Social and ethical implications of AI-based facial technologies in medicine and healthcare: a scoping review
- 1CIES-Iscte, University Institute of Lisbon
- 2Institute of Social Sciences, Centre for Research in Anthropology (CRIA-UMinho/IN2PAST), University of Minho
- 3Department of Public Health and Caring Sciences, Centre for Research Ethics & Bioethics (CRB), Uppsala University
Abstract
Background AI-based facial technologies are increasingly explored in medicine and healthcare for purposes ranging from diagnosis and monitoring to identification. While ethical debates on AI-in-health are well developed, the specific social and ethical implications of facial AI in medical and healthcare contexts remain fragmented. Methods We conducted a scoping review following PRISMA-ScR guidelines to map the social and ethical implications of AI-based facial technologies reported in the literature and to examine how these implications are framed across disciplinary domains. Searches of PubMed and Web of Science up to 9 October 2025 identified 43 peer-reviewed articles that met the inclusion criteria. Data were extracted using a standardised template and synthesised through content analysis. Results Most articles were published after 2020 and were empirical in nature. The most frequently discussed issues concerned safety, clinical risk, privacy, surveillance, data governance, autonomy, and consent. These concerns largely align with established AI-in-health ethics and mainstream bioethical frameworks. Substantive engagements with social justice, stigma, appearance norms, and patient and public perspectives were less prominent. Ethical framings varied across disciplinary domains, with technical and clinical fields tending to adopt instrumental approaches, while bioethics, legal studies, and social sciences more often addressed broader sociopolitical implications. Conclusion The literature on AI-based facial technologies in medicine and healthcare largely reproduces generic AI-in-health ethical concerns, while under-analysing face-specific moral stakes linked to identity, visibility, stigma, and vulnerability. Addressing these gaps requires more context-sensitive interdisciplinary ethical approaches that integrate justice broadly conceived and incorporate patients and public perspectives into ethical governance.
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BibTeX
@article{machado2026social,
title = {{Social and ethical implications of AI-based facial technologies in medicine and healthcare: a scoping review}},
author = {Helena Machado and Susana Silva and João Santos and Niklas Juth},
journal = {BMC Medical Ethics},
year = {2026},
month = jul,
doi = {10.1186/s12910-026-01564-7},
url = {https://doi.org/10.1186/s12910-026-01564-7},
note = {CC BY},
}
RIS
TY - JOUR
TI - Social and ethical implications of AI-based facial technologies in medicine and healthcare: a scoping review
AU - Helena Machado
AU - Susana Silva
AU - João Santos
AU - Niklas Juth
PY - 2026
DA - 2026/07/01
JO - BMC Medical Ethics
DO - 10.1186/s12910-026-01564-7
UR - https://doi.org/10.1186/s12910-026-01564-7
AB - Background AI-based facial technologies are increasingly explored in medicine and healthcare for purposes ranging from diagnosis and monitoring to identification. While ethical debates on AI-in-health are well developed, the specific social and ethical implications of facial AI in medical and healthcare contexts remain fragmented. Methods We conducted a scoping review following PRISMA-ScR guidelines to map the social and ethical implications of AI-based facial technologies reported in the literature and to examine how these implications are framed across disciplinary domains. Searches of PubMed and Web of Science up to 9 October 2025 identified 43 peer-reviewed articles that met the inclusion criteria. Data were extracted using a standardised template and synthesised through content analysis. Results Most articles were published after 2020 and were empirical in nature. The most frequently discussed issues concerned safety, clinical risk, privacy, surveillance, data governance, autonomy, and consent. These concerns largely align with established AI-in-health ethics and mainstream bioethical frameworks. Substantive engagements with social justice, stigma, appearance norms, and patient and public perspectives were less prominent. Ethical framings varied across disciplinary domains, with technical and clinical fields tending to adopt instrumental approaches, while bioethics, legal studies, and social sciences more often addressed broader sociopolitical implications. Conclusion The literature on AI-based facial technologies in medicine and healthcare largely reproduces generic AI-in-health ethical concerns, while under-analysing face-specific moral stakes linked to identity, visibility, stigma, and vulnerability. Addressing these gaps requires more context-sensitive interdisciplinary ethical approaches that integrate justice broadly conceived and incorporate patients and public perspectives into ethical governance.
SN - 1472-6939
ER -