In JMIR mental health
Recent developments in artificial intelligence technologies have come to a point where machine learning algorithms can infer mental status based on someone's photos and texts posted on social media. More than that, these algorithms are able to predict, with a reasonable degree of accuracy, future mental illness. They potentially represent an important advance in mental health care for preventive and early diagnosis initiatives, and for aiding professionals in the follow-up and prognosis of their patients. However, important issues call for major caution in the use of such technologies, namely, privacy and the stigma related to mental disorders. In this paper, we discuss the bioethical implications of using such technologies to diagnose and predict future mental illness, given the current scenario of swiftly growing technologies that analyze human language and the online availability of personal information given by social media. We also suggest future directions to be taken to minimize the misuse of such important technologies.
Loch Alexandre Andrade, Lopes-Rocha Ana Caroline, Ara Anderson, Gondim João Medrado, Cecchi Guillermo A, Corcoran Cheryl Mary, Mota Natália Bezerra, Argolo Felipe C
2022-Nov-01
artificial intelligence, at-risk mental state, clinical high risk, digital phenotyping, machine learning, natural language processing, psychosis
