Search

Cesario et al. argue that benchmarking the relative counts of killings by police on relative crime rates, rather than relative population sizes, generates a measure of racial disparity in the use of lethal force that is unbiased by differential crime rates. Their publication, however, lacked any formal derivation showing that their benchmarking methodology has the statistical properties required to establish such a claim. We use the causal model of lethal force by police conditional on relative crime rates implicit in their analyses and prove that their benchmarking methodology does not, in general, remove the bias introduced by crime rate differences. Instead, it creates strong statistical biases that mask true racial disparities, especially in the killing of unarmed noncriminals by police. Reanalysis of their data using formally derived criminality-correcting benchmarks shows that there is strong and statistically reliable evidence of anti-Black racial disparities in the killing of unarmed Americans by police in 2015–2016.

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.

Behavioral researchers increasingly recognize the need for more diverse samples that capture the breadth of human experience. Current attempts to establish generalizability across populations focus on threats to validity, constraints on generalization, and the accumulation of large, cross-cultural data sets. But for continued progress, we also require a framework that lets us determine which inferences canbe drawn and how to make informative cross-cultural comparisons. We describe a generative causal-modeling framework and outline simple graphical criteria to derive analytic strategies and implied generalizations. Using both simulated and real data, we demonstrate how to project and compare estimates across populations and further show how to formally represent measurement equivalence or inequivalence across societies. We conclude with a discussion of how a formal framework for generalizability can assist researchers in designing more informative cross-cultural studies and thus provides a more solid foundation for cumulative and generalizable behavioral research.

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.

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.

An innovative computational analysis of factors that might have influenced human brain evolution suggests that ecological, rather than social, factors had a key role in the evolution of large, rapidly developing brains. An innovative computational analysis of factors that might have influenced human brain evolution suggests that ecological, rather than social, factors had a key role in the evolution of large, rapidly developing brains.

Monogamy appears to have become the predominant human mating system with the emergence of highly unequal agricultural populations that replaced relatively egalitarian horticultural populations, challenging the conventional idea—based on the polygyny threshold model—that polygyny should be positively associated with wealth inequality. To address this polygyny paradox, we generalize the standard polygyny threshold model to a mutual mate choice model predicting the fraction of women married polygynously. We then demonstrate two conditions that are jointly sufficient to make monogamy the predominant marriage form, even in highly unequal societies. We assess if these conditions are satisfied using individual-level data from 29 human populations. Our analysis shows that with the shift to stratified agricultural economies: (i) the population frequency of relatively poor individuals increased, increasing wealth inequality, but decreasing the frequency of individuals with sufficient wealth to secure polygynous marriage, and (ii) diminishing marginal fitness returns to additional wives prevent extremely wealthy men from obtaining as many wives as their relative wealth would otherwise predict. These conditions jointly lead to a high population-level frequency of monogamy.

Economists study negotiation as a series of events—partner choice, information gathering, bargaining, etc.—with each step of the process affecting the outcome of the next, and the optimal decision at each stage depending on the player’s bargaining power. The context in which these negotiations occur—the market—is critical, since players can adjust their behaviors in response to outside offers. Animals similarly are faced with sequential decisions regarding courtship: who to court, how to approach a potential mate, at what level to display, when to give up, etc. Thus economic models of negotiation in a market provide a framework in which we can view not just the outcome of courtship (assortative mating), but also the process, where each sex can use tactics to improve their negotiating outcome, using the assets that they have available. Here we propose to use negotiation as a conceptual framework to explore the factors promoting tactical adjustments during sequential stages of courtship in lekking species. Our goal is to discuss the utility of negotiation as a heuristic tool, as well as the promise and peril of co-opting game theoretic models from economics to understand animal interactions. We will provide a brief overview of a few areas where we see promise for using negotiation as a framework to understand animal courtship dynamics: choice of a display territory, tactical partner choice for negotiation, approaching a potential partner and courtship haggling.