Ethical and legal challenges of artificial intelligence-driven healthcare
By Sara Gerke, Timo Minssen, Glenn Cohen. Artificial Intelligence in Healthcare, 2020
811 citations recorded by the source corpus.
This chapter will map the ethical and legal challenges posed by artificial intelligence (AI) in healthcare and suggest directions for resolving them. Section 1 will briefly clarify what AI is and Section 2 will give an idea of the trends and strategies in the United States (US) and Europe, thereby tailoring the discussion to the ethical and legal debate of AI-driven healthcare. This will be followed in Section 3 by a discussion of four primary ethical challenges, namely, (1) informed consent to use, (2) safety and transparency, (3) algorithmic fairness and biases, and (4) data privacy. Section 4 will then analyze five legal challenges in the US and Europe: (1) safety and effectiveness, (2) liability, (3) data protection and privacy, (4) cybersecurity, and (5) intellectual property law. Finally, Section 5 will summarize the major conclusions and especially emphasize the importance of building an AI-driven healthcare system that is successful and promotes trust and the motto Health AIs for All of Us.
Subfields: Health Informatics, Public Health, Environmental and Occupational Health, Safety Research
View Paper: https://www.semanticscholar.org/paper/152ef7762980f60ad23aa6fad59aaf7df9b82df0
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Citations in the corpus
- Revolutionizing healthcare: the role of artificial intelligence in clinical practice (2023, background): “Nevertheless, addressing the ethical risks associated with AI implementation is imperative, particularly concerning data privacy and confidentiality violations, informed consent, and patient autonomy [48, 119].”
- Multimodal biomedical AI (2022, background): “In contrast, the more recent General Data Protection Regulation (GDPR) from the European Union has a much broader scope regarding the definition of health data, and even goes beyond data protection to also require the release of information about automated decision-making using these data 164 .”
- Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? (2022, background): “To fully achieve the potential of AI in healthcare, four major ethical issues must be addressed: (1) informed consent to use data, (2) safety and transparency, (3) algorithmic fairness and biases, and (4) data privacy are all important factors to consider (27).”
- Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook (2024, neutral): “…health care domain, data often exhibit bias due to the uneven distribution of demographic attributes, preconceptions held by health care professionals involved in data collection and interpretation, and the varied academic and experiential backgrounds that influence their perspectives [175-177].”