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

2026-05-05

AI Summary

This study investigates the multiple forms of uncertainty—ontological, structural, and normative—that arise in human-AI intimate relationships due to AI identity ambiguity, system instability, and the absence of established social norms, along with their emotional consequences. Drawing on in-depth interviews with 25 users of AI companions, the research extends interpersonal uncertainty theory into the domain of human-AI interaction by introducing a novel tripartite framework of uncertainty. It identifies four user strategies for managing these uncertainties and translates these insights into design recommendations, including enhancing contextual transparency, strengthening user control, providing clear update notifications, and offering relational assurances. These contributions provide both theoretical grounding and practical guidance for developing safer, more trustworthy AI companionship systems.

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.

Problem

• ontological uncertainty
• structural uncertainty
• normative uncertainty
• human-AI relationships
• AI companionship

Innovation

• ontological uncertainty
• structural uncertainty
• normative uncertainty
• human-AI companionship
• socio-technical phenomenon