Generative artificial intelligence (GenAI) and decision-making

Legal & ethical hurdles for implementation in mental health

Datos Bibliográficos

ID21458896
AutoresBarry Solaiman (0000-0002-2600-5075, Weill Cornell Medical College in Qatar, autor de correspondencia)
Año2024
Volumen97
Páginas102028
Fecha de publicación2024-11-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaInternational Journal of Law and Psychiatry (JOURNAL)
Identificadores de la revistaISSN: 0160-2527 • E-ISSN: 1873-6386
EditorialElsevier BV (PUBLISHER)
DOI10.1016/j.ijlp.2024.102028
PMID39426042
OpenAlexW4403526037
IdiomaEN
Citas recibidas1
Referencias citadas34

This article argues that significant risks are being taken with using GenAI in mental health that should be assessed urgently. It recommends that guidelines for using generative artificial intelligence (GenAI) in mental health care must be established promptly. Currently, clinicians using chatbots without appropriate approval risk undermining legal protections for patients. This could harm the patient and undermine the standards of the profession, undermining trust in an area where human involvement in decision-making is critical. To explore these concerns, this paper is divided into three parts. First, it examines the needs of patients in mental health. Second, it explores the potential benefits of GenAI in mental health and highlights the risks of its use as it pertains to patient needs. Third, it notes the ethical and legal concerns around data use and medical liability that require careful attention. The impact of the European Union's (EU) Artificial Intelligence Act (AI-Act) is also considered. It will be seen that these laws are insufficient in the context of mental health. As such, the paper recommends that guidelines should be developed to help resolve the existing legal gaps until codified rules are established

Engineering ethics · Generative grammar · Management science · Mental health · Psychiatry · Artificial Intelligence in Healthcare and Education · Computer Science · Engineering · Ethics in Clinical Research · Neuroethics, Human Enhancement, Biomedical Innovations · Psychology · Artificial Intelligence