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

Author:

Veritti DanieleORCID,Rubinato Leopoldo,Sarao Valentina,De Nardin Axel,Foresti Gian Luca,Lanzetta Paolo

Abstract

Abstract 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.

Funder

Università degli Studi di Udine

Publisher

Springer Science and Business Media LLC

Subject

Cellular and Molecular Neuroscience,Sensory Systems,Ophthalmology

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. United Nations Roundtable on Telemedicine: Lessons Learned and Differing Perspectives (Preprint);2024-07-12

2. Motivations and Barriers to Using Digital Healthcare;Advances in Healthcare Information Systems and Administration;2024-03-29

3. Introduction to Machine Learning;Studies in Computational Intelligence;2024

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