One major textbook divides artificial intelligence (AI) systems into two categories, those that are meant to think and act rationally and those that are meant to think and act like people (Russell and Norvig, 2003). Developers of systems that focus on rational behavior seek to maximize expected rewards based on the agent’s goals; they do not attempt to account for the many social or cultural factors that influence human behavior. Even systems with human-like behavior as their goal, such as ACT-R (Anderson and Lebiere, 1998) and SOAR (Laird et al., 1987), generally focus either on passing the Turing test or simulating detailed aspects of cognition and/or neural physiology. These models are becoming more like intelligent software agents and are advancing our understanding of the neural and cognitive layers of human thought. However, very few AI systems explore the sociocultural layer of human thought. For decades, the so-called “soft sciences” (psychology, sociology, and anthropology) have focused on the behavioral phenomena that “make us human,” such as emotion, personality, and culture. Not surprisingly, however, these investigations have generated many competing, hotly debated theories but few clear answers.