How to mitigate the risks of deployment of artificial intelligence in medicine?


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Uygun İlikhan S., Özer M., Tanberkan H., Bozkurt V.

TURKISH JOURNAL OF MEDICAL SCIENCES, vol.54, no.3, pp.483-492, 2024 (SCI-Expanded)

  • Publication Type: Article / Article
  • Volume: 54 Issue: 3
  • Publication Date: 2024
  • Doi Number: 10.55730/1300-0144.5814
  • Journal Name: TURKISH JOURNAL OF MEDICAL SCIENCES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, MEDLINE, Veterinary Science Database, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.483-492
  • Istanbul University Affiliated: Yes

Abstract

Abstract: The aim of this study is to examine the risks associated with the use of artificial intelligence (AI) in medicine and to offer policy suggestions to reduce these risks and optimize the benefits of AI technology. AI is a multifaceted technology. If harnessed effectively, it has the capacity to significantly impact the future of humanity in the field of health, as well as in several other areas. However, the rapid spread of this technology also raises significant ethical, legal, and social issues. This study examines the potential dangers of AI integration in medicine by reviewing current scientific work and exploring strategies to mitigate these risks. Biases in data sets for AI systems can lead to inequities in health care. Educational data that is narrowly represented based on a demographic group can lead to biased results from AI systems for those who do not belong to that group. In addition, the concepts of explainability and accountability in AI systems could create challenges for healthcare professionals in understanding and evaluating AI-generated diagnoses or treatment recommendations. This could jeopardize patient safety and lead to the selection of inappropriate treatments. Ensuring the security of personal health information will be critical as AI systems become more widespread. Therefore, improving patient privacy and security protocols for AI systems is imperative. The report offers suggestions for reducing the risks associated with the increasing use of AI systems in the medical sector. These include increasing AI literacy, implementing a participatory society-in-the-loop management strategy, and creating ongoing education and auditing systems. Integrating ethical principles and cultural values into the design of AI systems can help reduce healthcare disparities and improve patient care. Implementing these recommendations will ensure the efficient and equitable use of AI systems in medicine, improve the quality of healthcare services, and ensure patient safety. Key words: Artificial intelligence, medicine, society-in-the-loop, bias, ChatGPT, accountability