How Culture Shapes What People Want From AI

要旨

There is an urgent need to incorporate the perspectives of culturally diverse groups into AI developments. We present a novel conceptual framework for research that aims to expand, reimagine, and reground mainstream visions of AI using independent and interdependent cultural models of the self and the environment. Two survey studies support this framework and provide preliminary evidence that people apply their cultural models when imagining their ideal AI. Compared with European American respondents, Chinese respondents viewed it as less important to control AI and more important to connect with AI, and were more likely to prefer AI with capacities to influence. Reflecting both cultural models, findings from African American respondents resembled both European American and Chinese respondents. We discuss study limitations and future directions and highlight the need to develop culturally responsive and relevant AI to serve a broader segment of the world population.

著者
Xiao Ge
Stanford University, Stanford, California, United States
Chunchen Xu
Stanford University, Stanford, California, United States
Daigo Misaki
Kogakuin University, Shinjuku-ku, Tokyo, Japan
Hazel Rose Markus
Stanford University, Stanford, California, United States
Jeanne L. Tsai
Stanford University, Stanford, California, United States
論文URL

https://doi.org/10.1145/3613904.3642660

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Better Future Worlds and AI

310 Lili'u Theater
3 件の発表
2024-05-16 20:00:00
2024-05-16 21:20:00