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Maccaro A, Stokes K, Statham L, He L, Williams A, Pecchia L, Piaggio D. Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices. J Pers Med 2024; 14:443. [PMID: 38793025 PMCID: PMC11121798 DOI: 10.3390/jpm14050443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 05/26/2024] Open
Abstract
The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications of such technologies. The presented scoping review captures the progression of the ethical and legal debate and the proposed ethical frameworks available concerning the use of AI-based medical technologies, capturing key themes across a wide range of medical contexts. The ethical dimensions are synthesised in order to produce a coherent ethical framework for AI-based medical technologies, highlighting how transparency, accountability, confidentiality, autonomy, trust and fairness are the top six recurrent ethical issues. The literature also highlighted how it is essential to increase ethical awareness through interdisciplinary research, such that researchers, AI developers and regulators have the necessary education/competence or networks and tools to ensure proper consideration of ethical matters in the conception and design of new AI technologies and their norms. Interdisciplinarity throughout research, regulation and implementation will help ensure AI-based medical devices are ethical, clinically effective and safe. Achieving these goals will facilitate successful translation of AI into healthcare systems, which currently is lagging behind other sectors, to ensure timely achievement of health benefits to patients and the public.
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Affiliation(s)
- Alessia Maccaro
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
| | - Katy Stokes
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
| | - Laura Statham
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
- Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK
| | - Lucas He
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
- Faculty of Engineering, Imperial College, London SW7 1AY, UK
| | - Arthur Williams
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
| | - Leandro Pecchia
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
- Intelligent Technologies for Health and Well-Being: Sustainable Design, Management and Evaluation, Faculty of Engineering, Università Campus Bio-Medico Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy
| | - Davide Piaggio
- Applied Biomedical Signal Processing Intelligent eHealth Lab, School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (A.M.); (K.S.); (L.S.); (L.H.); (A.W.); (L.P.)
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Alanzi T, Alhajri A, Almulhim S, Alharbi S, Alfaifi S, Almarhoun E, Mulla R, Alasafra ZO, Alalwan Z, Alnasser F, Almukhtar F, Al Ghadeer F, Amro S, Alodhayb I, Alanzi N. Artificial Intelligence and Patient Autonomy in Obesity Treatment Decisions: An Empirical Study of the Challenges. Cureus 2023; 15:e49725. [PMID: 38161816 PMCID: PMC10757560 DOI: 10.7759/cureus.49725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2023] [Indexed: 01/03/2024] Open
Abstract
Background This study aims to explore the factors associated with artificial intelligence (AI) and patient autonomy in obesity treatment decision-making. Methodology A cross-sectional, online, descriptive survey design was adopted in this study. The survey instrument incorporated the Ideal Patient Autonomy Scale (IPAS) and other factors affecting patient autonomy in the AI-patient relationship. The study participants included 74 physicians, 55 dieticians, and 273 obese patients. Results Different views were expressed in the scales AI knows the best (μ = 2.95-3.15) and the patient should decide (μ = 2.95-3.16). Ethical concerns (μ = 3.24) and perceived privacy risks (μ = 3.58) were identified as having a more negative influence on patient autonomy compared to personal innovativeness (μ = 2.41) and trust (μ = 2.85). Physicians and dieticians expressed significantly higher trust in AI compared to patients (p < 0.05). Conclusions Patient autonomy in the AI-patient relationship is significantly affected by privacy, trust, and ethical issues. As trust is a multifaceted factor and AI is a novel technology in healthcare, it is essential to fully explore the various factors influencing trust and patient autonomy.
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Affiliation(s)
- Turki Alanzi
- Department of Health Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, SAU
| | - Ahlam Alhajri
- College of Agricultural and Food Sciences, King Faisal University, Al Hofuf, SAU
| | - Sara Almulhim
- College of Medicine, King Faisal University, Al Hofuf, SAU
| | - Sara Alharbi
- College of Applied Medical Sciences, Umm Al-Qura University, Makkah, SAU
| | - Samya Alfaifi
- College of Pharmacy, Umm Al-Qura University, Makkah, SAU
| | - Eslam Almarhoun
- Family Medicine, South Khobar Primary Healthcare Center, Khobar, SAU
| | - Raghad Mulla
- College of Medicine, King Abdulaziz University, Jeddah, SAU
| | | | - Zainab Alalwan
- College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, SAU
| | - Fatima Alnasser
- College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, SAU
| | - Fatima Almukhtar
- Medicine and Surgery, King Fahad University Hospital, Khobar, SAU
| | | | - Sara Amro
- Family Medicine, King Fahad Armed Forces Hospital, Jeddah, SAU
| | - Ibrahim Alodhayb
- College of Agriculture and Veterinary Medicine, Qassim University, Buraydah, SAU
| | - Nouf Alanzi
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf university, Sakakah, SAU
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