# The Cost-Benefit of Interdisciplinarity in AI for Mental Health

arXiv: https://arxiv.org/abs/2510.18581 · HTML: https://mlsanity.com/paper/2510.18581/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 36 references that are in the map.
- First posted on arXiv 21 Oct 2025.

## Builds on (most cited first, 3 of 3)

- [AI Companions Reduce Loneliness](https://mlsanity.com/paper/2407.19096/) (2024)
- [An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives](https://mlsanity.com/paper/2310.17017/) (2023)
- [Interdisciplinarity as Diversity in Citation Patterns among Journals: Rao-Stirling Diversity, Relative Variety, and the Gini coefficient](https://mlsanity.com/paper/1807.04115/) (2018)

## Abstract (arXiv)

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.