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Physicians' ethical concerns about artificial intelligence in medicine: a qualitative study: . | LitMetric

AI Article Synopsis

Article Abstract

Background/aim: Artificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sentience or consciousness but focuses on data processing, pattern recognition, and prediction through algorithms and learned experiences. In healthcare including neuroscience, AI is valuable for improving prevention, diagnosis, prognosis, and surveillance.

Methods: This qualitative study aimed to investigate the acceptability of AI in Medicine (AIIM) and to elucidate any technical and scientific, as well as social and ethical issues involved. Twenty-five doctors from various specialties were carefully interviewed regarding their views, experience, knowledge, and attitude toward AI in healthcare.

Results: Content analysis confirmed the key ethical principles involved: confidentiality, beneficence, and non-maleficence. Honesty was the least invoked principle. A thematic analysis established four salient topic areas, i.e., , , and . Alongside the advantages, there were many limitations and risks. The study revealed a perceived need for precautions to be embedded in healthcare policies to counter the risks discussed. These precautions need to be multi-dimensional.

Conclusion: The authors conclude that AI should be rationally guided, function transparently, and produce impartial results. It should assist human healthcare professionals collaboratively. This kind of AI will permit fairer, more innovative healthcare which benefits patients and society whilst preserving human dignity. It can foster accuracy and precision in medical practice and reduce the workload by assisting physicians during clinical tasks. AIIM that functions transparently and respects the public interest can be an inspiring scientific innovation for humanity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11631923PMC
http://dx.doi.org/10.3389/fpubh.2024.1428396DOI Listing

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