Ethical Considerations of Augmenting Healthcare and Clinical Decisions with Artificial Intelligence: Current Issues and Future Considerations

Presented by:
Dr. Besa Bauta, Ph.D., MPH, MSW
Adj. Assistant Professor
Silver School of Social Work
New York University

Faculty Disclosure:

Dr. Bauta has disclosed that she has no relevant financial relationships. No one else in a position to control content has any financial relationships to disclose.

Conflict of interest information for the CME Advisory Committee members can be found on the following website: All relevant financial relationships have been mitigated.

Release Date: October 29, 2022
Expiration Date:  October 28, 2025

Target Audience: All physicians

Learning Objectives:

As a result of participation in this activity, participants should be able to:

  1. Recognize the use of Artificial Intelligence applications in healthcare settings.
  2. Identify how AI/ML applications can support and/or augment clinical decision-making.
  3. Evaluate how AI-based applications enhance or alter clinical decision-making.
  4. Identify ethical challenges with AI/ML applications in healthcare and clinical settings.
  5. Determine how commercialization, privatization, and outsourcing of healthcare technology impacts the provision of health, discovery, and research.

Requirements for successful completion: Certificates are awarded upon successful completion (80% proficiency) of the post-test.

Accreditation: The University of Florida College of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

Credit: The University of Florida College of Medicine designates this enduring material for a maximum of 1 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Resource(s) for further study:

  1.  Turing, AM. Computing Machinery and Intelligence.
  2. Stanford. One Hundred Year Study on Artificial Intelligence, 2016 Report.
  7. WHO and partners launch world’s most extensive freely accessible AI health worker. Oct 4, 2022.
  8. CA Cancer J Clin. March/April 2019. Doi: 10.3322/caac.21552.CCBY4
  9. Johnson KB, Wei WQ, Weeraratne D, Frisse ME, Misulis K, Rhee K, Zhao J, Snowdon JL. Precision Medicine, AI, and the Future of Personalized Health Care. Clin Transl Sci. 2021 Jan;14(1):86-93. doi: 10.1111/cts.12884.
  10. Ćosić K, Popović S, Šarlija M, Kesedžić I, Jovanovic T. Artificial intelligence in prediction of mental health disorders induced by the COVID-19 pandemic among health care workers. Croat Med J. 2020 Jul 5;61(3):279-288. doi: 10.3325/cmj.2020.61.279. PMID: 32643346; PMCID: PMC7358693.
  11. Rastpour A, McGregor C. Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach. JMIR Ment Health 2022;9(8):e38428. URL:  DOI: 10.2196/38428
  13. Kenner B, Chari ST, Kelsen D, Klimstra DS, Pandol SJ, Rosenthal M, Rustgi AK, Taylor JA, Yala A, Abul-Husn N, Andersen DK, Bernstein D, Brunak S, Canto MI, Eldar YC, Fishman EK, Fleshman J, Go VLW, Holt JM, Field B, Goldberg A, Hoos W, Iacobuzio-Donahue C, Li D, Lidgard G, Maitra A, Matrisian LM, Poblete S, Rothschild L, Sander C, Schwartz LH, Shalit U, Srivastava S, Wolpin B. Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review. Pancreas. 2021 Mar 1;50(3):251-279. doi: 10.1097/MPA.0000000000001762. PMID: 33835956; PMCID: PMC8041569.
  14. CiteKenner, Barbara PhD; Chari, Suresh T. MD; Kelsen, David MD; Klimstra, David S. MD; Pandol, Stephen J. MD; Rosenthal, Michael MD, PhD; Rustgi, Anil K. MD; Taylor, James A. MD; Yala, Adam MEng; Abul-Husn, Noura MD, PhD; Andersen, Dana K. MD, FACS; Bernstein, David PhD; Brunak, Søren PhD; Canto, Marcia Irene MD, MHS; Eldar, Yonina C. PhD; Fishman, Elliot K. MD; Fleshman, Julie JD, MBA; Go, Vay Liang W. MD; Holt, Jane M. BA; Field, Bruce BS; Goldberg, Ann BA; Hoos, William MBA; Iacobuzio-Donahue, Christine MD, PhD; Li, Debiao PhD; Lidgard, Graham PhD; Maitra, Anirban MBBS; Matrisian, Lynn M. PhD, MBA; Poblete, Sung RN, PhD; Rothschild, Laura MBA; Sander, Chris PhD; Schwartz, Lawrence H. MD; Shalit, Uri PhD; Srivastava, Sudhir PhD, MPH, MS; Wolpin, Brian MD, MPH. Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review. Pancreas: March 2021 – Volume 50 – Issue 3 – p 251-279 doi: 10.1097/MPA.0000000000001762.
  15. Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. Artificial Intelligence in Healthcare. 2020:295–336. doi: 10.1016/B978-0-12-818438-7.00012-5. Epub 2020 Jun 26. PMCID: PMC7332220.
  16. Sharova D.E., Zinchenko V.V., Akhmad E.S., Mokienko O.A., Vladzymyrskyy A.V., Morozov S.P. On the issue of ethical aspects of the artificial intelligence systems implementation in healthcare // Digital Diagnostics. – 2021. – Vol. 2. – N. 3. – P. 356-368. doi: 10.17816/DD77446
  17. Stanford University. One Hundred Year Study on Artificial Intelligence (AI100).
  18. Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, and Toby Walsh. “Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report.” Stanford University, Stanford, CA, September 2021. Doc: Accessed: September 16, 2021.
  19. Crigger E, Reinbold K, Hanson C, Kao A, Blake K, Irons M. Trustworthy Augmented Intelligence in Health Care. J Med Syst. 2022 Jan 12;46(2):12. doi: 10.1007/s10916-021-01790-z. PMID: 35020064; PMCID: PMC8755670.
  20. UNESCO. Recommendation on the Ethics of Artificial Intelligence. Retrieved on October 24, 2022.
  21. AMA. 2019 Board Report: Augmented Intelligence in Health Care. Retrieved on October 24, 2022.
  22. NAII.  National AI Strategy.  Retrieved on October 24, 2022.
  23. Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? Frontiers in Surgery, v9. Available from
  24. Machine learning in medicine: Addressing ethical challenges. Vayena E, Blasimme A, Cohen IG (2018) Machine learning in medicine: Addressing ethical challenges. PLOS Medicine 15(11): e1002689.

If you have any questions please feel free to contact Nancy Boyd at (352) 594-4298 or at