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

2026-01-23

AI Summary

This study investigates privacy risks, blurred boundaries, and diminished user autonomy in romantic relationships between humans and artificial intelligence. Through semi-structured interviews with 17 participants and thematic analysis, it systematically examines users’ privacy experiences across the stages of relationship initiation, intimacy development, and termination. The research reveals, for the first time, a multi-agent privacy construction mechanism involving platforms, developers, and AI agents, proposing a novel perspective that recognizes AI as an agentic entity actively negotiating privacy boundaries. Findings indicate diverse relational configurations—from one-to-one to one-to-many—and demonstrate that deepening intimacy leads to increased boundary permeability. Participants commonly expressed concerns about conversation leakage and preferred anonymous interactions, underscoring the need to reconceptualize and reconstruct privacy frameworks specifically tailored to human–AI intimate relationships.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Philosophy and Ethics of AI: Privacy & Security
• Intelligent Robots: Embodied AI

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

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.

Problem

• privacy
• human-AI romantic relationships
• AI agency
• privacy boundaries
• LLM-based applications

Innovation

• human-AI romantic relationships
• privacy boundaries
• AI agency
• LLM-based companions
• platform affordances