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, Goldenberg will describe the challenges and questions her team has resolved, and future directions for her ongoing work implementing AI techniques in a healthcare context.
Talk title:
“Designing machine learning for deployment in healthcare”
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 is ready to enable the future of medicine.
About Anna Goldenberg
Anna Goldenberg is a professor in the Departments of Computer Science and the Laboratory Medicine and Pathobiology at the University of Toronto. She is a Varma Family Chair in Biomedical Informatics and Artificial Intelligence at SickKids Research Institute as well as a CIFAR AI Chair at the Vector Institute. Goldenberg trained in machine learning at Carnegie Mellon University, with a postdoctoral focus in computational biology and medicine. The current focus of her lab is on developing and deploying machine learning models to healthcare. Goldenberg’s lab is strongly committed to creating responsible AI to benefit patients across a variety of conditions.
About Women in AI
Women in AI is a six-part virtual speaker and mentorship series developed by the Schwartz Reisman Institute for Technology and Society in collaboration with Deloitte that connects a global audience with a diverse group of female thought leaders in the field of AI research. The Women in AI series convenes leading female AI researchers to share knowledge and mentorship opportunities through seminar events that promote opportunities for women across the technology sector. Participants will explore how women are leading the development of new technologies and approaches, and investigating emerging trends across the sector. The series provides insights into cutting-edge research, bold points of views, and help business and community leaders elevate diverse voices while promoting opportunities for women to share their perspectives.
Anna Goldenberg