AI Data Conference Proceedings


Pina D'Agostino, Associate Professor, Osgoode Hall Law School; Founder & Director, IP Osgoode

AI Data Opening Remarks Transcript


Why is Data so Important to the Development of AI?

What is data and why is big-data essential for the development of artificial intelligence and machine learning? Looking through the lenses of industry, legal practitioners and leaders in the scholarly community, this panel will set the stage for the sessions that follow by diving into the legal and technical aspects of Data & AI.

Pina D’Agostino, Associate Professor, Osgoode Hall Law School; Founder & Director, IP Osgoode

Jonathan Penney Assistant Professor of Law; Director, Law & Technology Institute, Schulich School of Law, Dalhousie University
Carole Piovesan Partner & Co-Founder, Intell Data Law

Panel 1 - Why is Data Transcript


Intellectual Property at a Crossroad

With advancements in technology – especially within the field of artificial intelligence – intellectual property is at a crossroad. This panel considers how anticipated changes will impact patent and copyright laws in Canada, focusing on both practical and theoretical implications. Panelists will also explore whether intellectual property laws should offer protection to artificial intelligence works and inventions.

David Vaver Professor of IP Law, Osgoode Hall Law School

Dave Green Assistant General Counsel, IP Law & Policy, Microsoft
Catherine Lacavera Director of Intellectual Property, Litigation and Employment, Google Inc.
Maya Medeiros Partner, Norton Rose Fulbright Canada LLP
Shlomit Yanisky-Ravid Faculty Member and Lecturer, ONO Academic Law School and Fordham Law School

Panel 2 - IP at a Crossroad Transcript


Resolving Data Barriers

Many AI tools require access to an enormous amount of data in order to facilitate their development. That being said, the mere availability of data is not enough - good data is needed! Incomplete or biased data can exacerbate problems. Good data, however, might be subject to copyright, which may prove problematic: where an AI’s input infringes copyright, the output may follow suit. This panel will address the ways copyright laws might adapt in order to accommodate the needs of AI and discuss legal alternatives and exceptions, including fair dealing, sui generis AI legislation or carving out specific exceptions for data mining/AI training.

Aviv Gaon Adjunct Professor, IDC Herzliya

Paul Gagnon Legal Counsel, Element AI
Dave Green Assistant General Counsel, IP Law & Policy, Microsoft
Momin Malik Data Science Postdoctoral Fellow, Berkman Klein Center for Internet & Society at Harvard University

Panel 3 - Resolving Data Barriers Transcript


Luncheon Keynote
“Affective Artificial Intelligence & Law: Opportunities, Applications, and Challenges”

Kang Lee Professor, and Tier 1 CRC Chair in developmental neuroscience, University of Toronto

AI Data Luncheon Keynote Transcript


Big Data, Health & Science

Governments, researchers, care providers and private industry all recognize the incredible potential big data has to help advance scientific knowledge and improve both healthcare service deliver and patient outcomes. Using big data in health and science can be a real challenge however. What data can we collect, who can we collect it from, and how can we understand and use it?

Terry Sachlos Assistant Professor, Department of Mechanical Engineering and the Associate Director of the Bergeron Entrepreneurs of Science and Technology (BEST) Initiative, Lassonde School of Engineering

Pina D’Agostino Associate Professor, Osgoode Hall Law School; Founder & Director, IP Osgoode
James Elder Professor, Lassonde School of Engineering; York Research Chair in Human and Computer Vision, York University
Victor Garcia Managing Director & CEO, ABCLive Corporation
Ian Stedman Fellow in AI Law & Ethics at SickKids' Centre for Computational Medicine

Panel 4 - Big Data, Health and Science Transcript


What Makes a Smart City?

Sidewalk Toronto challenges us to consider what the role of government is in deciding how private sector actors can collect data in public spaces. What is the right way to balance concerns about consent and privacy against the broader interest in supporting innovation?

Pamela Robinson Associate Dean, Graduate Studies and Strategic Initiatives, Faculty of Community Services, and Associate Professor, School of Urban and Regional Planning, Ryerson University

The Honourable Jeff Lehman Mayor, City of Barrie
Neetika Sathe Vice President, Advanced Planning, Alectra Inc.
Natasha Tusikov Assistant Professor, Dept. Social Science, York University; The City Institute at York University
John Weigelt National Technology Officer, Microsoft Canada Inc.

Panel 5 - What Makes a Smart City Transcript