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.

In a new paper published, SRI Faculty Affiliate Ashton Anderson uses machine learning to demonstrate the 2016 rise in online political polarization was driven by a growth in new, largely right-wing, users, rather than the radicalization of existing users. Anderson’s data challenges the theory that online echo chambers are a primary cause of polarization.

Absolutely Interdisciplinary 2021 brought together over 270 participants from around the world, to explore the theme of “Human and Machine Normativity: New Connections.” The conference brought together researchers working on similar questions from a variety of disciplines in order to map out new terrain for thinking about human and machine normativity.

Hailing from a wide variety of disciplines, our graduate fellows represent the best and brightest U of T student researchers working on topics at the intersection of technology and society. The fellows will serve a one-year term at the Schwartz Reisman Institute.

Rosalie Wang, Syed Ishtiaque Ahmed, Jason Plaks, and Anna Su join the Schwartz Reisman Institute to expand research on AI-enabled assistive and rehabilitation technologies, moral psychology and human-computer interaction, data practices in the Global South, and international human rights.

SRI Research Leads Lisa Austin and David Lie are part of a multidisciplinary team behind a new global study that explores the privacy expectations and behaviour of smartphone users.

SRI Research Lead Wendy H. Wong examines the issues at stake around facial-recognition technology, and their impacts on human rights and consent. Wong argues data alters basic conceptions of autonomy and dignity in ways that “profoundly change human experience”—leading to a need to reconsider the framework of human rights for the digital era.

How are algorithms influencing the production and consumption of culture? A new white paper on AI, music recommendation, and cultural consumption released by the Schwartz Reisman Institute argues their impacts are profound and far-reaching.

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 spanning the sciences, social sciences, and humanities.

In the second of two posts, Leslie Regan Shade, Monica Jean Henderson, and Katie Mackinnon explore research on children’s and youth’s experiences of online spaces, their needs for privacy protection, and how conceptions of digital tools and the corporations that make them can be better informed through digital literacy.