Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles

• URL: http://arxiv.org/abs/2304.11530v4
• Date: Thu, 21 Sep 2023 00:10:48 GMT
• Title: Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles
• Authors: Debesh Jha, Ashish Rauniyar, Abhiskek Srivastava, Desta Haileselassie Hagos, Nikhil Kumar Tomar, Vanshali Sharma, Elif Keles, Zheyuan Zhang, Ugur Demir, Ahmet Topcu, Anis Yazidi, Jan Erik H{\aa}akeg{\aa}rd, and Ulas Bagci
• Abstract summary: AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by matching the clinical level or surpassing clinical experts. The democratization of such AI tools can reduce the cost of care, optimize resource allocation, and improve the quality of care. integrating AI into healthcare raises several ethical and philosophical concerns, such as bias, transparency, autonomy, responsibility, and accountability.
• Score: 4.705984758887425
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by matching the clinical level or surpassing clinical experts. As a result, advanced healthcare services can be affordable to all populations, irrespective of demographics, race, or socioeconomic background. The democratization of such AI tools can reduce the cost of care, optimize resource allocation, and improve the quality of care. In contrast to humans, AI can uncover complex relations in the data from a large set of inputs and even lead to new evidence-based knowledge in medicine. However, integrating AI into healthcare raises several ethical and philosophical concerns, such as bias, transparency, autonomy, responsibility, and accountability. Here, we emphasize recent advances in AI-assisted medical image analysis, existing standards, and the significance of comprehending ethical issues and best practices for clinical settings. We cover the technical and ethical challenges and implications of deploying AI in hospitals and public organizations. We also discuss key measures and techniques to address ethical challenges, data scarcity, racial bias, lack of transparency, and algorithmic bias and provide recommendations and future directions.

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