{"ID":2852242,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.18581","arxiv_id":"2510.18581","title":"The Cost-Benefit of Interdisciplinarity in AI for Mental Health","abstract":"Artificial intelligence has been introduced as a way to improve access to mental health support. However, most AI mental health chatbots rely on a limited range of disciplinary input, and fail to integrate expertise across the chatbot's lifecycle. This paper examines the cost-benefit trade-off of interdisciplinary collaboration in AI mental health chatbots. We argue that involving experts from technology, healthcare, ethics, and law across key lifecycle phases is essential to ensure value-alignment and compliance with the high-risk requirements of the AI Act. We also highlight practical recommendations and existing frameworks to help balance the challenges and benefits of interdisciplinarity in mental health chatbots.","short_abstract":"Artificial intelligence has been introduced as a way to improve access to mental health support. However, most AI mental health chatbots rely on a limited range of disciplinary input, and fail to integrate expertise across the chatbot's lifecycle. This paper examines the cost-benefit trade-off of interdisciplinary coll...","url_abs":"https://arxiv.org/abs/2510.18581","url_pdf":"https://arxiv.org/pdf/2510.18581v1","authors":"[\"Katerina Drakos\",\"Eva Paraschou\",\"Simay Toplu\",\"Line Harder Clemmensen\",\"Christoph Lütge\",\"Nicole Nadine Lønfeldt\",\"Sneha Das\"]","published":"2025-10-21T12:34:44Z","proceeding":"cs.CY","tasks":"[\"cs.CY\",\"cs.AI\"]","methods":"[]","has_code":false}