Better Future Worlds and AI

会議の名前
CHI 2024
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
Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Students
要旨

Students' increasing use of Artificial Intelligence (AI) presents new challenges for assessing their mastery of knowledge and skills in project-based learning (PBL). This paper introduces a co-design study to explore the potential of students' AI usage data as a novel material for PBL assessment. We conducted workshops with 18 college students, encouraging them to speculate an alternative world where they could freely employ AI in PBL while needing to report this process to assess their skills and contributions. Our workshops yielded various scenarios of students' use of AI in PBL and ways of analyzing such usage grounded by students' vision of how educational goals may transform. We also found that students with different attitudes toward AI exhibited distinct preferences in how to analyze and understand their use of AI. Based on these findings, we discuss future research opportunities on student-AI interactions and understanding AI-enhanced learning.

著者
Chengbo Zheng
Hong Kong University of Science and Technology, Hong Kong, China
Kangyu Yuan
Sun Yat-sen University, Zhuhai, Guangdong, China
Bingcan Guo
The Hong Kong University of Science and Technology, Hong Kong, China
Reza Hadi Mogavi
University of Waterloo, Waterloo, Ontario, Canada
Zhenhui Peng
Sun Yat-sen University, Zhuhai, Guangdong Province, China
Shuai Ma
The Hong Kong University of Science and Technology, Hong Kong, China
Xiaojuan Ma
Hong Kong University of Science and Technology, Hong Kong, Hong Kong
論文URL

https://doi.org/10.1145/3613904.3642807

動画
Socio-technical Imaginaries: Envisioning and Understanding AI Parenting Supports through Design Fiction
要旨

How might emerging modalities (e.g., NLP) be leveraged to transform the provision of parenting support? To explore the role of AI technologies in supporting parenting behaviour—and child-well-being—we surveyed 92 parents to gather their perspectives on nine future-oriented scenarios. We used Design Fiction and Speed Dating to understand parents needs and preferences around the design of agent-based supports. We explore the perceived benefits of AI assistants (i.e., receiving objective feedback, managing emotions and personalised guidance) and the most voiced concerns (i.e., AI undermining parental authority, replacing human interactions, and promoting lazy parenting). Finally, we highlight a number of plausible design directions based on the scenarios that parents were positive about.

著者
Melina Petsolari
King's College London, London, United Kingdom
Seray B. Ibrahim
King's College London, London, United Kingdom
Petr Slovak
King's College London, London, United Kingdom
論文URL

https://doi.org/10.1145/3613904.3642619

動画