The Cost-Benefit of Interdisciplinarity in AI for Mental Health
This addresses the challenge of ensuring effective and compliant AI mental health support for users, though it is incremental as it builds on existing frameworks and recommendations.
The paper tackles the problem of limited disciplinary input in AI mental health chatbots by examining the cost-benefit trade-off of interdisciplinary collaboration, arguing that involving experts from technology, healthcare, ethics, and law across lifecycle phases is essential for value-alignment and compliance with the AI Act.
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.