A survey of open questions on chatbots and mental health

1. 06:39
   arXiv: Alignment, Deception & Oversight

   Open questions for chatbots and mental health

   Researchers reviewed the most critical open questions for general-purpose chatbots used for emotional and mental health support, noting that risks such as sycophancy, reinforcing delusional beliefs and inadequate crisis response are difficult to study and evaluate. The paper first discusses the challenges of controllable evaluation, including establishing construct validity and ecological validity for evaluations, assessing multi-turn interactions, and linking evaluation to improvements in chatbot behavior; conventional benchmarks relying on static datasets cannot establish chatbot safety, and new simulation methods also need validation. Second, the authors argue for connecting research with real-world evidence by analyzing products already deployed by AI companies and mental health practitioners, including their user interfaces and the human review and escalation mechanisms for user well-being issues, but the clinical analysis opportunities offered by sharing chat logs are constrained by significant privacy concerns. Finally, the authors call on researchers to actively participate in evidence-based policymaking covering user protection, standards of care, protected access to chat logs, inter-institutional data sharing, incident reporting and post-deployment monitoring, and argue that behavioral evaluation, real-world research and data governance are interdependent and must advance together.

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