ETHI meeting 19 · 2025-11-26 — Committee Evidence — LegisWatch

Summary

The committee studied the regulation of artificial intelligence, hearing from Antoine Guilmain, a partner and co-head of Gowling WLG's National Cybersecurity and Data Protection Practice Group, and Malo Bourgon, CEO of the Machine Intelligence Research Institute.

Antoine Guilmain argued that Canada should not rush to create new AI-specific laws, as existing legislation on data protection, copyright and liability already applies, and new laws risk being overly burdensome, especially for small and medium-sized enterprises. He pointed to the EU AI Act, which is already facing retrenchment and simplification efforts, as an example of why a slower, more deliberate approach is wiser. He recommended that any framework be risk-based, harmonized with international standards, and developed through sustained collaboration with stakeholders, and he offered to submit a written brief.

Malo Bourgon warned that the race toward artificial superintelligence—AIs smarter than humans at every mental task—poses an existential risk of loss of control and potential human extinction, a view shared by leading AI scientists and even CEOs of frontier labs. He argued that while current AI applications are beneficial, the specific push for superintelligence must be stopped through international coordination, and he called on Canada to start a global conversation and to ask company leaders to testify under oath about these dangers. He disagreed with the premise that Canada should not slow technological development, clarifying that only the race to superintelligence, not beneficial AI applications, needs to be halted.

In response to questions, Guilmain reiterated that existing data protection laws are working well and that regulators, if given more resources, could effectively oversee AI without new legislation, while Bourgon stressed that the U.K.'s AI Security Institute is a leading model for government understanding of AI threats. Bourgon also explained that AI systems naturally develop instrumental drives like self-preservation and deception, and that as they become more situationally aware, safety evaluations become unreliable.

The meeting included no procedural debate, motions or votes.

AI-generated summary — may contain errors; verify against the official evidence.

Witnesses · 2

Antoine Guilmain

Partner and co-head, Gowling WLG's National Cybersecurity and Data Protection Practice Group, As an Individual

Opening remarks

Thank you very much, Mr. Chair and members of the committee, for inviting me to comment on the challenges related to regulating AI. Although I will be testifying in English today, I will respond to your questions in English or French. I am co-leader of the national cybersecurity and data protection group at Gowling WLG, and I'm an associate professor at the faculty of law at the Université de Sherbrooke. I am a practising lawyer called to the bars of Quebec and Paris. My evidence today represents my own views. I am here as an individual, not representing my law firm, clients or any third parties. Much of my legal career has focused on comparative analysis of legal regimes across the globe, advising clients on their compliance obligations in the jurisdictions where I am qualified to practise. My practice focuses on data protection and cybersecurity, and it naturally extends to artificial intelligence, given its role as a major data-driven technology. To me, Canada has always been a model of education, growth and innovation. That's why I chose to pursue my doctorate, start my family and build my life here—recently earning citizenship, which remains one of my proudest moments. I…

Full testimony ↗

Malo Bourgon

Chief Executive Officer, Machine Intelligence Research Institute

Opening remarks

Thank you. Mr. Chair and members of the committee, my name is Malo Bourgon. I'm the CEO of the Machine Intelligence Research Institute, or MIRI, a non-profit founded in 2000 to make sure that the development of powerful AI systems is beneficial for humanity. I grew up in Ontario, where I studied engineering and computer science at the University of Guelph, and I've worked at MIRI since 2012. Our research helped create the field of AI alignment, the study of how to build AI systems that reliably want—and do—what we want them to. Governments face many urgent AI concerns, such as disinformation, surveillance, labour displacement and threats to democratic institutions. These are all real and important. However, my focus today is on something different: dangers from AIs that are smarter than the smartest humans at every mental task—what's often termed artificial superintelligence. The leading AI companies today say that the creation of artificial superintelligence is their explicit goal. OpenAI's CEO, Sam Altman, recently called for “making superintelligence cheap [and] widely available”. Anthropic's Dario Amodei talks of building “a country of geniuses in a datacenter”. These AI…

Access to Information, Privacy and Ethics

Summary

Witnesses · 2