The Schwartz Reisman Institute’s 2021–23 faculty fellows explored the social implications of new technologies, foregrounding the significance of ethics, equity, and human-centred values. Learn more about their research projects and how to apply for Schwartz Reisman fellowships.

U of T University Professor emeritus and “godfather of AI” Geoffrey Hinton delivered a lecture at Convocation Hall discussing whether large language models understand what they are doing and the existential risks posed by unfettered development of the technology he helped create.

Seven new senior fellows, including SRI Director Gillian Hadfield, have been selected by Schmidt Futures to solve hard problems in artificial intelligence through multidisciplinary research, with up to USD $7 million in support.

In We, The Data, Wendy H. Wong argues that we need to reboot human rights to match the pressures of our data-intensive world. Exploring surveillance, facial recognition technologies, data rights, and more, Wong makes a compelling case for why the public needs to engage Big Tech as data stakeholders.

Luke Stark, an assistant professor at Western University, has been appointed as the inaugural Schwartz Reisman Scholar-in-Residence. Stark’s work interrogates the historical, social, and ethical impacts of computing and artificial intelligence technologies, particularly those mediating social and emotional expression.

A new AI-powered solutions network for predicting and preventing diabetes developed by SRI researchers Laura Rosella, Jennifer Gibson, and Shion Guha has received $900K in funding from CIFAR’s AI for Health Solution Networks grant program.

Like an ouroboros—or snake eating its own tail—future AI models trained on the internet, where AI-generated content is expected to become ubiquitous, could end up devouring the problematic work of their predecessors.

The next generation of state-of-the-art foundation models could have capabilities that severely threaten public safety and global security. In a new multi-author white paper, the authors discuss the challenges of regulating frontier AI models, explore the building blocks of a potential regulatory regime, and suggest some minimum safety standards.

A new paper by Aparna Balagopalan, David Madras, David H. Yang, Dylan Hadfield-Menell, Gillian Hadfield, and Marzyeh Ghassemi describes how decisions made by machine learning models can be improved by labelling data that explicitly reflects value judgments.

In a recent article in PLOS Digital Health, SRI Graduate Affiliate Vinyas Harish explores how cross-sector partnerships can enable new technologies for more effective healthcare during emergencies, and the importance of robust governance frameworks.

Can government regulation benefit cybersecurity in the private sector? What requirements are needed to better assess threats and reduce vulnerability for Canadians? To answer these questions, SRI Research Lead David Lie led a panel discussion on the future of cybersecurity regulation.

In his new book Power and Prediction: The Disruptive Economics of Artificial Intelligence, SRI Research Lead Avi Goldfarb makes a compelling case for how AI innovation will evolve, and why it will require systems-level changes to the ways public and private sector organizations make decisions.