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2026 Annual Fall Lectures: Agency & AI — Lecture Three
The Rotman Institute of Philosophy is pleased to present the 2026 Annual Fall Lecture Series:
"Agency & AI"
What does human agency mean in a world where AI systems are becoming increasingly integrated into everyday life? Where does human agency begin and end? What are the risks and impacts of treating AI as agents? Can AI systems be designed to support and strengthen human agency and capacity-building rather than replace or diminish them?
This year's series brings together leading scholars and thinkers to explore these and related questions from a range of perspectives. Join us each Thursday in October for five engaging lectures examining one of the most important philosophical issues of our time.
As part of the Rotman Institute's commitment to public philosophy, each lecture will be hosted at a different venue across London. These community-based events are designed to bring together scholars, industry professionals, students, community organizations, and members of the public for thoughtful conversations that connect philosophical inquiry with contemporary challenges and everyday life.
Speaker: Aimee van Wynsberghe
Date: October 15th
Time: 7:00 - 8:30 pm
Location: Innovation Works, Community Room, 201 King Street
Title: Repairing AI for Environmental Justice
Abstract: Let us imagine that Artificial Intelligence (AI) is broken. Not in the physical sense in which pieces are falling apart and need to be put together; rather, in the metaphorical sense in which there are serious ethical concerns related to the design and development of AI that demand repair. In this talk I will outline a definition of Sustainable AI as an umbrella term to cover two branches with different aims and methods: AI for sustainability vs the sustainability of AI. I will show that AI for sustainability holds great promise but is lacking in one crucial aspect; it fails to account for the environmental impact from the development of AI. Alternatively, the environmental impact of AI training (and tuning) sits at the core of the sustainability of AI, for example measuring carbon emissions and electricity consumption, water and land usage, and regulating the mining of precious minerals. All of these environmental consequences fall on the shoulders of the most marginalized and vulnerable demographics across the globe (e.g. the slave like working conditions in the mining of minerals, the coastal communities susceptible to unpredictable weather conditions). By placing environmental consequences in the centre one is forced to recognize the environmental justice concerns underpinning all AI models. The question then becomes, how can the AI space be repaired to transform current structures and practices that systemically exacerbate environmental justice issues with the consequence of further marginalizing vulnerable groups.