Privacy in Human-AI Romantic Relationships: Concerns, Boundaries, and Agency

TL;DR

This work addresses privacy risks in human–AI romantic relationships by conducting an interview study with 17 participants and a platform feature analysis. Using a three-stage model of exploration, intensified exchange, and dissolution, the study reveals that AI partners are perceived to possess agency and actively influence privacy boundaries, while intimacy tends to erode these boundaries and expand disclosure. It highlights a complex privacy landscape shaped by diverse relationship forms and multiple actors beyond the dyad, including creators, platforms, and moderators, as well as concerns about conversation exposure, platform surveillance, and memory retention. The authors propose emotionally aware privacy regulation, privacy nudges delivered by AI, and enhanced platform oversight as concrete steps to safeguard users while recognizing the unique dynamics of human–AI intimate relationships.

Abstract

An increasing number of LLM-based applications are being developed to facilitate romantic relationships with AI partners, yet the safety and privacy risks in these partnerships remain largely underexplored. In this work, we investigate privacy in human-AI romantic relationships through an interview study (N=17), examining participants' experiences and privacy perceptions across stages of exploration, intimacy, and dissolution, alongside platforms they used. We found that these relationships took varied forms, from one-to-one to one-to-many, and were shaped by multiple actors, including creators, platforms, and moderators. AI partners were perceived as having agency, actively negotiating privacy boundaries with participants and sometimes encouraging disclosure of personal details. As intimacy deepened, these boundaries became more permeable, though some participants voiced concerns such as conversation exposure and sought to preserve anonymity. Overall, platform affordances and diverse romantic dynamics expand the privacy landscape, underscoring the need to rethink how privacy is constructed in human-AI intimacy.