AI/ML provides unprecedented opportunities for biomedical researchers, such as the quick identification of the genetic basis of diseases, including Alzheimer’s Disease. However, potential biases in the design and implementation of medical AI studies may lead to problematic findings and contribute to health disparity. While governments, corporations, non-governmental agencies, and bioethicists have laid down the basic ethical principles of AI research, researchers have yet to unpack the specific ethical challenges in medical AI research at the intersection of AI and biomedical research.

This NIH-funded interdisciplinary project developed a VR-based, interactive application for education on ethical decision-making medical AI in research.

Here are some of the publications that come out of this project.

Fantus, S., Li, J., Wang, T., & Tang, L. (2026). From awareness to action: Exploring ethical Knowledge, challenges, and institutional strategies among medical AI developers and researchers. Journal of Medical Internet Research. e79613. doi: 10.2196/79613. [Full text]  (Corresponding author)

Garcia, B., Seo, H, Fantus, S., Li, J., Wang, T., Tang, L. (2025). Enhancing AI ethics education: Developing a VR application to teach ethical principles to AI researchers. Proceedings of HCII 2025.

Tang, L., Li, J. & Fantus, S. (2023). Medical AI ethics: A systematic review of empirical studies. Digital Health, 9. https://doi.org/10.1177/20552076231186064 [Full text]

Zou, W., Li, J., Yang, Y., & Tang, L. (2023). Exploring the early adoption of Open AI among laypeople and technical professionals: An analysis of Twitter conversations on ChatGPT and GPT-3. International Journal of Human-Computer Interaction. DOI: 10.1080/10447318.2023.2295725 [Full text] [Summary]