Evidence, ethics and the promise of artificial intelligence in psychiatry

被引:18
|
作者
McCradden, Melissa [1 ,2 ,3 ]
Hui, Katrina [4 ,5 ]
Buchman, Daniel Z. [1 ,4 ,6 ]
机构
[1] Univ Toronto, Joint Ctr Bioeth, Dalla Lana Sch Publ Hlth, Toronto, ON, Canada
[2] Hosp Sick Children, Bioeth, Toronto, ON, Canada
[3] Peter Gilgan Ctr Res & Learning, Genet & Genome Biol, Toronto, ON, Canada
[4] Ctr Addict & Mental Hlth, Everyday Ethics Lab, Toronto, ON, Canada
[5] Univ Toronto, Dept Psychiat, Toronto, ON, Canada
[6] Ctr Addict & Mental Hlth, Toronto, ON M6J 1H1, Canada
关键词
Psychiatry; Decision Making; Ethics-Medical; Mental Health; EVIDENCE-BASED MEDICINE; EPISTEMIC HUMILITY; HEALTH-CARE; BIG DATA; RISK;
D O I
10.1136/jme-2022-108447
中图分类号
B82 [伦理学(道德学)];
学科分类号
摘要
Researchers are studying how artificial intelligence (AI) can be used to better detect, prognosticate and subgroup diseases. The idea that AI might advance medicine's understanding of biological categories of psychiatric disorders, as well as provide better treatments, is appealing given the historical challenges with prediction, diagnosis and treatment in psychiatry. Given the power of AI to analyse vast amounts of information, some clinicians may feel obligated to align their clinical judgements with the outputs of the AI system. However, a potential epistemic privileging of AI in clinical judgements may lead to unintended consequences that could negatively affect patient treatment, well-being and rights. The implications are also relevant to precision medicine, digital twin technologies and predictive analytics generally. We propose that a commitment to epistemic humility can help promote judicious clinical decision-making at the interface of big data and AI in psychiatry.
引用
收藏
页码:573 / 579
页数:7
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