Stereotypically Yours: Portrayal and Perception of Race-Coded AI Companions

2026-09-17

AI Summary

研究通过算法审计和用户访谈，探讨了种族编码AI伴侣的表现及其对用户感知的影响，揭示了存在的刻板印象问题，并讨论了如何避免再现这些刻板印象。

Abstract

AI companions can purportedly adopt racial personas, raising questions about how they represent identity and how users interpret these portrayals. We combined an algorithmic audit of race-coded AI personas with interviews with 12 companion users who interacted with a probe. Our audit revealed systematic differences, such as Asian-coded male personas receiving higher submissiveness scores than White counterparts, and Black, Hispanic, and Indigenous male personas receiving higher aggression scores than their White counterparts in open-weight models. Interviews revealed that participants envisioned AI companions as offering cultural familiarity and outside perspectives, but differed in which portrayals they considered meaningful or stereotypical. Some rejected overt racial signaling while still expecting culturally distinctive responses. Triangulating these findings with theory, we highlight how social norms and cultural expectations complicate efforts to support meaningful racial representation without reproducing stereotypes. We discuss how companion personalization should be evaluated beyond user satisfaction to account for broader representational harms.

Problem

• racial representation
• AI companions
• cultural expectations
• stereotypes
• algorithmic audit

Innovation

• racial representation
• algorithmic audit
• cultural expectations
• stereotypes
• personalization