Скачать или смотреть The Disruptive Economics of AI in Healthcare | Dr. Avi Goldfarb

Title: The Disruptive Economics of AI in Healthcare
Speaker: Professor Avi Goldfarb
Series: Professor Robert Hill Memorial Lectureship – hosted by UBC’s Division of Developmental Pediatrics and Sunny Hill Health Centre at BC Children’s Hospital.

Learning objectives:
1) Be able to cut through the AI hype in medicine to understand what is possible and what remains science fiction.’
2) Understand the key skills we humans need in order to work well with AI
3) Recognize that AI adoption in healthcare is most effective when it is combined with a change in workflow.
4) Identify opportunities for AI within BC Children’s Hospital

About the speaker:
Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare, and Professor of Marketing, at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, a Research Associate at the National Bureau of Economic Research, a Distinguished Fellow at the School of Business Administration at The Hebrew University of Jerusalem, and a research lead at the Acceleration Consortium. A former Senior Editor at Marketing Science, his research focuses on the economics of digital technology and artificial intelligence. He has published academic articles in marketing, computing, law, management, medicine, physics, political science, public health, statistics, and economics. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award, and he testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising, and before the Canadian House of Commons on the AI and Data Act. A regular speaker at leading universities and companies around the world, his keynotes include the NATO Defense College’s 70th anniversary event, the Lancet Commission on Cancer and Health Systems, the IEEE Aerospace Conference, and the European Commission’s Workshop on the Economics of AI. Avi received his Ph.D. in economics from Northwestern University. He co-authored the bestselling books Prediction Machines and Power and Prediction, both on the economics of artificial intelligence.