mlsanityData to 14 Oct 2026

AI Chaperones Are (Really) All You Need to Prevent Parasocial Relationships with Chatbots

arXiv 2508.15748 ↗First posted 21 Aug 2025cs.AIcited by 1

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Abstract (arXiv)

Emerging reports of the harms caused to children and adults by AI sycophancy and by parasocial ties with chatbots point to an urgent need for safeguards against such risks. Yet, preventing such dynamics is challenging: parasocial cues often emerge gradually in private conversations between chatbots and users, and we lack effective methods to mitigate these risks. We address this challenge by introducing a simple response evaluation framework (an AI chaperone agent) created by repurposing a state-of-the-art language model to evaluate ongoing conversations for parasocial cues. We constructed a small synthetic dataset of thirty dialogues spanning parasocial, sycophantic, and neutral conversations. Iterative evaluation with five-stage testing successfully identified all parasocial conversations while avoiding false positives under a unanimity rule, with detection typically occurring within the first few exchanges. These findings provide preliminary evidence that AI chaperones can be a viable solution for reducing the risk of parasocial relationships.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 30 references that are in the map. First posted on arXiv 21 Aug 2025.

Builds on

13 of 30 references.

References · 13

  1. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  2. 2023Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversationscited by 1,207
  3. 2021Ethical and social risks of harm from Language Modelscited by 966
  4. 2025Defeating Prompt Injections by Designcited by 297
  5. 2025ELEPHANT: Measuring and understanding social sycophancy in LLMscited by 129
  6. 2024The Ethics of Advanced AI Assistantscited by 107
  7. 2024The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationshipscited by 62
  8. 2025Why human-AI relationships need socioaffective alignmentcited by 47
  9. 2025Be Friendly, Not Friends: How LLM Sycophancy Shapes User Trustcited by 34
  10. 2022Evaluating Psychological Safety of Large Language Modelscited by 26
  11. 2024From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agentscited by 25
  12. 2025Defense Against the Dark Prompts: Mitigating Best-of-N Jailbreaking with Prompt Evaluationcited by 8
1 more
  1. 2024Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Settingcited by 5

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