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A Review of the Ethical and Legal Challenges of Using Artificial Intelligence in the Health System

Yıl 2025, Cilt: 12 Sayı: 1, 307 - 318

Öz

Today, artificial intelligence technologies can provide unimaginable benefits to the health system. While artificial intelligence has significant potential to improve the performance of the health system, on the other hand, it also comes with challenges that sometimes lead to harm in the health system. Therefore, the aim of the present study is to review the ethical and legal challenges associated with the use of artificial intelligence in the health system. This is a review study. To collect information, an evidence search was used in the Web of Science, PubMed, and Scopus databases using the keywords artificial intelligence, medical ethics, health rights, health care, and human dignity. In all stages of the present research design, honesty and trustworthiness were observed, while respecting the originality of the text. The research findings regarding ethical challenges can be attributed to trust in artificial intelligence, violation of human dignity in artificial intelligence, respect for the principle of individual autonomy and its rules, artificial intelligence in the diagnosis of complete treatment, and artificial intelligence and emotional function. Legal challenges include standardization of artificial intelligence in medicine, artificial intelligence and civil liability, artificial intelligence and medical guarantees, artificial intelligence and violation of data privacy, and Artificial Intelligence and Cybersecurity are.

Kaynakça

  • Badal, K. et al. (2023). Guiding principles for the responsible development of artificial intelligence tools for healthcare. Communications Medicine, 3(1), 47.
  • Balthazar, P., et al. (2018). Protecting your patients’ interests in the era of big data, artificial intelligence and predictive analytics. Journal of the American College of Radiology.; 15(3), 580-586.
  • Bluemke, D.A. et al. (20209. Assessing radiology authors, reviewers and readers-from the radiology editorial board. Radiological Society of North America. Radiology, 294 (3), 487-489.
  • Cole, M., Cant, C., Ustek Spilda, F., & Graham, M. (2022). Politics by automatic means? A critique of artificial intelligence ethics at work. Frontiers in Artificial Intelligence, 5, 869114.
  • Gao, S. et al. (2020). Public perception of artificial intelligence in medical care: Content analysis of social media. Journal of Medical Internet Research, 22(7), e16649.
  • He, J. et al. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25 (1), 30-36.
  • Juravle, G. et al. (2020). Trust in artificial intelligence for medical diagnoses. Progress in Brain Research, 253, 263-282.
  • Masters, K. (2023). Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574-584.
  • Meskó, B. & Görög, M. (2020). A short guide for medical professionals in the era of artificial intelligence. NPJ Digital Medicine, 3 (1), 126. Moor, M. et al. (2023). Foundation models for generalist medical artificial intelligence. Nature, 616 (7956), 259-265.
  • Narayanan, A., & Shmatikov, V. (2009, May). De-anonymizing social networks. In 2009 30th IEEE symposium on security and privacy (pp. 173-187). IEEE.
  • Nyholm, L., Santamäki-Fischer, R., & Fagerström, L. (2021). Users’ ambivalent sense of security with humanoid robots in healthcare. Informatics for Health and Social Care, 46(2), 218-226.
  • Obermeyer, Z. et al. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366 (6464), 447-453.
  • Pashkov, V. M., Harkusha, A. O. & Harkusha, Y.O. (2020). Artificial intelligence in medical practice: Regulative issues and perspectives. Wiad Lek, 73(12 cz 2), 2722-2727.
  • Pepito, J. A. et al. (2020). Intelligent humanoid robots expressing artificial humanlike empathy in nursing situations. Nursing Philosophy, 21(4), e12318.
  • Price, I, et al. (2017). Artificial intelligence in health care: Applications and legal issues. The Sci Tech Lawyer, 14(1), 10-13.
  • Rodrigues, R. (2020). Legal and human rights issues of AI: Gaps, challenges and vulnerabilities. Journal of Responsible Technology, 4, 100005.
  • Yu, C. et al. (2022). Socially assistive robots for people with dementia: Systematic review and meta-analysis of feasibility, acceptability and the effect on cognition, neuropsychiatric symptoms and quality of life. Ageing Research Reviews, 78, 101633.
  • Yu, K.H, Beam, A.L. & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719-731.

A Review of the Ethical and Legal Challenges of Using Artificial Intelligence in the Health System

Yıl 2025, Cilt: 12 Sayı: 1, 307 - 318

Öz

Today, artificial intelligence technologies can provide unimaginable benefits to the health system. While artificial intelligence has significant potential to improve the performance of the health system, on the other hand, it also comes with challenges that sometimes lead to harm in the health system. Therefore, the aim of the present study is to review the ethical and legal challenges associated with the use of artificial intelligence in the health system. This is a review study. To collect information, an evidence search was used in the Web of Science, PubMed, and Scopus databases using the keywords artificial intelligence, medical ethics, health rights, health care, and human dignity. In all stages of the present research design, honesty and trustworthiness were observed, while respecting the originality of the text. The research findings regarding ethical challenges can be attributed to trust in artificial intelligence, violation of human dignity in artificial intelligence, respect for the principle of individual autonomy and its rules, artificial intelligence in the diagnosis of complete treatment, and artificial intelligence and emotional function. Legal challenges include standardization of artificial intelligence in medicine, artificial intelligence and civil liability, artificial intelligence and medical guarantees, artificial intelligence and violation of data privacy, and Artificial Intelligence and Cybersecurity are.

Kaynakça

  • Badal, K. et al. (2023). Guiding principles for the responsible development of artificial intelligence tools for healthcare. Communications Medicine, 3(1), 47.
  • Balthazar, P., et al. (2018). Protecting your patients’ interests in the era of big data, artificial intelligence and predictive analytics. Journal of the American College of Radiology.; 15(3), 580-586.
  • Bluemke, D.A. et al. (20209. Assessing radiology authors, reviewers and readers-from the radiology editorial board. Radiological Society of North America. Radiology, 294 (3), 487-489.
  • Cole, M., Cant, C., Ustek Spilda, F., & Graham, M. (2022). Politics by automatic means? A critique of artificial intelligence ethics at work. Frontiers in Artificial Intelligence, 5, 869114.
  • Gao, S. et al. (2020). Public perception of artificial intelligence in medical care: Content analysis of social media. Journal of Medical Internet Research, 22(7), e16649.
  • He, J. et al. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25 (1), 30-36.
  • Juravle, G. et al. (2020). Trust in artificial intelligence for medical diagnoses. Progress in Brain Research, 253, 263-282.
  • Masters, K. (2023). Ethical use of artificial intelligence in health professions education: AMEE Guide No. 158. Medical Teacher, 45(6), 574-584.
  • Meskó, B. & Görög, M. (2020). A short guide for medical professionals in the era of artificial intelligence. NPJ Digital Medicine, 3 (1), 126. Moor, M. et al. (2023). Foundation models for generalist medical artificial intelligence. Nature, 616 (7956), 259-265.
  • Narayanan, A., & Shmatikov, V. (2009, May). De-anonymizing social networks. In 2009 30th IEEE symposium on security and privacy (pp. 173-187). IEEE.
  • Nyholm, L., Santamäki-Fischer, R., & Fagerström, L. (2021). Users’ ambivalent sense of security with humanoid robots in healthcare. Informatics for Health and Social Care, 46(2), 218-226.
  • Obermeyer, Z. et al. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366 (6464), 447-453.
  • Pashkov, V. M., Harkusha, A. O. & Harkusha, Y.O. (2020). Artificial intelligence in medical practice: Regulative issues and perspectives. Wiad Lek, 73(12 cz 2), 2722-2727.
  • Pepito, J. A. et al. (2020). Intelligent humanoid robots expressing artificial humanlike empathy in nursing situations. Nursing Philosophy, 21(4), e12318.
  • Price, I, et al. (2017). Artificial intelligence in health care: Applications and legal issues. The Sci Tech Lawyer, 14(1), 10-13.
  • Rodrigues, R. (2020). Legal and human rights issues of AI: Gaps, challenges and vulnerabilities. Journal of Responsible Technology, 4, 100005.
  • Yu, C. et al. (2022). Socially assistive robots for people with dementia: Systematic review and meta-analysis of feasibility, acceptability and the effect on cognition, neuropsychiatric symptoms and quality of life. Ageing Research Reviews, 78, 101633.
  • Yu, K.H, Beam, A.L. & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719-731.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgi Güvenliği Yönetimi
Bölüm Makaleler
Yazarlar

Mohammad Ekram Yawar 0000-0003-3198-5212

Mohammad Qurban Hakımı 0009-0005-6121-5069

Erken Görünüm Tarihi 17 Şubat 2025
Yayımlanma Tarihi
Gönderilme Tarihi 9 Eylül 2024
Kabul Tarihi 4 Şubat 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 12 Sayı: 1

Kaynak Göster

APA Yawar, M. E., & Hakımı, M. Q. (2025). A Review of the Ethical and Legal Challenges of Using Artificial Intelligence in the Health System. Akademik Tarih Ve Düşünce Dergisi, 12(1), 307-318.

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