WiM Presents: Integrating Ethics into AI Development - March 3, 2025

Monday 17th February 2025

Women in MICCAI (WiM) is happy to announce the fourth invited talk in the WiM "Health Equity in the AI Era" Webinar Series

Integrating Ethics into AI development: Towards Robust Interdisciplinary Collaborations

Speaker: Dr. Elise Li Zheng, Columbia University Irving Medical Center
Monday, March 3, 2025
5:00 - 6:00 PM UTC / 9:00 - 10:00 AM PST / 12:00 – 1:00 PM EST

The last decade has seen an unprecedented growth in Artificial Intelligence (AI), with various tools and approaches being introduced to the medical and healthcare fields. Developing ethical, inclusive, and equitable AI tools and datasets requires interdisciplinary collaborations and meaningful community engagement. However, forging collaborative relationships in the field of AI presents multiple challenges: What is the scope of ethical AI? Who are considered experts? What institutional and organizational arrangements can foster equitable collaborations between scientists, engineers, social scientists, and impacted communities?

This presentation draws on findings from case studies of US federal-funded national AI consortia in biomedicine and healthcare to explore the current challenges of integrating ethics into medical AI and strategies for cultivating a robust ethics culture in research collaborations.

Join us on Monday, March 3, 2025 at 5:00 PM-6:00 PM UTC / 9:00 AM-10:00 AM PST / 12:00-1:00 PM EST

Register here

About the Speaker:

Elise Li Zheng is a postdoctoral research scientist at the Division of Ethics, Columbia University Irving Medical Center. Her research focuses on the ethical and social implications of digital health data, with a particular emphasis on the integration of consumer wearable data into healthcare practices. Her interdisciplinary work spans AI ethics, big data ethics, and human-technology interactions. Elise earned her PhD in Science and Technology Studies from the Georgia Institute of Technology, where she studied in the sociotechnical dimensions of self-tracking.