This paper examines the use of qualitative representations in modeling the similarities and differences in causal reasoning for biological kinds between Menominee Native Americans and US majority culture. Qualitative Concept Maps are used for modeling and analyzing transcripts of interviews conducted with these groups. The individual models are used to construct generalizations for the groups, which are tested both by inspection and by creating a classifier to distinguish models from these two cultures.

For more than a century, most psychologists have based their discussions of human thinking on the cardinal assumption that basic cognitive processes are the same for all normal adult human beings, whether in the plains of Central Asia, the villages of East Africa, or the

To be published in Behavioral and Brain Sciences (in press)

Whether and to what extent concepts and basic cognitive functions are universal is of fundamental importance for understanding of the nature of human thought. On the one hand, a shared cognitive architecture might be argued to provide constraints on the nature of knowledge and thought processes that transcend cultural differences. On the other hand, much of human knowledge is acquired through the medium of language and in the context of specific cultural needs and interpretations, and thus language and culture may filter or shape the knowledge acquired and perhaps even the cognitive processes that typically operate on them. In this panel, we present three papers that examine these possibilities from different angles to deepen our understanding of the interplay among universally shared

Broad claims about human psychology and behavior based on narrow samples from Western societies are regularly published. Are such species‐generalizing claims justified? This review suggests not only substantial variability in experimental results across populations in basic domains, but that standard subjects are unusual compared with the rest of the species— outliers. The domains reviewed include visual perception, fairness, spatial reasoning, moral reasoning, thinking‐styles, and self‐concepts. This suggests (1) caution in addressing questions of human nature from this slice of humanity, and (2) that understanding human psychology will require broader subject pools. We close by proposing ways to address these challenges. Behavioral scientists routinely publish broad claims about human psychology, cognition, and behavior in the world’s top journals based on samples drawn entirely from highly educated segments of Western societies. Researchers—often implicitly—assume that either there is little variation across human populations, or that these “standard subjects ” are as representative of the species as any other. Are these assumptions justified? Here, our review of the comparative

Humans are unique among animals for both the diverse complexity of our cognition and our reliance on culture, the socially-transmitted representations and practices that shape experience and behavior. Adopting an evolutionary psychological approach, in this essay we consider four different facets of the relationship between cognition and culture. We begin with a discussion of two well-established research traditions, the investigation of features of mind that are universal despite cultural diversity, and the examination of features of mind that vary across cultures. We then turn to two topics that have only recently begun to receive attention, the cognitive mechanisms that underlie the acquisition of cultural information, and the effects of features of cognition on culture. Throughout, our goal is not to provide comprehensive reviews so much as to frame these issues in such a way as to spur further research.

ABSTRACT—Just as neurons interconnect in networks that create structured thoughts beyond the ken of any individual neuron, so people spontaneously organize themselves into groups to create emergent organizations that no individual may intend, comprehend, or even perceive. Recent technological advances have provided us with unprecedented opportunities for conducting controlled laboratory experiments on human collective behavior. We describe two experimental paradigms in which we attempt to build predictive bridges between the beliefs, goals, and cognitive capacities of individuals and patterns of behavior at the group level, showing how the members of a group dynamically allocate themselves to resources and how innovations diffuse through a social network. Agent-based computational models have provided useful explanatory and predictive accounts. Together, the models and experiments point to tradeoffs between exploration and exploitation—that is, compromises between individuals using their own innovations and using innovations obtained from their peers—and the emergence of group-level organizations such as population waves, bandwagon effects, and spontaneous specialization. KEYWORDS—collective behavior; imitation; social networks; competition; group behavior; foraging It is natural for psychologists to focus on the behavior of single individuals, because introspection provides people with motivation and perspective at this level. However, in a literal sense, we are all participating in entities greater than ourselves. Selforganized collectives of people create emergent group-level patterns that are rarely understood or intended by any individual. A business has a style and ethos that transcends its employees. A culture has a nature, integrity, and systematicity that transcends its inhabitants while still being grounded by their

The study of decision making has been dominated by economic perspectives, which model people as rational agents who carefully weigh costs and benefits and try to maximize the utility of every choice, without consideration of issues such as cultural norms, religious beliefs and moral rules. However, psychological findings indicate that in many situations people are not rational decision makers as defined by the economic theories. One of the domains in which traditional cost-benefit models fail to predict human behavior is the domain of moral reasoning. This work presents the first computational model of recognitionbased moral decision making, MoralDM, which integrates several AI techniques in order to model recent psychological findings on moral decision making. MoralDM uses a natural language system to produce formal representations from psychological stimuli,

There has been a recent upsurge of research on moral judgment and decision making. One important issue with this body of work concerns the relative advantages of calculating costs and benefits versus adherence to moral rules. The general tenor of recent research suggests that adherence to moral rules is associated with systematic biases and that systematic cost-benefit analysis is a normatively superior decision strategy. This article queries both the merits of cost-benefit analyses and the shortcomings of moral rules. We argue that outside the very narrow domain in which consequences can be unambiguously anticipated, it is not at all clear that calculation processes optimize outcomes. In addition, there are good reasons to believe that following moral rules can lead to superior consequences in certain contexts. More generally, different modes of decision making can be seen as adaptations to particular environments.