Skip to main content

PERSPECTIVE article

Front. Psychiatry
Sec. Digital Mental Health
Volume 15 - 2024 | doi: 10.3389/fpsyt.2024.1407562
This article is part of the Research Topic Digitalization and Mental Health: Challenges and Ethical Aspects View all 4 articles

Ethical Trade-Offs in AI for Mental Health

Provisionally accepted
Sune Holm Sune Holm *
  • University of Copenhagen, Copenhagen, Denmark

The final, formatted version of the article will be published soon.

    It is expected that machine learning algorithms will enable better diagnosis, prognosis, and treatment in psychiatry. A central argument for deploying algorithmic methods in clinical decision-making in psychiatry is that they may enable not only faster and more accurate clinical judgments but also that they may provide a more objective foundation for clinical decisions. This article argues that the outputs of algorithms are never objective in the sense of being unaffected by human values and possibly biased choices. And it suggests that the best way to approach this is to ensure awareness of and transparency about the ethical trade-offs that must be made when developing an algorithm for mental health.

    Keywords: AI, Psychiatry, diagnosis, Mental Health, decision-making, fairness, Explainability So far, Østergaard

    Received: 26 Mar 2024; Accepted: 15 Jul 2024.

    Copyright: © 2024 Holm. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Sune Holm, University of Copenhagen, Copenhagen, Denmark

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.