Core Insights - A study from the University of Washington indicates that AI systems can learn and internalize cultural values by observing human behavior within specific cultures, providing new insights into AI's cross-cultural adaptation challenges [1][2] Group 1: Research Findings - The current training of AI typically relies on large-scale internet data, which often contains culturally biased values, leading to inconsistent performance across different cultural backgrounds [1] - The research team employed a method of "observational learning," allowing AI to absorb values from specific cultural groups rather than being programmed with a universal set of principles [1][2] - An experiment involving 190 adults showed that participants exhibited more altruistic behavior when interacting with an AI agent during a collaborative task, suggesting that AI can learn social behaviors through observation [1] Group 2: Methodology and Implications - AI agents utilized "inverse reinforcement learning" to infer the behavioral goals and intrinsic values of the observed group, successfully applying learned altruistic tendencies to new scenarios, such as donation tasks [2] - The study draws parallels between AI learning and children's learning processes, emphasizing that values are often "captured" rather than "taught" [2] - The research highlights the importance of creating culturally adaptive AI that can understand different perspectives, which is a significant challenge in today's society [2]