract:Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity results from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model -based on self-interest -fails in all of the societies studied. Second, our data reveal substantially more behavioral variability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life.

Recent behavioral experiments aimed at understanding the evolutionary foundations of human cooperation have suggested that a willingness to engage in costly punishment, even in one-shot situations, may be part of human psychology and a key element in understanding our sociality. However, because most experiments have been confined to students in industrialized societies, generalizations of these insights to the species have necessarily been tentative. Here, experimental results from 15 diverse populations show that (i) all populations demonstrate some willingness to administer costly punishment as unequal behavior increases, (ii) the magnitude of this punishment varies substantially across populations, and (iii) costly punishment positively covaries with altruistic behavior across populations. These findings are consistent with models of the gene-culture coevolution of human altruism and further sharpen what any theory of human cooperation needs to explain.

Large-scale societies in which strangers regularly engage in mutually beneficial transactions are puzzling. The evolutionary mechanisms associated with kinship and reciprocity, which underpin much of primate sociality, do not readily extend to large unrelated groups. Theory suggests that the evolution of such societies may have required norms and institutions that sustain fairness in ephemeral exchanges. If that is true, then engagement in larger-scale institutions, such as markets and world religions, should be associated with greater fairness, and larger communities should punish unfairness more. Using three behavioral experiments administered across 15 diverse populations, we show that market integration (measured as the percentage of purchased calories) positively covaries with fairness while community size positively covaries with punishment. Participation in a world religion is associated with fairness, although not across all measures. These results suggest that modern prosociality is not solely the product of an innate psychology, but also reflects norms and institutions that have emerged over the course of human history.

Poor research design and data analysis encourage false-positive findings. Such poor methods persist despite perennial calls for improvement, suggesting that they result from something more than just misunderstanding. The persistence of poor methods results partly from incentives that favour them, leading to the natural selection of bad science. This dynamic requires no conscious strategizing—no deliberate cheating nor loafing—by scientists, only that publication is a principal factor for career advancement. Some normative methods of analysis have almost certainly been selected to further publication instead of discovery. In order to improve the culture of science, a shift must be made away from correcting misunderstandings and towards rewarding understanding. We support this argument with empirical evidence and computational modelling. We first present a 60-year meta-analysis of statistical power in the behavioural sciences and show that power has not improved despite repeated demonstrations of the necessity of increasing power. To demonstrate the logical consequences of structural incentives, we then present a dynamic model of scientific communities in which competing laboratories investigate novel or previously published hypotheses using culturally transmitted research methods. As in the real world, successful labs produce more ‘progeny,’ such that their methods are more often copied and their students are more likely to start labs of their own. Selection for high output leads to poorer methods and increasingly high false discovery rates. We additionally show that replication slows but does not stop the process of methodological deterioration. Improving the quality of research requires change at the institutional level.

Humans are unique in their range of environments and in the nature and diversity of their behavioral adaptations. While a variety of local genetic adaptations exist within our species, it seems certain that the same basic genetic endowment produces arctic foraging, tropical horticulture, and desert pastoralism, a constellation that represents a greater range of subsistence behavior than the rest of the Primate Order combined. The behavioral adaptations that explain the immense success of our species are cultural in the sense that they are transmitted among individuals by social learning and have accumulated over generations. Understanding how and when such culturally evolved adaptations arise requires understanding of both the evolution of the psychological mechanisms that underlie human social learning and the evolutionary (population) dynamics of cultural systems.

Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences. We first outline a set of questions that are fundamental to this emerging field and then explore the technical, legal and institutional constraints on the study of machine behaviour.

Participants in laboratory games are often willing to alter others' incomes at a cost to themselves, and this behaviour has the effect of promoting cooperation. What motivates this action is unclear: punishment and reward aimed at promoting cooperation cannot be distinguished from attempts to produce equality. To understand costly taking and costly giving, we create an experimental game that isolates egalitarian motives. The results show that subjects reduce and augment others' incomes, at a personal cost, even when there is no cooperative behaviour to be reinforced. Furthermore, the size and frequency of income alterations are strongly influenced by inequality. Emotions towards top earners become increasingly negative as inequality increases, and those who express these emotions spend more to reduce above-average earners' incomes and to increase below-average earners' incomes. The results suggest that egalitarian motives affect income-altering behaviours, and may therefore be an important factor underlying the evolution of strong reciprocity and, hence, cooperation in humans.