The paper "How Culture Shapes What People Want From AI" by Xiao Ge, Chunchen Xu, Daigo Misaki, Hazel Rose Markus, and Jeanne L Tsai explores the impact of cultural models on people's preferences for AI. The authors propose a conceptual framework that integrates independent and interdependent cultural models of the self and the environment to understand how these models influence people's ideal AI interactions. Two survey studies support this framework, revealing that Chinese respondents view AI as less important to control and more important to connect with, compared to European American respondents. African American respondents' preferences reflect both independent and interdependent views. The findings suggest that cultural backgrounds significantly shape people's perceptions of AI, highlighting the need for culturally responsive AI development to serve a broader segment of the global population. The study advances the field of human-computer interaction by providing empirical evidence for the cultural variability in AI preferences and expanding current models of human-computer interaction.The paper "How Culture Shapes What People Want From AI" by Xiao Ge, Chunchen Xu, Daigo Misaki, Hazel Rose Markus, and Jeanne L Tsai explores the impact of cultural models on people's preferences for AI. The authors propose a conceptual framework that integrates independent and interdependent cultural models of the self and the environment to understand how these models influence people's ideal AI interactions. Two survey studies support this framework, revealing that Chinese respondents view AI as less important to control and more important to connect with, compared to European American respondents. African American respondents' preferences reflect both independent and interdependent views. The findings suggest that cultural backgrounds significantly shape people's perceptions of AI, highlighting the need for culturally responsive AI development to serve a broader segment of the global population. The study advances the field of human-computer interaction by providing empirical evidence for the cultural variability in AI preferences and expanding current models of human-computer interaction.