Research
Integrating research across traditional boundaries to deepen our knowledge of technologies, societies, and what it means to be human.
Research Overview
Our Research Stream examines and re-conceptualizes common notions of the ways technology, systems, and society interact.
Comprising diverse areas of inquiry, from machine learning, computer engineering, epistemology, systems theory, and ethics to legal design, systems of governance, and human rights, our research agenda crosses traditional boundaries and is fundamentally inspired by a commitment to reinventing from the ground up.
We seek to increase the range and depth of interdisciplinary research in the AI and society ecosystem at the University of Toronto and beyond through ongoing initiatives such as our cross-disciplinary seminars, discussion groups, conferences, and workshops. We are connecting scholars across disciplines to foster new research programs, and connecting cross-disciplinary research teams to grants and philanthropy.
We are also fostering and advancing new fields of research in the sciences, social sciences, and humanities to deepen our understanding of powerful technologies and human relationships to technology. This includes identifying and developing novel, promising lines of research, promoting collaborations, funding, publications, seminars, conferences, and workshops that advance these lines of research, and helping to grow a community of diverse, globally-engaged scholars at U of T and beyond.
Our cross-disciplinary work seeks to contribute to new forms of regulation and governance around AI and powerful new technologies by integrating technical solutions with legal and regulatory frameworks. Our focus is to develop democratic, agile, and efficient governance that works at a global scale, addresses growing public/private power gaps, and aligns technology with human flourishing, agency, and values.
Gillian Hadfield is focused on innovative legal design and regulatory innovation for artificial intelligence systems, and how to better align AI systems with human values.
Sheila McIlraith is exploring how to build AI systems that are safe, and co-leads the Embedded Ethics Initiative, integrating ethics into computer science courses.
Karina Vold is exploring the social and ethical impacts of AI and what technology can teach us about being human.
Lisa Austin and David Lie are researching how digital tools impact transparency, security, and privacy.
Our research is informed by four “conversations”:
01
The Information Order
Exploring the norms, rules, and dynamics that govern how information is generated, transmitted, shared, and used, including concepts such as privacy, consent, ownership, and governance of data. Who knows what and why? Where can information go? What can people and entities do with the information they acquire?
02
Human Values
Connecting humanists, social scientists, and computer scientists to create shared and actionable frameworks for understanding human norms and values and the systems that generate them. What is “ethical” AI? What does it mean for machine learning to be “fair”? How will we judge causation and responsibility in human-plus machine systems with complex emergent behaviour? What is required for a computer system to be accountable or trustworthy?
03
Value Alignment
Developing the technical, market, and governance systems that can help ensure that our technologies produce outcomes that are reliably aligned with what humans value, both individually and through the various means (such as democracies) by which human communities determine which goals and values to pursue.
04
The Meaning of Technology
Looking beyond the immediate effects of technology to examine the ways that new technology transforms our social and societal structures, and asking how these technologies can serve, interact with, and shape the human agenda. How does technology transform the ways we understand ourselves and interact with each other? Who controls technology and who is controlled by it?
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