Report
BibTex RIS Cite

Year 2025, Volume: 23 Issue: 2, 233 - 241, 09.08.2025

Abstract

References

  • 1. Keskinbora KH. Medical Doctors’ Perspective on Artificial Intelligence: Brief Overview. Am J Comp Sci Eng Surv 2020;8:1-4.
  • 2. The power of AI for health equity. (PATH) Dec 2023. Available date: May 30, 2024. [online] Available from: https://www.path.org/our-impact/articles/the-power-of-ai-for-health-equity/
  • 3. World Health Organization. Ethics and Governance of Artificial Intelligence for Health: WHO Guidance. License: CC BY-NC-SA 3.0 IGO. Geneva, Switzerland: World Health Organization; 2021.
  • 4. Uche-Anya E, Anyane-Yeboa A, Berzin TM, Ghassemi M, May FP. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity. Gut. Gut 2022;71(9):1909-1915. Epub 2022 Jun 10.
  • 5. Shen L, Margolies LR, Rothstein JH, Fluder E, McBride R, Sieh W. Deep Learning to Improve Breast Cancer Detection on Screening Mammography. Sci Rep 2019;9(1):12495.
  • 6. Burdick H, Lam C, Mataraso S, et al. Prediction of respiratory decompensation in COVID-19 patients using machine learning: The READY trial. Comput Biol Med 2020;124:103949.
  • 7. Nordling L. A fairer way forward for AI in health care. Nature 2019;573(7775):S103-S105.
  • 8. CDC, Public Health Surveillance and Data. Looking at AI’s Potential Impact on Health Equity. Available date: May 28, 2024. [online] Available from: https://www. cdc.gov/surveillance/data-modernization/snapshot/2022- snapshot/stories/ai-impact-health-equity.html
  • 9. Thomasian NM, Eickhoff C, Adashi EY. Advancing health equity with artificial intelligence. J Public Health Policy. 2021;42(4):602-611.
  • 10. Murphy K, Di Ruggiero E, Upshur R, et al. Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics 2021;22(1):14(1-17).
  • 11. USAID. Artificial intelligence in Global Health: Defining a Collective Path Forward, 2024. Available date: Nov 1, 2024. [online] Available from: https://www.usaid.gov/cii
  • 12. Farhud DD, Zokaei S. Ethical issues of artificial intelligence in medicine and healthcare. Iran J Public Health 2021;50(11):i-v.
  • 13. Ismail SJ, Hardy K, Tunis MC, Young K, Sicard N, Quach C. A framework for the systematic consideration of ethics, equity, feasibility, and acceptability in vaccine program recommendations. Vaccine 2020;38(36):5861-5876.
  • 14. Makhni S, Chin MH, Fahrenbach J, Rojas JC. Equity Challenges for Artificial Intelligence Algorithms in Health Care. Chest 2022;161(5):1343-1346.
  • 15. Rojas JC, Fahrenbach J, Makhni S, Cook SC, Williams JS, Umscheid CA, Chin MH. Framework for Integrating Equity into Machine Learning Models: A Case Study. Chest 2022;161(6):1621-1627. Epub 2022 Feb 7.
  • 16. Chen IY, Pierson E, Rose S, Joshi S, Ferryman K, Ghassemi M. Ethical Machine Learning in Healthcare. Annu Rev Biomed Data Sci 2021;4:123-144. Epub 2021 May 6.
  • 17. Abràmoff MD, Tarver ME, Loyo-Berrios N, et al. Considerations for addressing bias in artificial intelligence for health equity. NPJ Digit Med 2023;6(1):170.
  • 18. Johnson AE, Brewer LC, Echols MR, Mazimba S, Shah RU, Breathett K. Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure. Heart Fail Clin 2022;18(2):259-273. Epub 2022 Mar 4.
  • 19. Shaw J, Ali J, Atuire CA. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 2024;(25):46.
  • 20. Birhane A. Algorithmic injustice: a relational ethics approach. Patterns (N Y). 2021;2(2):100205.
  • 21. Keskinbora KH. Medical ethics considerations on artificial intelligence. J Clin Neurosci 2019;64:277-282.

Reframing artificial intelligence for global health equity and ethics

Year 2025, Volume: 23 Issue: 2, 233 - 241, 09.08.2025

Abstract

Artificial intelligence (AI) drives rapid changes in health systems and services worldwide. However,
the speed of change in health technology and research is not always followed by the same speed of
change in educational, legal, societal, and ethical aspects. AI has a huge potential to decrease global
health inequities. Yet, it also carries risks that might widen disparities. This report presents some of
the literature findings and discussion regarding AI, health equity, and ethics. Related to this, core
determinants of health equity in the AI era were discussed in light of medical ethics, and public
health principles and recommendations were developed with a special focus on increased community
participation, educational reforms, and alignment with global sustainability efforts. The main discussion
points and recommendations were summarized in a figure and a table, created by the co-authors. Current
literature suggests that implementing secure data storage, transparent quality assurance mechanisms, and
continuous monitoring and evaluation of newly introduced AI tools, including their effects on public and
environmental health outcomes, health equity, and ethics are needed for future policies and practices.
Health professionals, researchers, policymakers, and businesses need up-to-date guidelines, regulations,
and tools to enable the development and use of AI solutions to promote health equity, including principles
of medical and public health ethics. Community engagement in designing, implementing, and evaluating
AI solutions is crucial, especially to ensure that populations with vulnerabilities are not left behind.

Ethical Statement

Ethics approval was not needed in preparation of this work.

References

  • 1. Keskinbora KH. Medical Doctors’ Perspective on Artificial Intelligence: Brief Overview. Am J Comp Sci Eng Surv 2020;8:1-4.
  • 2. The power of AI for health equity. (PATH) Dec 2023. Available date: May 30, 2024. [online] Available from: https://www.path.org/our-impact/articles/the-power-of-ai-for-health-equity/
  • 3. World Health Organization. Ethics and Governance of Artificial Intelligence for Health: WHO Guidance. License: CC BY-NC-SA 3.0 IGO. Geneva, Switzerland: World Health Organization; 2021.
  • 4. Uche-Anya E, Anyane-Yeboa A, Berzin TM, Ghassemi M, May FP. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity. Gut. Gut 2022;71(9):1909-1915. Epub 2022 Jun 10.
  • 5. Shen L, Margolies LR, Rothstein JH, Fluder E, McBride R, Sieh W. Deep Learning to Improve Breast Cancer Detection on Screening Mammography. Sci Rep 2019;9(1):12495.
  • 6. Burdick H, Lam C, Mataraso S, et al. Prediction of respiratory decompensation in COVID-19 patients using machine learning: The READY trial. Comput Biol Med 2020;124:103949.
  • 7. Nordling L. A fairer way forward for AI in health care. Nature 2019;573(7775):S103-S105.
  • 8. CDC, Public Health Surveillance and Data. Looking at AI’s Potential Impact on Health Equity. Available date: May 28, 2024. [online] Available from: https://www. cdc.gov/surveillance/data-modernization/snapshot/2022- snapshot/stories/ai-impact-health-equity.html
  • 9. Thomasian NM, Eickhoff C, Adashi EY. Advancing health equity with artificial intelligence. J Public Health Policy. 2021;42(4):602-611.
  • 10. Murphy K, Di Ruggiero E, Upshur R, et al. Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics 2021;22(1):14(1-17).
  • 11. USAID. Artificial intelligence in Global Health: Defining a Collective Path Forward, 2024. Available date: Nov 1, 2024. [online] Available from: https://www.usaid.gov/cii
  • 12. Farhud DD, Zokaei S. Ethical issues of artificial intelligence in medicine and healthcare. Iran J Public Health 2021;50(11):i-v.
  • 13. Ismail SJ, Hardy K, Tunis MC, Young K, Sicard N, Quach C. A framework for the systematic consideration of ethics, equity, feasibility, and acceptability in vaccine program recommendations. Vaccine 2020;38(36):5861-5876.
  • 14. Makhni S, Chin MH, Fahrenbach J, Rojas JC. Equity Challenges for Artificial Intelligence Algorithms in Health Care. Chest 2022;161(5):1343-1346.
  • 15. Rojas JC, Fahrenbach J, Makhni S, Cook SC, Williams JS, Umscheid CA, Chin MH. Framework for Integrating Equity into Machine Learning Models: A Case Study. Chest 2022;161(6):1621-1627. Epub 2022 Feb 7.
  • 16. Chen IY, Pierson E, Rose S, Joshi S, Ferryman K, Ghassemi M. Ethical Machine Learning in Healthcare. Annu Rev Biomed Data Sci 2021;4:123-144. Epub 2021 May 6.
  • 17. Abràmoff MD, Tarver ME, Loyo-Berrios N, et al. Considerations for addressing bias in artificial intelligence for health equity. NPJ Digit Med 2023;6(1):170.
  • 18. Johnson AE, Brewer LC, Echols MR, Mazimba S, Shah RU, Breathett K. Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure. Heart Fail Clin 2022;18(2):259-273. Epub 2022 Mar 4.
  • 19. Shaw J, Ali J, Atuire CA. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 2024;(25):46.
  • 20. Birhane A. Algorithmic injustice: a relational ethics approach. Patterns (N Y). 2021;2(2):100205.
  • 21. Keskinbora KH. Medical ethics considerations on artificial intelligence. J Clin Neurosci 2019;64:277-282.
There are 21 citations in total.

Details

Primary Language English
Subjects Health Services and Systems (Other)
Journal Section Report
Authors

Kadircan Keskinbora 0000-0003-1940-1026

Özge Karadağ 0000-0003-1372-1555

Early Pub Date August 6, 2025
Publication Date August 9, 2025
Submission Date November 11, 2024
Acceptance Date June 25, 2025
Published in Issue Year 2025 Volume: 23 Issue: 2

Cite

APA Keskinbora, K., & Karadağ, Ö. (2025). Reframing artificial intelligence for global health equity and ethics. Turkish Journal of Public Health, 23(2), 233-241. https://doi.org/10.20518/tjph.1582811
AMA Keskinbora K, Karadağ Ö. Reframing artificial intelligence for global health equity and ethics. TJPH. August 2025;23(2):233-241. doi:10.20518/tjph.1582811
Chicago Keskinbora, Kadircan, and Özge Karadağ. “Reframing Artificial Intelligence for Global Health Equity and Ethics”. Turkish Journal of Public Health 23, no. 2 (August 2025): 233-41. https://doi.org/10.20518/tjph.1582811.
EndNote Keskinbora K, Karadağ Ö (August 1, 2025) Reframing artificial intelligence for global health equity and ethics. Turkish Journal of Public Health 23 2 233–241.
IEEE K. Keskinbora and Ö. Karadağ, “Reframing artificial intelligence for global health equity and ethics”, TJPH, vol. 23, no. 2, pp. 233–241, 2025, doi: 10.20518/tjph.1582811.
ISNAD Keskinbora, Kadircan - Karadağ, Özge. “Reframing Artificial Intelligence for Global Health Equity and Ethics”. Turkish Journal of Public Health 23/2 (August2025), 233-241. https://doi.org/10.20518/tjph.1582811.
JAMA Keskinbora K, Karadağ Ö. Reframing artificial intelligence for global health equity and ethics. TJPH. 2025;23:233–241.
MLA Keskinbora, Kadircan and Özge Karadağ. “Reframing Artificial Intelligence for Global Health Equity and Ethics”. Turkish Journal of Public Health, vol. 23, no. 2, 2025, pp. 233-41, doi:10.20518/tjph.1582811.
Vancouver Keskinbora K, Karadağ Ö. Reframing artificial intelligence for global health equity and ethics. TJPH. 2025;23(2):233-41.

                     13955                      13956                         13959                        28911                              13958

  

       

TURKISH JOURNAL OF PUBLIC HEALTH - TURK J PUBLIC HEALTH. online-ISSN: 1304-1096 

Copyright holder Turkish Journal of Public Health. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.