In a recent SRI Seminar, Julia Haas explored a new conception of the human mind as fundamentally evaluative in nature. According to Haas, a senior research scientist in the Ethics Research Team at DeepMind, this insight could assist in designing expanded forms of artificial intelligence that incorporate moral questions.

Amidst the challenges of COVID-19, SRI’s inaugural cohort of Faculty Fellows (2020–2021) engaged important questions at the intersection of technology and society through research, output, and connection with the SRI community, developing new approaches towards the study of environmental justice, data privacy, democratic engagement, and learning.

SRI Faculty Affiliate Karina Vold explores the intersections between philosophy and artificial intelligence, the relationship between humans and their tools, and the social and ethical implications of new technologies like GPT-3. As her research shows, technology has a lot to teach us about what it means to be human, and making sense of new tools sometimes requires—and creates—new concepts and ideas.

The practice of sortition, in which random selection is used to generate citizens’ assemblies, is a method of political representation as old as democracy itself. In a recent SRI Seminar, Harvard professor Ariel Procaccia discussed how better algorithms can ensure this process accurately represents population demographics. SRI Graduate Fellow Lillio Mok reflects here on the implications of Procaccia’s research.

The 2022 Schwartz Reisman Graduate Workshop invites graduate and early career scholars to present their work at a one-day, virtual event on June 20th, as part of Absolutely Interdisciplinary 2022. Organized by SRI’s Graduate Fellows, this year’s workshop centers on the theme of trust, broadly defined, and its relationship to technology and society.

In the Schwartz Reisman Institute’s inaugural Kitchen Table event, Research Lead Wendy Wong and Faculty Fellow Anna Su hosted a wide-ranging discussion on the implications of human rights for data ownership and privacy, and how we can address the challenges of writing new rules for an increasingly digital world.

In a recent SRI Seminar, Faculty Fellow Syed Ishtiaque Ahmed demonstrated how the dominant model of AI ethics is insufficient to strengthen the voices of local communities in the Global South. Ahmed contends scholars should move away from “universal” notions of intelligence, and foster situated ethical practices that take into account local hopes, faith, and stories.

SRI Faculty Affiliate Shion Guha joined U of T’s Faculty of Information in 2021 to help develop its new program in human-centered data science, a nascent field that he has co-authored a new textbook about. In this interview, Guha reflects on the challenges of using algorithmic decision-making in public policy, and how to make better data-driven systems by incorporating human-centered design.

Are you a U of T researcher who is passionate about ensuring new technologies are effective, safe, ethical, and fair? The Schwartz Reisman Institute welcomes faculty and graduate fellowship applications from U of T researchers from all academic disciplines.

Where is technology leading us? When we speak about the future, what does it mean for our identity as individuals and as citizens of states? When we arrive home, what will it look like? Themes of identity, place, and mediation were explored at the Schwartz Reisman Institute’s graduate workshop “Views on Techno-Utopia” by presenters Rushay Naik and Lilith Acadia.

Machine learning (ML) is increasingly used for producing automated decisions throughout society. While ML offers the promise of scale and efficiency, it runs the risk of codifying biases—such as racism and sexism—in its decisions. As discussed in the Absolutely Interdisciplinary conference session “Fairness in Machine Learning,” understanding and mitigating this risk will require a team effort from scholars across many disciplines.

At the Schwartz Reisman Institute’s graduate workshop "Views on Techno-Utopia," presenters Jamie Duncan and Julian Posada discussed the disconnect between the complex circumstances in which the data used to train AI systems are sourced and the laws and regulations designed to protect people’s data rights.