Evidence-Based Reviews

Artificial intelligence in psychiatry

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References

The Nuffield Council on Bioethics also emphasizes the importance of identifying the ethical issues raised by using AI in health care. Concerns include erroneous decisions made by AI and determining who is responsible for such errors, difficulty in validating the outputs of AI systems, and the potential for AI to be used for malicious purposes.29

For clinicians who are considering implementing AI into their practice, it is vital to recognize where this technology belongs in a workflow and in the decision-making process. Jeffery Axt, a researcher on the clinical applications of AI, encourages clinicians to view using AI as a consulting tool to eliminate the element of fear associated with not having control over diagnostics and management.30

What’s on the horizon

Research into using AI in psychiatry has drawn the attention of large companies. IBM is building an automated speech analysis application that uses machine learning to provide a real-time overview of a patient’s mental health.31 Social media platforms are also starting to incorporate AI technologies to scan posts for language and image patterns suggestive of suicidal thoughts or behavior.32

“Chat bots”—AI that can conduct a conversation in natural language—are becoming popular as well. Woebot is a cognitive-behavioral therapy–based chat bot designed by a Stanford psychologist that can be accessed through Facebook Messenger. In a 2-week study, 70 young adults (age 18 to 28) with depression were randomly assigned to use Woebot or to read mental health e-books.33 Participants who used Woebot experienced a significant reduction in depressive symptoms as measured by change in score on the Patient Health Questionnaire-9, while those assigned to the reading group did not.33

Other researchers have focused on identifying patterns of inattention, hyperactivity, and impulsivity in children using AI technologies such as computer vision, machine learning, and data mining. For example, researchers at the University of Texas at Arlington and Yale University are analyzing data from watching children perform certain tasks involving attention, decision making, and emotion management.34 There have been several advances in using AI to note abnormalities in a child’s gaze pattern that might suggest autism.35

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