AI EDUCATION SYMPOSIUM
At Western University’s Faculty of Education: 1137 Western Road, London, Ontario, Canada, N6G 1G7
Join us for 3 AI keynotes & discussions:
- AI & Democracy – afternoon of Friday May 31
- 12:30 pm – 4:00 pm – Light Lunch provided
- Lunch & Talk in Community Room
- AI & Education – morning of Saturday June 1
- 8:30 am – 12:00 pm – Light Breakfast provided
- Breakfast & talk in Community Room
- AI & Indigenous Knowledge Systems – afternoon of Saturday June 1
- 12:30 pm – 4:00 pm – Light Lunch provided
- Lunch in Community Room; Talk in Wampum Learning Lodge
Registration & Accommodation
REGISTRATION
In-person or virtual (keynotes only) participation:
- No cost.
- In-person attendance is limited.
- Virtual participants (keynotes only) will receive links a few days prior to events. Links will also be posted on this page.
ACCOMMODATION
Ontario Hall Residence is adjacent to symposium venue + includes hot breakfast
- Reserve at: https://conference.has.uwo.ca/Register/default.aspx?code=C001822
- Daily cost = $85.50 or $65.50 (CDN)
BUILDING MAP
Parking
- Park where shown below (top-right of image)
- Enter building where shown below (“ENTER HERE”)
- Parking
- Parking is free on Saturday
- If you need a Parking Pass for Friday, please complete this form https://uwo.eu.qualtrics.com/jfe/form/SV_3jCmECpZUUIj1fo and a Parking Pass will be available for you at registration (outside of Community Room)
Sessions
- AI & Democracy – afternoon of Friday May 31
- Lunch (12:30 pm) & talk (1:00 pm) in Community Room
- AI & Education – morning of Saturday June 1
- Breakfast (8:30 am) & talk (9:00 am) in Community Room
- AI & Indigenous Knowledge Systems – afternoon of Saturday June 1
- Lunch (12:30 pm) in Community Room; Talk (1:00 pm) in Wampum Learning Lodge
Schedule
DAY 1: Friday May 31, 2024
AI & DEMOCRACY
- *** 12:30 pm – Light lunch provided***
- 1:00 pm – Sheila Jasanoff (+ response + Q&A)
- 2:30 pm – Discussion of issues and next steps
DAY 2: Saturday June 1, 2024
AI & Education
- ***8:30 am – Light breakfast provided***
- 9:00 am – Mark Daley (+ response + Q&A)
- 10:30 am – Discussion of issues and next steps
AI & INDIGENOUS KNOWLEDGE SYSTEMS
- *** 12:30 pm – Light lunch provided***
- 1:00 pm – Danica Pawlick-Potts: What Does Kinship Mean for AI? (+ response + Q&A)
- 2:30 pm – Discussion of issues and next steps
Keynote Speakers
SHEILA JASANOFF, Harvard Kennedy School
AI and Democracy
Sheila Jasanoff is Pforzheimer Professor of Science and Technology Studies at the Harvard Kennedy School. A pioneer in her field, she has authored more than 130 articles and chapters and is author or editor of more than 15 books, including The Fifth Branch, Science at the Bar, Designs on Nature, The Ethics of Invention, and Can Science Make Sense of Life? Her work explores the role of science and technology in the law, politics, and policy of modern democracies.
MARK DALEY, Western University
AI and Education
Mark Daley is the Chief AI Officer at Western University and a full professor in the Department of Computer Science with cross-appointments in five other departments, The Rotman Institute of Philosophy, and The Western Institute for Neuroscience. He is also a faculty affiliate of Toronto’s Vector Institute for Artificial Intelligence.
Mark has previously served as the Vice-President (Research) at the Canadian Institute for Advanced Research(CIFAR), and Chief Digital Information Officer, Special Advisor to the President, and Associate Vice-President (Research) at Western.
Mark is the past chair of Compute Ontario and serves on a number of other boards.
DANICA PAWLICK-POTTS, Western University
What Does Kinship Mean for AI?
Danica Pawlick-Potts is an Indigenous PhD Candidate and lecturer in the Faculty of Information and Media Studies at Western University. Danica’s research explores how Indigenous knowledge and protocols including Indigenous data sovereignty can guide and enhance ethical frameworks for the development of algorithmic systems and data infrastructures. If she had to sum up her research agenda into one question it would be: how can we all (including AI—looking at you ChatGPT) be good kin to Indigenous peoples in our data practices?