SRI: Women in AI- Anna Goldenberg: “Designing machine learning for deployment in healthcare”

The Women in AI speaker series, a collaboration between the Schwartz Reisman Institute for Technology and Society and Deloitte, welcomes Anna Goldenberg, a professor in the University of Toronto’s Departments of Computer Science and Laboratory Medicine and Pathobiology, Varma Family Chair in Biomedical Informatics and Artificial Intelligence at SickKids Research Institute, and CIFAR AI Chair at the Vector Institute. Goldenberg’s research focuses on developing and deploying machine learning models to healthcare, and is committed to developing responsible AI techniques that benefit patients across a variety of conditions.

In this talk, Goldenberg will explore how machine learning is poised to become a crucial part of decision-making in healthcare. Examining several of her recent projects, Goldberg will describe the challenges and questions her team has resolved, and future directions for her ongoing work implementing AI techniques in a healthcare context.

Abstract: Machine learning is poised to become an important part of decision-making in healthcare. There is a growing support for AI integration into clinical practice as well. And yet, the reality of enabling AI in healthcare broadly is fraught with many obstacles from ethical to legal to still fundamentally unresolved machine learning issues. In this talk, I will cover several AI for healthcare projects that we have worked on to date, and the many machine learning and broad computer science questions that we had to solve—and are still solving—along the way. Finally, I will discuss some of the future work that is necessitated by our commitment to designing AI for deployment and where I believe we should focus our efforts to ensure that the technology

Please register: Women in AI