The Cost-Benefit of Interdisciplinarity in AI for Mental Health

TL;DR

This paper analyzes the trade-offs of incorporating interdisciplinary expertise in AI mental health chatbots to enhance value-alignment, compliance, and effectiveness, emphasizing the importance of cross-disciplinary collaboration throughout the development lifecycle.

Contribution

It provides a systematic examination of the costs and benefits of interdisciplinary collaboration in AI mental health tools, offering practical recommendations and frameworks.

Findings

Interdisciplinary input improves chatbot safety and compliance.

Collaboration across disciplines enhances value alignment.

Practical frameworks facilitate interdisciplinary integration.

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.