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On March 23, 2026, IP Osgoode Director Professor Craig appeared before the . You can read her prepared remarks below or watch her testimony . A full transcript of the meeting, including the Q&A period, is available on .

"Thank you, Chair, and members of this committee. My name is Carys Craig. I am a professor at Osgoode Hall Law School, 91��ɫ, where my research focuses on copyright, technology, and the public interest. I submitted briefs to the Government’s previous consultations on AI and copyright, and I’ve published widely on the topic. I appreciate the opportunity to share my views today.

I want to make three points about copyright protection relevant to this Committee’s work. First, it is vital to distinguish copyright law from AI regulation; copyright is the wrong legal tool for regulating AI technologies. Second, relatedly, copyright law must not obstruct AI research, development, and training in Canada. And third, Canada’s copyright law must continue to refuse copyright protection to AI-generated works.

Copyright Is the Wrong Tool for AI Regulation

There is understandable concern about generative AI —its effects on creative workers, cultural industries, information integrity, the concentration of foreign corporate power. I share those concerns. But I urge the committee to be cautious about including expanded copyright protections as part of an AI regulatory package to address them. Copyright exists to encourage the creation and dissemination of works, to reward authors and foster a vibrant public domain. It is technology neutral. It is not designed to govern technology risks or restrain technological developments; it should not be pressed into that service now.

The real risks of AI — from bias and misinformation to deepfakes and privacy violations, labour displacement, corporate consolidation — demand dedicated, fit-for-purpose regulatory responses. Expanding copyright control risks distorting copyright principles while failing to address—or indeed worsening—the harms themselves. This is what I’ve called running into the “AI-Copyright Trap”—mistakenly turning to copyright as an easy catch-all (or for some, a windfall) in response to the threats posed by generative AI.

Copyright Law Must Not Obstruct AI Training

My second point concerns AI training. Some have called for mandatory licensing for copyrighted works used in training data, backstopped by owners’ rights to opt out or in. I understand the impulse, but the consequences of this approach would be deeply harmful.

Under current law, it is not established and far from clear that training AI on copyright works even implicates the rights of owners. When an AI system is trained, it does not memorize or reproduce the works it processes. It translates expressive content into statistical patterns — meaning becomes math. This is a technical, intermediate, non-public use to extract information that copyright does not protect. But even if copyright extended to this data extraction process, most text and data mining is likely lawful without permission or license under Canada's fair dealing provisions, as interpreted by the Supreme Court. If the Committee is interested in supporting AI research and innovation in Canada, the real problem is the current legal uncertainty, not illegality.

Requiring licensing would create a pay-to-play system regulated by private actors. Only the wealthiest corporations could afford access to the vast data troves required. Academic researchers, non-profits, startups and SMEs will be shut out. This would concentrate AI development further in the hands of Big Tech — the very outcome many are trying to prevent. It would also incentivize secrecy, reduce the diversity of AI systems and competition, exacerbate bias, and be practically impossible to administer effectively (as implementation efforts in the EU reveal). It would surely off-shore AI development while Canadian creators would gain little if anything. [Canada’s focus should be on public data governance, not shoring up its private commodification.]

So, if Canada is to amend the Copyright Act, it should be to confirm that text and data mining for informational analysis does not constitute infringement. This was the original INDU recommendation in the 2019 Copyright Act Review, and it remains the best way to support a healthy AI ecosystem in Canada. It would align with emerging US fair use jurisprudence—but give us the significant advantage of legal clarity.

Refuse Copyright Protection for AI-Generated Outputs

My third and final point concerns AI outputs. The most effective thing copyright can do to protect human creators is to maintain the position that copyright requires a human author — [a work must originate from a human being to attract protection] while AI-generated content belongs in the public domain. That is the correct result, and it protects the role of human creators in the creative industries. Granting copyright or new rights in AI-outputs would be an unnecessary, misplaced incentive and further chill human creativity.

Conclusion

In closing, I want to emphasize that copyright law, at its best, serves human creativity and the public interest. It exists because we value what human beings create, share, and learn from each other. We cannot allow it to become a tool for controlling technology, or a bargaining chip for corporate licensing deals and rent-seeking, or a vehicle for granting monopoly rights over information or machine-generated content. I urge the committee to keep copyright’s principled limits and practical effects in view — there are many more apt solutions to the risks posed by AI systems. Thank you."