Ethical dilemmas in the relationship between professional and patient before the integration of the IA in psychiatric diagnosis

The purpose of this case study is to analyze the ethical and professional challenges that arise in the integration of artificial intelligence for psychiatric diagnosis, with special emphasis on the relationship between the health professional and the patient. The study included the review of scientific literature, analysis of ethical and regulatory standards, as well as the elaboration of a hypothetical clinical case in order to illustrate the issues that are associated with data privacy, as well as the dehumanization of care, aspects of clinical liability and the emergence of biases in algorithms. It was identified that AI is a tool that can improve diagnostic accuracy and personalization of treatments, but this implies risk in the use of sensitive data, the affectation of the therapeutic link and ambiguity in the assignment of responsibilities, as well as the perpetuation of structural inequalities and biases. The multidisciplinary analysis shows the need to balance the potential technological benefits with the protection of human values and ethical aspects in both diagnosis and treatment. It is concluded that AI in psychiatry must be implemented responsibly, ensuring transparency, equity, protection of patients' rights and humanity as the center of the relationship between professional and patient, which makes necessary a clear regulation about safe clinical practice in the digital era.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-07-04
DOI
https://doi.org/10.30574/wjarr.2025.27.1.2472
Primary Topic
Mental Health and Psychiatry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ethical dilemmas in the relationship between professional and patient before the integration of the IA in psychiatric diagnosis

José Fernando Mendez-Licona
World Journal of Advanced Research and Reviews
Mental Health and Psychiatry
article

Ethical dilemmas in the relationship between professional and patient before the integration of the IA in psychiatric diagnosis

José Fernando Mendez-Licona
article en

Abstract

The purpose of this case study is to analyze the ethical and professional challenges that arise in the integration of artificial intelligence for psychiatric diagnosis, with special emphasis on the relationship between the health professional and the patient. The study included the review of scientific literature, analysis of ethical and regulatory standards, as well as the elaboration of a hypothetical clinical case in order to illustrate the issues that are associated with data privacy, as well as the dehumanization of care, aspects of clinical liability and the emergence of biases in algorithms. It was identified that AI is a tool that can improve diagnostic accuracy and personalization of treatments, but this implies risk in the use of sensitive data, the affectation of the therapeutic link and ambiguity in the assignment of responsibilities, as well as the perpetuation of structural inequalities and biases. The multidisciplinary analysis shows the need to balance the potential technological benefits with the protection of human values and ethical aspects in both diagnosis and treatment. It is concluded that AI in psychiatry must be implemented responsibly, ensuring transparency, equity, protection of patients' rights and humanity as the center of the relationship between professional and patient, which makes necessary a clear regulation about safe clinical practice in the digital era.

World Journal of Advanced Research and ReviewsVol. 27(1)
Openalex Percentile: Top 83%
Mental Health and Psychiatry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.