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.
InProceedings of the 2022 Conference on Empirical Methods in Natural Lan- guage Processing, pages 2438–2459, Abu Dhabi, United Arab Emirates
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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.