Centre for Social Ethics and Policy, Department of Law, School of Social Sciences, The University of Manchester, United Kingdom.
Int J Law Psychiatry. 2019 Sep-Oct;66:101479. doi: 10.1016/j.ijlp.2019.101479. Epub 2019 Aug 17.
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in order to regulate the use of ML in clinical research on psychosis prediction. It is argued that its lawful implementation will depend upon the legal requirements regarding the balance between potential harms and benefits, particularly with reference to: (i) any additional risks introduced by the use of ML for data analysis and outcome prediction; and (ii) the inclusion of vulnerable research populations such as minors or incapacitated adults. Second, this article investigates how clinical prediction via ML might affect the practice of risk assessment under mental health legislation, with reference to English Law. It is argued that there is a potential for virtuous applications of clinical prediction in psychiatry. However, reaffirming the distinction between psychosis risk and risk of harm is paramount. Establishing psychosis risk and assessing a person's risk of harm are discrete practices, and so should remain when using artificial intelligence for psychiatric assessment. Evaluating whether clinical prediction via ML might benefit individuals with psychosis will depend on which risk we try to assess and on what we try to predict, whether this is psychosis transition, a psychotic relapse, self-harm and suicidality, or harm to others.
机器学习（ML）的最新进展有可能彻底改变精神病预测和精神科评估。本文有两个目标。首先，它阐明了哪些英国法律方面与监管 ML 在精神病预测临床研究中的使用有关。有人认为，其合法实施将取决于潜在危害和收益之间的平衡的法律要求，特别是参考以下方面：（i）使用 ML 进行数据分析和结果预测带来的任何额外风险；以及（ii）将未成年人或无行为能力的成年人等弱势群体纳入研究对象。其次，本文调查了通过 ML 进行临床预测可能如何影响心理健康立法下的风险评估实践，参考英国法律。有人认为，精神病学中的临床预测有良性应用的潜力。然而，重申精神病风险和伤害风险之间的区别至关重要。确定精神病风险和评估一个人的伤害风险是两个不同的做法，因此在使用人工智能进行精神科评估时也应保持这一做法。评估通过 ML 进行临床预测是否可能使精神病患者受益，将取决于我们尝试评估的风险以及我们尝试预测的内容，无论是精神病发作的转变、精神病复发、自残和自杀倾向，还是对他人的伤害。
