SRI Faculty Affiliate and Fellow Nisarg Shah has been named one of 10 outstanding young scholars to watch in the field of artificial intelligence by IEEE Intelligent Systems. Situated at the intersection of AI and economics, Shah’s research on computational social choice examines the theoretical foundations of fairness in algorithmic decision-making.

As the first generation to grow up with the internet, millennials are more likely to be well-versed in digital technology. New research by Kristina McElheran shows that older workers who struggle with software may lose out when software investment in firms increases. Learn more about this detailed analysis of over a decade of U.S. Census Bureau data. 

Meet the Schwartz Reisman inaugural group of faculty and graduate fellows, whose areas of research and proposed projects vary widely in scope and subject matter but are united in their focus on ensuring powerful new technologies are effective, safe, ethical, and fair. SRI is pleased to support the innovative work conducted by these stellar U of T researchers across all three campuses.

Deborah Hellman, professor of law at the University of Virginia, spoke at the Schwartz Reisman Institute’s weekly seminar about the ways in which algorithmic decision-making can exacerbate the already-present possibility of “compounding injustice” and “accuracy-affecting injustice.” To capture our moral intuitions in cases like this, Hellman proposes the “Anti-Compounding Injustice Principle.”

SRI Director Gillian K. Hadfield will discuss her book Rules for a Flat World as part of Rotman’s Big Ideas series. The paperback edition includes a new prologue about artificial intelligence—its risks, benefits, evolution, and regulation. In this interview, Hadfield offers insights into how we might understand, govern, and build technology that is responsive to human values.

SRI faculty affiliate Marzyeh Ghassemi worries that explainable AI may make things worse rather than better. Her research suggests that explainable AI is perceived to be more trustworthy even when it is in fact less accurate. Learn more about Ghassemi’s research.

Human decision-makers who approve or deny refugee claims “are often unjustifiably certain in their beliefs,” says Avi Goldfarb. The economist and data scientist with specialization in AI and machine learning started to wonder: could ML’s ability to reduce uncertainty help reduce false refugee claim denials?

What is the alignment problem and how can we encourage the development of human-aligned AI? What is normativity and how do humans channel appropriate behaviour? If normativity is central to human intelligence, how can it apply to artificial intelligence as well?

The pace of change in cities—technological, social, economic—seems to speed up day by day, posing challenges to municipal government structures established in different times. More than 50 experts from academia, government, non-profits, and the private sector gathered for four working sessions to find solutions to crucial problems cropping up in city governance.

Eight world renowned scholars will form the core intellectual leadership of the Schwartz Reisman Institute. They will collaboratively develop an ambitious research agenda that spans research in artificial intelligence and computer science, the social sciences, and the humanities. Learn more about our inaugural research leadership team.