AI Chaperones Are (Really) All You Need to Prevent Parasocial Relationships with Chatbots
This addresses the risk of AI sycophancy and parasocial ties for children and adults, though it is incremental as it builds on existing language models with a small synthetic dataset.
The paper tackled the problem of preventing parasocial relationships with chatbots by introducing an AI chaperone agent that evaluates conversations for parasocial cues, achieving detection of all parasocial conversations in a synthetic dataset with no false positives under a unanimity rule.
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.