Towards A Human-AI Hybrid Medicine: Future Medicine — A Hybrid System Where AI Complements Instead of Replaces Humans

Jurģis Šķilters; Juris Pokrotnieks; Aleksejs Derovs

doi:10.2478/prolas-2024-0032

.blurhash-client-img { display: none !important; }

Towards A Human-AI Hybrid Medicine: Future Medicine — A Hybrid System Where AI Complements Instead of Replaces Humans

Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences.

Volume 78 (2024): Issue 4 (August 2024)

By: Jurģis Šķilters, Juris Pokrotnieks and Aleksejs Derovs

Open Access

|Sep 2024

Abstract

Our paper provides a critical overview of the advantages, disadvantages, uncertainties, and challenges regarding AI application in medicine. Without denying the importance of the AI in medical applications, we are arguing for a hybrid and complementary view of future medical systems where powerful AI resources are integrated in and with human decision making.

References

Beam, A. L., Drazen, J. M., Kohane, I. S., Leong, T. Y., Manrai, A. K., Rubin, E. J. (2023). Artificial intelligence in medicine. New England J. Med., 388 (13), 1220–1221.
Search in Google Scholar Back to article
Binz, M., Schulz, E. (2023). Using cognitive psychology to understand GPT-3. Proc. Nat. Acad. Sci., 120 (6), e2218523120.
Search in Google Scholar Back to article
Bengio, Y., Hinton, G., Yao, A., Song, D., Abbeel, P., Harari, Y. N., Zhang, Y. Q., Xue, L., Shalev-Schwartz, S., Hadfield, G., et al. (2023). Managing AI risks in an era of rapid progress. Science, 384 (6698), 842–845. DOI: 10.1126/science.adn0.
Search in Google Scholar Back to article
Chemero, A. (2023). LLMs differ from human cognition because they are not embodied. Nat. Hum. Behav., 7 (11), 1828–1829.
Search in Google Scholar Back to article
Donald, M. (1993). Précis of origins of the modern mind: Three stages in the evolution of culture and cognition. Behav. Brain Sci., 16 (4), 737–748.
Search in Google Scholar Back to article
Goldberg, C. B., Adams, L., Blumenthal, D., Brennan, P. F., Brown, N., Butte, A. J., Cheatam, M., deBronkart, D., Dixon, J., Drazen, J., et al. (2024). To do no harm — and the most good — with AI in health care. NEJM AI, 1 (3), AIp2400036.
Search in Google Scholar Back to article
Hamzelou, J. (2023). Artificial Intelligence is infiltrating health care. We shouldn’t let it make all decisions. MIT Technol. Rev., April 21
Search in Google Scholar Back to article
Lenharo, M. (2023). An AI revolution is brewing in medicine. What will it look like? Nature, 622, 686–688.
Search in Google Scholar Back to article
Longoni, C., Bonezzi, A., Morewedge, C. K. (2019). Resistance to medical artificial intelligence. J. Consumer Res., 46 (4), 629–650.
Search in Google Scholar Back to article
Marcus, G. (2023). Hoping for the best as AI evolves. Communi. ACM, 66 (4), 6–7.
Search in Google Scholar Back to article
Messeri, L., Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627 (8002), 49–58.
Search in Google Scholar Back to article
Naddaf, M. (2023) ChatGPT generates fake data set to support scientific hypothesis. Nature, 623 (7989), 895-896. DOI: https://doi.org/10.1038/d41586-023-03635-w.
Search in Google Scholar Back to article
Pezzulo, G., Parr, T., Cisek, P., Clark, A., Friston, K. (2024). Generating meaning: Active inference and the scope and limits of passive AI. Trends Cognit. Sci., 28 (2), 97–112. DOI: https://doi.org/10.1016/j.tics.2023.10.002.
Search in Google Scholar Back to article
Rajpurkar, P., Chen, E., Banerjee, O., Topol, E. J. (2022). AI in health and medicine. Nature Med., 28 (1), 31–38.
Search in Google Scholar Back to article
Meskó, B., Topol, E. J. (2023). The imperative for regulatory oversight of large language models (or generative AI) in healthcare. npj Digital Medicine, 6 (1), 120.
Search in Google Scholar Back to article
Taylor, K. (2009). Paternalism, participation and partnership — the evolution of patient centeredness in the consultation. Patient Educ. Counsel., 74 (2), 150–155.
Search in Google Scholar Back to article
Veatch, R. M. (2000). Doctor does not know best: Why in the new century physicians must stop trying to benefit patients. J. Med. Philos., 25 (6), 701–721.
Search in Google Scholar Back to article
WHO (2023). WHO Outlines Considerations for Regulation of Artificial Intelligence for Health. https://www.who.int/news/item/19-10-2023-who-outlines-considerations-for-regulation-of-artificial-intelligence-for-health (accessed 11.08.2024).
Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.2478/prolas-2024-0032 | Journal eISSN: 2255-890X (formerly 1407-009X) | Journal ISSN: 1407-009X

Journal RSS Feed

Language: English

Page range: 233 - 238

Submitted on: Jul 5, 2024

Accepted on: Jul 24, 2024

Published on: Sep 5, 2024

Published by: Latvian Academy of Sciences

In partnership with: Paradigm Publishing Services

Keywords:

applications of AI in medicine,

artificial and natural cognitive systems,

medical safety,

medical sustainability

Related subjects:

Mathematics,

General mathematics

© 2024 Jurģis Šķilters, Juris Pokrotnieks, Aleksejs Derovs, published by Latvian Academy of Sciences
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 78 (2024): Issue 4 (August 2024)