The AI-Futures Hot Topic Action Group (AI-Futures HTAG) seeks to proactively engage health professional educators in critical discussions around artificial intelligence (AI) within Health Professional Education (HPE). This HTAG proposes to address a strategic priority that is poised to impact significantly on healthcare practice and education.

The group will serve as a think tank, offering insights and guidance to the HPE community on learning, teaching and assessment, and ethical considerations of AI in education. Through thought leadership, the HTAG will help shape the future direction of health professions education in the context of rapid technological advancement.

HTAG leads: Chinthaka Balasooriya and Margo Lane

If you would like to be involved in this HTAG, please express your interest via this link. The HTAG leads, Chinthaka Balasooriya or Margo Lane can be contacted via c.balasooriya@unsw.edu.au or margo.lane@unsw.edu.au (please cc to the anzahpe office).

Please note: HTAGs are open to members of ANZAHPE; if non-ANZAHPE members decide to join a HTAG, they  must become a member of ANZAHPE  to take part in the group.

Resources:

·  Lodge, J. M., Howard, S., Bearman, M., Dawson, P., Agostinho, S., Buckingham Shum, S., et al. (2023). Assessment reform for the age of artificial intelligence. TEQSA. Retrieved from https://www.teqsa.gov.au/guides-resources/resources/corporate-publications/assessment-reform-age-artificial-intelligence

·  Al-Amoudi, I. (2022). Are post-human technologies dehumanizing? Human enhancement and artificial intelligence in contemporary societies. Journal of Critical Realism, 21(5), 516-538. link

·  Fawns, T., & Schuwirth, L. (2024). Rethinking the value proposition of assessment at a time of rapid development in generative artificial intelligence. Medical Education, 58(1), 14-16. Link

·  Bearman, M., Tai, J., Dawson, P., Boud, D., & Ajjawi, R. (2024). Developing evaluative judgement for a time of generative artificial intelligence. Assessment & Evaluation in Higher Education, 1-13. Link

·  Cukurova, M., Miao, X., & Brooker, R. (Eds.). (2023). Adoption of artificial intelligence in schools: Unveiling factors influencing teachers’ engagement. International Conference on Artificial Intelligence in Education. Springer. Link

·  Lodge, J. M., Yang, S., Furze, L., & Dawson, P. (2023). It’s not like a calculator, so what is the relationship between learners and generative artificial intelligence? Learning: Research and Practice, 9(2), 117-124. Link

·  Semmler, C. A., & Tikhomirov, L. (2023). Responsible AI means keeping humans in the loop. In Responsible AI: Your questions answered. Australian Academy of Technological Sciences and Engineering (ATSE). Retrieved from https://www.atse.org.au/what-we-do/strategic-advice/responsible-ai-essays/

·  Tikhomirov, L., Semmler, C., McCradden, Searston, R. A., & Oakden-Rayner, L. (in press). Medical AI for Radiology: The Lost Cognitive Perspective. The Lancet: Digital Health. https://doi.org/10.31234/osf.io/79hvb

·  McCradden, M., Hui, K., & Buchman, D. Z. (2023). Evidence, ethics and the promise of artificial intelligence in psychiatry. Journal of Medical Ethics, 49, 573-579. link

·  Balasooriya, C., Lyons, K., Tran, M., Pather, N., Chur-Hansen, A., & Steketee, C. (2024). Learning, teaching and assessment in health professional education and scholarship in the next 50 years. Focus on Health Professional Education: A Multi-Professional Journal, 25(2), 110–129. https://doi.org/10.11157/fohpe.v25i2.785

·  Dhiman, P., Whittle, R., Van Calster, B., et al. (2023). The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nature Machine Intelligence, 5, 816–817. https://doi.org/10.1038/s42256-023-00705-6

·  Balasooriya, C. (2024). AI in education: A futuristic vision. Medical Teacher, 46(7), 986-988. https://doi.org/10.1080/0142159X.2024.2352160