# Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions

arXiv: https://arxiv.org/abs/2609.16907 · HTML: https://mlsanity.com/paper/2609.16907/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 98 references that are in the map.
- First posted on arXiv 15 Sep 2026.

## Builds on (most cited first, 23 of 23)

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- [Large Language Models Produce Responses Perceived to be Empathic](https://mlsanity.com/paper/2403.18148/) (2024)
- [AI Companions Reduce Loneliness](https://mlsanity.com/paper/2407.19096/) (2024)
- ["My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community](https://mlsanity.com/paper/2509.11391/) (2025)
- [Chatbots for Mental Health Support: Exploring the Impact of Emohaa on Reducing Mental Distress in China](https://mlsanity.com/paper/2209.10183/) (2022)
- [Lessons From an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships](https://mlsanity.com/paper/2412.14190/) (2024)
- [User-Driven Value Alignment: Understanding Users' Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions](https://mlsanity.com/paper/2409.00862/) (2024)
- [Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect](https://mlsanity.com/paper/2302.09885/) (2023)
- [Community notes reduce engagement with and diffusion of false information online](https://mlsanity.com/paper/2502.13322/) (2025)
- [Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives](https://mlsanity.com/paper/2507.15783/) (2025)
- [AI on My Shoulder: Supporting Emotional Labor in Front-Office Roles with an LLM-based Empathetic Coworker](https://mlsanity.com/paper/2411.02408/) (2024)
- [Longitudinal Study on Social and Emotional Use of AI Conversational Agent](https://mlsanity.com/paper/2504.14112/) (2025)
- [Mental Health Impacts of AI Companions: Triangulating Social Media Quasi-Experiments, User Perspectives, and Relational Theory](https://mlsanity.com/paper/2509.22505/) (2025)
- [Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?](https://mlsanity.com/paper/2303.07242/) (2023)
- ["Please, don't kill the only model that still feels human": Understanding the #Keep4o Backlash](https://mlsanity.com/paper/2602.00773/) (2026)
- ["Death" of a Chatbot: Investigating and Designing Toward Psychologically Safe Endings for Human-AI Relationships](https://mlsanity.com/paper/2602.07193/) (2026)
- [CompanionHarm: A Multi-Turn Benchmark for Detecting Harms in Real-World AI Companion Conversations](https://mlsanity.com/paper/2608.25377/) (2026)
- [Situated, Dynamic, and Subjective: Envisioning the Design of Theory-of-Mind-Enabled Everyday AI with Industry Practitioners](https://mlsanity.com/paper/2602.11342/) (2026)
- [Twitch Third-Party Developers' Support Seeking and Provision Practices on Discord](https://mlsanity.com/paper/2604.07732/) (2026)
- [The Fragility of AI Companionship: Ontological, Structural, and Normative Uncertainty in Human-AI Relationships](https://mlsanity.com/paper/2605.03367/) (2026)
- [The Impact of Security and Privacy Controls on Users' Emotional Engagement with Generative AI Chatbots](https://mlsanity.com/paper/2607.06371/) (2026)

## Abstract (arXiv)

AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion disruptions: platform changes that alter or terminate users' ongoing companionship with an AI. We compile 30 disruption events across major platforms, develop a taxonomy of six disruption types, identify three broad reasons for disruption, and propose a risk-assessment framework comprising four dimensions: relational discontinuity, population vulnerability, communication deficit, and transition-support deficit. Using longitudinal Reddit data, we estimate community-level psychosocial responses with a hierarchical Bayesian interrupted time-series model incorporating predictive controls. Across events, disruption onset was associated with immediate increases in anxiety, stress, suicidal expression, and grief activation, with relational discontinuity and transition-support deficit being associated with more adverse immediate responses across several outcomes. Our findings provide a cross-platform characterization of AI companion disruptions, quantitative evidence of their psychosocial impacts, and a prospective framework for assessing their potential risks before implementation.