Behind the mask: a critical perspective on the ethical, moral, and legal implications of AI in ophthalmology

Purpose This narrative review aims to provide an overview of the dangers, controversial aspects, and implications of artificial intelligence (AI) use in ophthalmology and other medical-related fields. Methods We conducted a decade-long comprehensive search (January 2013–May 2023) of both academic an...

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Bibliographic Details
Published in:Graefe's archive for clinical and experimental ophthalmology 2024-03, Vol.262 (3), p.975-982
Main Authors: Veritti, Daniele, Rubinato, Leopoldo, Sarao, Valentina, De Nardin, Axel, Foresti, Gian Luca, Lanzetta, Paolo
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Breakthroughs in artificial intelligence for ophthalmology
Databases, Factual
Decision making
Ethics
Health care
Humans
Medicine
Medicine & Public Health
Mini Review
Morals
Ophthalmology
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Summary:Purpose This narrative review aims to provide an overview of the dangers, controversial aspects, and implications of artificial intelligence (AI) use in ophthalmology and other medical-related fields. Methods We conducted a decade-long comprehensive search (January 2013–May 2023) of both academic and grey literature, focusing on the application of AI in ophthalmology and healthcare. This search included key web-based academic databases, non-traditional sources, and targeted searches of specific organizations and institutions. We reviewed and selected documents for relevance to AI, healthcare, ethics, and guidelines, aiming for a critical analysis of ethical, moral, and legal implications of AI in healthcare. Results Six main issues were identified, analyzed, and discussed. These include bias and clinical safety, cybersecurity, health data and AI algorithm ownership, the “black-box” problem, medical liability, and the risk of widening inequality in healthcare. Conclusion Solutions to address these issues include collecting high-quality data of the target population, incorporating stronger security measures, using explainable AI algorithms and ensemble methods, and making AI-based solutions accessible to everyone. With careful oversight and regulation, AI-based systems can be used to supplement physician decision-making and improve patient care and outcomes.
ISSN:0721-832X
1435-702X
DOI:10.1007/s00417-023-06245-4