Artificial intelligence is embedded in the systems we use for our work, to access goods and services, to educate and entertain ourselves, to control our buildings and factories. But what are the implications to our world as AI algorithms are increasingly involved in decision making as opposed to human expertise and authority?
Enhance your digital literacy by joining computing science professors Eleni Stroulia and Nidhi Hegde, '95 BSc(Spec), for the next installment of the Science Connects Webinar Series where they discuss how AI is affecting our day-to-day existence. Learn how artificial intelligence generates, collects, and uses personal data to make decisions on your behalf in areas such as finance, justice, and access to resources. Find out what aspects of digital privacy to watch out for and what steps you can take to protect yourself.
Talk is suitable for general audiences, targeted at age 14+.
Date: Friday, April 23, 2021
Time: 12 to 1 p.m. MDT
Cost: Free
Eleni Stroulia is a professor in the Department of Computing Science and the director of the AI4Society Signature Research Area at the University of Alberta. Formerly, she held the NSERC/AITF Industrial Research Chair on Service Systems Management with IBM. Her research focuses on addressing industry-driven problems, adopting AI and machine-learning methods to improve or automate tasks. Stroulia’s flagship project in the area of healthcare is the Smart Condo in which she investigates the use of technology to support people with chronic conditions live independently longer and to educate health-science students to provide better care for these clients.
Nidhi Hegde, '95 BSc(Spec), is an associate professor in the Department of Computing Science at the University of Alberta. She is a fellow at the Alberta Machine Intelligence Institute and holds an artificial intelligence chair from the Canadian Institute for Advanced Research. Hegde’s current research goal is to investigate how outcomes from AI and machine learning methods breach privacy and impact fairness and bias, and to design algorithms that are private and fair by design. Before joining the U of A, she was a research team lead at Borealis AI (a research institute at Royal Bank of Canada) where her team worked on privacy-preserving methods for machine learning models and other applied problems.
