Accepted for/Published in: JMIR Mental Health
Date Submitted: Jul 13, 2022
Open Peer Review Period: Jul 13, 2022 - Sep 7, 2022
Date Accepted: Oct 4, 2022
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Are we ready to "see" mental illness? Ethical implications concerning the use of language analysis technologies in diagnosing and forecasting psychiatric disorders
ABSTRACT
Recent developments in artificial intelligence technologies have come up 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 healthcare for preventive and early diagnosis initiatives, and for aiding professionals in the follow-up and prognosing 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 article we discuss the bioethical implications of using such technologies to diagnose and to predict future mental illness, given the current scenario of swiftly growing technologies to 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.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.