Ethical Implications of the Use of Language Analysis Technologies for the Diagnosis and Prediction of Psychiatric Disorders.
Alexandre Andrade LochAna Caroline Lopes-RochaAnderson AraJoão Medrado GondimGuillermo A CecchiCheryl Mary CorcoranNatalia Bezerra MotaFelipe C ArgoloPublished in: JMIR mental health (2022)
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.
Keyphrases
- social media
- mental illness
- machine learning
- health information
- artificial intelligence
- mental health
- big data
- deep learning
- current status
- end stage renal disease
- endothelial cells
- newly diagnosed
- peritoneal dialysis
- healthcare
- prognostic factors
- induced pluripotent stem cells
- hepatitis c virus
- patient reported
- patient reported outcomes
- antiretroviral therapy