Submission to Canadian Government Consultation on a Modern Copyright Framework for AI and the Internet of Things

6 Pages Posted: 2 Nov 2021

See all articles by Sean Flynn

Sean Flynn

American University - Washington College of Law; Program on Information Justice and Intellectual Property

Lucie Guibault

Schulich School of Law

Christian Handke

Erasmus University Rotterdam (EUR) - Faculty of History and Arts

Joan-Josep Vallbé

Department of Political Science, University of Barcelona

Michael Palmedo

American University - Program on Information Justice and Intellectual Property; American University

Carys J. Craig

Osgoode Hall Law School, York University, Toronto

Michael A. Geist

University of Ottawa - Common Law Section

João Pedro Quintais

University of Amsterdam - Institute for Information Law (IViR)

Date Written: September 17, 2021

Abstract

We are grateful for the opportunity to participate in the Canadian Government’s consultation on a modern copyright framework for AI and the Internet of Things. Below, we present some of our research findings relating to the importance of flexibility in copyright law to permit text and data mining (“TDM”). As the consultation paper recognizes, TDM is a critical element of artificial intelligence. Our research supports the adoption of a specific exception for uses of works in TDM to supplement Canada’s existing general fair dealing exception.

Empirical research shows that more publication of citable research takes place in countries with “open” research exceptions -- that is, research exceptions that are open to all uses (e.g. reproduction and communication), to all works, and to all users. Empirical research also shows that text and data mining research is promoted through exceptions that more specifically authorize text and data mining research. While these studies are preliminary and we are still improving on them, they provide evidence that supports the approach of combining a general research exception with a more specific data mining exception.

Keywords: Copyright, Intellectual Property, Law, Artificial Intelligence, AI, TDM

Suggested Citation

Flynn, Sean and Guibault, L. and Handke, Christian and Vallbé, Joan-Josep and Palmedo, Michael and Craig, Carys J. and Geist, Michael A. and Quintais, João Pedro, Submission to Canadian Government Consultation on a Modern Copyright Framework for AI and the Internet of Things (September 17, 2021). Available at SSRN: https://ssrn.com/abstract=3952238 or http://dx.doi.org/10.2139/ssrn.3952238

Sean Flynn

American University - Washington College of Law ( email )

4300 Nebraska Avenue, NW
Washington, DC 20016
United States

Program on Information Justice and Intellectual Property

4300 Nebraska Avenue N.W.
Washington, DC 20016
United States

L. Guibault

Schulich School of Law ( email )

6061 University Avenue
6061 University Ave
Halifax, Nova Scotia B3H 4H9
Canada

Christian Handke

Erasmus University Rotterdam (EUR) - Faculty of History and Arts ( email )

P.O. Box 1738
Rotterdam NL-3000 DR
Netherlands

HOME PAGE: http://www.eshcc.eur.nl/handke/

Joan-Josep Vallbé

Department of Political Science, University of Barcelona ( email )

Diagonal 684
Faculty of Law
Barcelona, Barcelona 08015
Spain

Michael Palmedo (Contact Author)

American University - Program on Information Justice and Intellectual Property ( email )

4801 Massachusetts Avenue N.W.
Washington, DC 20016
United States

American University ( email )

4400 Massachusetts Ave, NW
Washington, DC 20016
United States

Carys J. Craig

Osgoode Hall Law School, York University, Toronto ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada
416 736 5189 (Phone)
416 736 5736 (Fax)

HOME PAGE: http://www.osgoode.yorku.ca

Michael A. Geist

University of Ottawa - Common Law Section ( email )

57 Louis Pasteur Street
Ottawa, K1N 6N5
Canada
613-562-5800 x3319 (Phone)
613-562-5124 (Fax)

João Pedro Quintais

University of Amsterdam - Institute for Information Law (IViR) ( email )

Rokin 84
Amsterdam, 1012 KX
Netherlands

HOME PAGE: http://https://www.ivir.nl/profile/quintais/

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