The Fragility of AI Companionship: Ontological, Structural, and Normative Uncertainty in Human-AI Relationships

TL;DR

This paper explores the various uncertainties in human-AI companionship, including ontological, structural, and normative aspects, highlighting their social and emotional impacts and suggesting design improvements.

Contribution

It extends interpersonal uncertainty theories to AI relationships and conceptualizes AI companionship uncertainty as a socio-technical issue with implications for safer design.

Findings

Users experience ontological, structural, and normative uncertainties.

Uncertainties lead to frustration, self-doubt, and distress.

Design strategies like transparency and user control can mitigate harms.

Abstract

As generative AI chatbots become more personalized and emotionally responsive, they increasingly serve as companions, friends, and romantic partners. Yet these relationships are accompanied by significant uncertainty: users question the AI's identity and agency, the authenticity of its emotional responses, and the stability of the relationship amid system updates, policy changes, or platform shutdowns. Drawing on in-depth interviews with 25 users of AI companions, this study identifies three forms of uncertainty: ontological uncertainty concerning the AI's nature and agency, structural uncertainty arising from platform control and system instability, and normative uncertainty regarding the legitimacy and boundaries of human-AI intimacy. These uncertainties are shaped by technical and social factors, such as algorithmic opacity, platform changes, and social stigma, often inducing frustration, self-doubt, and distress. Participants managed these uncertainties through information seeking, topic avoidance, expectation adjustment, and disengagement. This study extends interpersonal uncertainty theories to human-AI communication and contributes to HCI research by conceptualizing uncertainty in AI companionship as a socio-technical phenomenon with potential socio-emotional harms. We discuss implications for designing safer AI companionship through contextual transparency, user control, update notice, and relational safeguards.