Symposium | AI in the City : Building Civic Engagement and Public Trust

How can we, as members of academia and civil society, make a difference in the way artificial intelligence (AI) is being procured, deployed, and used? Can trustworthy technology be created when there is no institutional trust?
CIRM’s AI in the City: Building Civic Engagement and Public Trust Symposium will be a day of discussions on what civic engagement and public trust in the era of artificial intelligence (AI) can look like in cities. It will be an opportunity to consolidate a network of multidisciplinary scholars, activists, and practitioners involved in a diverse range of initiatives, from research to advocacy, and map strategies to take this agenda forward. Bringing in local, national and global discourses, this symposium will explore questions related to trustworthy technology, participation in AI, digital rights, data ethics, algorithmic impact assessments, and tech policy in urban spaces.
Organized and moderated by:
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Ana Brandusescu – PhD Student, McGill University; 2019-2021 McConnell Professor of Practice, CIRM
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Jess Reia – Assistant Professor, School of Data Science, University of Virginia; 2020-2021 BMO Fellow, CIRM
Panel 1: Public trust and AI
09:30 - 10:45 AM
Panelists:
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Bianca Wylie – Tech Reset Canada; Digital Public
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Chenai Chair – Mozilla Foundation; My Data Rights (Africa)
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Miko Cañares - StepUp Consultants
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Nanjira Sambuli – Carnegie Endowment for International Peace
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Renata Ávila – Open Knowledge Foundation
Panel 2: Meaningful civic engagement with data and AI
1:00 – 2:45 PM
Panelists:
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Caroline Running Wolf – UBC; Indigenous Protocol & AI Working Group
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J. Carlos Lara - Derechos Digitales
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Mich Spieler - @MichSpieler on Twitter
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Renée Cummings – University of Virginia
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Renée Sieber – McGill University
Where: Zoom
When: February 10
This event will be held in English. Registration is required to access the login links.
REGISTRATION
Meaningful Civic Engagement with Data and AI
This event has been made possible thanks to the funding of the McConnell Foundation, BMO and the Andrew W. Mellon Foundation, as well as through the institutional support of the Centre for Interdisciplinary Research on Montréal (CIRM) and the University of Virginia’s School of Data Science.