Ethical Implications of the Use of Language Analysis Technologies for the Diagnosis and Prediction of Psychiatric Disorders

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 me...

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Bibliographic Details
Published in:JMIR mental health 2022-11, Vol.9 (11), p.e41014-e41014
Main Authors: Loch, Alexandre Andrade, Lopes-Rocha, Ana Caroline, Ara, Anderson, Gondim, João Medrado, Cecchi, Guillermo A, Corcoran, Cheryl Mary, Mota, Natália Bezerra, Argolo, Felipe C
Format: Article
Language:English
Subjects:
Artificial intelligence
Bioethics
Cancer
Communication
Language
Machine learning
Medical diagnosis
Medical personnel
Mental disorders
Mental health
Privacy
Professionals
Psychosis
Schizophrenia
Social networks
Stigma
Thyroid gland
Viewpoint
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Summary: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.
ISSN:2368-7959
2368-7959
DOI:10.2196/41014