Holm Sune
Department of Food and Resource Economics, University of Copenhagen, Frederiksberg, Denmark.
Front Psychiatry. 2024 Aug 29;15:1407562. doi: 10.3389/fpsyt.2024.1407562. eCollection 2024.
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.
预计机器学习算法将在精神病学中实现更好的诊断、预后和治疗。在精神病学临床决策中采用算法方法的一个核心论点是，它们不仅可以实现更快、更准确的临床判断，还可以为临床决策提供更客观的基础。本文认为，算法的输出在不受人类价值观和可能存在的偏见选择影响的意义上绝不是客观的。并且它表明，处理这个问题的最佳方法是确保在开发心理健康算法时，对必须做出的伦理权衡有认识并保持透明。
