Proposes an interdisciplinary framework and taxonomy for responsible evaluation of AI mental health tools based on analysis of 135 publications identifying gaps in metrics, expert involvement, safety, and equity.
InFindings of the Association for Compu- tational Linguistics: ACL 2025, pages 13750–13770, Vienna, Austria
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Responsible Evaluation of AI for Mental Health
Proposes an interdisciplinary framework and taxonomy for responsible evaluation of AI mental health tools based on analysis of 135 publications identifying gaps in metrics, expert involvement, safety, and equity.