AI and Digital Technology: What does this mean for the future of epidemiology?
Laura Rosella, PhD, MHSc
Associate Professor | Dalla Lana School of Public Health | University of Toronto
Where: Hybrid Event | 2001 McGill College, Room 1140; Zoom
The role of data and analytics has never been more important in society and, in particular, for informing public health decisions. There has been a rapid change in the nature of data used in epidemiologic research and an increased focus on the use of Artificial Intelligence (AI) in the analysis of those emerging data sources. There are many conflicting points of view on the utility of AI in an epidemiologic context and a lack of clarity on the implications for the discipline and public health more generally. This talk will cover the myths, the debates, and the skepticism (from all sides) and outline a proposed direction for the role of AI in the future of epidemiology. We will additionally cover the intersection of AI with a precision public health frame and the potential impact and unintended consequences of this framing. The talk will include implications related to bias, health equity, surveillance and causal inference. We will conclude by summarizing the implications for epidemiology research and training.
- Define Artificial Intelligence (AI) and Machine Learning (ML) in the context of epidemiology and public health
- Describe how advanced in AI/ML intersects with issues related to bias, health equity, surveillance and causal inference
- Summarize the building blocks needed to build capacity and mitigate concerns as AI applications in epidemiology grow
Laura Rosella is the Principal Investigator and Scientific Director of the Population Health Analytics Lab. She is an Associate Professor at the Dalla Lana School of Public Health at the University of Toronto, where she holds Canada Research Chair in Population Health Analytics, the Stephen Family Research Chair in Community Health at the Institute for Better Health, Trillium Health Partners, the Education Lead for the Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM), and the Associate Director of Education and Training at the University of Toronto’s Data Science Initiative (DSI). Her additional scientific appointments include Faculty Affiliate at the Vector Institute and the Schwartz Reisman Institute and Site Director for ICES UofT. Her research interests include population health and health equity, data science, predictive models to support public health planning, knowledge translation and evaluation, and population health management. She has authored over 230 peer-reviewed publications in the areas of epidemiology, population health and health services research. She has been awarded several national grants, including a CIHR Foundation grant to support her population health analytics research program. Dr. Rosella was awarded the Brian MacMahon Early Career Epidemiology Award by the Society for Epidemiologic Research, was named one of Canada’s Top 40 Under 40 and was recently inducted into the Royal Society of Canada’s (RSC) College of New Scholars.
Presented as part of the Epidemiology Seminar Series
The Department of Epidemiology, Biostatistics and Occupational Health Seminar Series is a self-approved Group Learning Activity (Section 1) as defined by the maintenance of certification program of the Royal College of Physicians and Surgeons of Canada