Presentation Information
[4Yin-A-02]Whose Fairness, and for Whom?Value Gaps in AI Ethics and the Conditions for Institutionalization
〇Aoi Miyazaki1 (1. Chiba University)
Keywords:
AI,Ethics,Fairness
As the social implementation of generative AI accelerates, ethical concerns surrounding fairness have become increasingly salient. This study examines whose fairness is prioritized, and for whom, by focusing on value gaps in AI ethics and their implications for institutionalization. To investigate this issue, a web-based survey was conducted with 600 respondents, including members of the Japanese Society for Artificial Intelligence andgeneral users. The survey analyzed definitions of fairness, perceptions of social fairness, and expectations toward AI across different attributes.
The results reveal a systematic value gap: AI practitioners tend to emphasize procedural fairness and transactional legitimacy, whereas general users place greater weight on outcome equality and the protection of vulnerable groups. Based on these findings, this study argues that the institutionalization of AI ethics requires a multi-layered conception of fairness, strengthened ethics education for practitioners, and closer alignment with international regulatory frameworks to ensure social legitimacy and resilience.
The results reveal a systematic value gap: AI practitioners tend to emphasize procedural fairness and transactional legitimacy, whereas general users place greater weight on outcome equality and the protection of vulnerable groups. Based on these findings, this study argues that the institutionalization of AI ethics requires a multi-layered conception of fairness, strengthened ethics education for practitioners, and closer alignment with international regulatory frameworks to ensure social legitimacy and resilience.