SRSR Committee Meeting

     I call this meeting to order.

    Welcome to meeting number 25 of the Standing Committee on Science and Research. The committee is meeting today on the study of artificial intelligence.

    Before we start, the committee needs to adopt a new budget for our study on artificial intelligence, since we have two more meetings than we estimated in our previous budget. There is also a budget for our next study on governance and accountability of federal science policy and institutions. The clerk has sent you both draft budgets by email.

    Is it the will of the committee to adopt these budgets?

    Some hon. members: Agreed.

    The Chair: Thank you. Those two budgets are adopted.

    Before I get to our witnesses, I would like to make a few comments for the benefit of witnesses and members.

    Please wait until I recognize you by name before speaking. Those participating by video conference can click on the microphone icon to activate your mic. Those on Zoom can select the appropriate channel for interpretation at the bottom of your screen of floor, English or French. Please mute yourself when you're not speaking. I remind you that all comments should be addressed through the chair.

    With that, I would like to welcome the witnesses for our first panel.

    We are joined today in person by Mehmet Murat Kristal, a professor at the Schulich School of Business, York University. We are also joined, via video conference, by Dr. Taylor Owen, Beaverbrook chair in media, ethics and communications, and founding director of the Centre for Media, Technology and Democracy. From Ontario Tech University, we are joined, via video conference, by Dr. Steven Murphy, president and vice-chancellor. We are expecting Dr. Peter Lewis, Canada research chair in trustworthy artificial intelligence. He will join soon.

    All witnesses will have five minutes for their opening remarks, and then we will go into rounds of questioning by the members.

    We will start with Dr. Kristal.

    Please go ahead.

     Thank you.

    Chair, vice-chairs and members of the committee, thank you for the invitation to appear today.

    My remarks focus on one central message: Canada is not falling behind in artificial intelligence, research or talent, but we are at risk of falling behind in AI execution and productivity impact.

    Canada remains a global leader in foundational AI research, ethics and graduate-level talent. We produce world-class ideas, models and researchers. The gap is not in invention but in translation, turning research excellence into large-scale deployment, productivity gains and sustained economic impact.

     Over the next decade, countries that lead in AI will not be those that publish the most papers. They will be those that embed AI most effectively into the real economy, influencing finance, energy, health, logistics, public services and critical infrastructure.

    The single biggest obstacle to AI adoption in Canada is not technology; it is institutional capability. Canada produces excellent engineers and data scientists. What we lack at scale are AI-literate executives, AI-capable boards, and AI-trained regulators and senior public servants. Without this leadership layer, AI remains siloed, risk-averse and under-scaled, even when funding and technical talent are available.

     On employment, the core risk is not mass unemployment but uneven transition. AI primarily displaces tasks rather than entire occupations. The real risks are job polarization, widening productivity gaps across firms and sectors, and skill obsolescence, particularly among mid-career workers. The policy response should not be to slow AI adoption. It should be to align AI deployment with workforce transition, re-skilling and executive training so that productivity gains are broadly shared.

    With respect to regulation, Canada should focus on regulating AI systems and outcomes, not just models. Effective governance emphasizes explainability, bias monitoring, auditability, data governance and cyber-resilience. This approach allows innovation to continue, while ensuring accountability where real-world risk occurs.

    This leads to Canada's strategic opportunity. Canada does not need to out-scale the United States or China in AI platforms. Our opportunity is to outperform in trusted, regulated, large-scale AI deployment. Canada can lead globally in regulated and trustworthy AI, privacy-preserving AI, and AI deployment in finance, infrastructure and public systems. In these domains, institutional trust is not a constraint; it is a competitive advantage.

    From a federal policy perspective, three priorities matter the most: first, executive and public sector capability building, including AI literacy at the board, deputy minister and regulator levels; second, shared national data and AI infrastructure to move beyond fragmented pilots toward scalable platforms; and third, clear deployable standards for trustworthy AI so that organizations can operationalize, certify and scale AI responsibly.

     In closing, the biggest policy mistake Canada could make is treating AI as only an innovation issue rather than a national infrastructure issue. AI now underpins economic security, payment systems, energy grids, public services and cyber-resilience. Governing it accordingly through capability, coordination and accountability will shape Canada's productivity and competitiveness over the next decade.

    Thank you. I look forward to your questions.

     Thank you.

    We will now proceed to Dr. Owen. You will have five minutes for your opening remarks.

    Please go ahead. The floor is yours.

    Thank you, Chair and members of the committee, for this invitation to appear today. I was recently asked to contribute to the federal AI strategy task force on the theme of trust and safety. My remarks today draw on that submission, which is publicly available.

    I understand that this study is focused on AI research, on recent advances, on the needs of research institutions and on the role of the federal government in promoting a responsible AI research ecosystem. I want to address that final point directly because I personally think it's foundational to all the others.

    The government has made it clear that it wants Canadians to adopt AI. This is understandable. I increasingly believe that this technology is transformational and has the genuine potential to improve productivity, reshape public services and strengthen our economic competitiveness. To do this, Canada should certainly invest in AI research infrastructure, fund centres of excellence and recruit world-class talent, but investment alone is not a strategy for adoption. Creating the conditions under which those systems can be safely integrated into public life is equally essential. If the systems that emerge from the Canadian AI research and development are deployed without clear standards for safety, transparency and accountability, and if the public does not trust them as a result, then the entire enterprise is undermined. A responsible AI research ecosystem, then, requires a responsible AI governance ecosystem. The two can't be separated.

    Right now, that public confidence is simply not there. Only 34% of Canadians are willing to trust AI systems. Nearly 80% are concerned about negative outcomes on their lives, and 78% fear AI will undermine our elections. Seventy per cent are worried about their children's safety, and close to 80% believe AI threatens their jobs. However, 88% want stronger governance. This is not, then, a literacy gap. Canadians are making reasonable judgments. These systems were deployed without meaningful oversight, and they have seen and felt the consequences. This is a governance gap, and without closing it, neither the adoption the government seeks nor public confidence in AI research will materialize.

    My submission to the task force argues that closing this governance gap requires action on three fronts. I think of these as the democratic foundations of AI governance—really the bare minimum we need to do.

    The first is citizen safety. AI systems are being deployed at an unprecedented pace, often without meaningful risk assessments. We've seen chatbots fail users in mental health crises and children exposed to harmful content through many AI-powered products. Democratic governance requires independent regulatory authority with the power to mandate risk assessments before deployment and ensure heightened protections for children.

    The second is information integrity. AI now both curates and creates our information environment. Synthetic media is proliferating. Provenance is obscured, and citizens cannot distinguish meaningfully between authentic material and fabrication. Democratic governance requires mandatory AI labelling and provenance disclosure, at least for now, and data access frameworks that allow research to study these systems.

    The third is democratic legitimacy. Citizens must have meaningful agency over AI systems that affect their lives, recourse mechanisms when AI causes harm, data portability so that users are not locked into products, and structured public consultations so that governance is shaped by the people it affects.

    These principles can be translated—and I would suggest easily—into concrete policy. Canada does not need sweeping new AI legislation. Most of these measures can be implemented through two existing frameworks, an amended online harms act that brings AI chatbots into scope and an amended consumer privacy protection act with AI-specific transparency requirements. Both bills had cross-partisan support. Both could be revived quickly.

    I would also add that addressing this governance gap is itself a research challenge. Too often, AI funding is understood narrowly as investment in computer science and technical infrastructure, but understanding AI's effect on society and developing policy tools to address that require sustained investment in social science, humanities and interdisciplinary research. Canada has strengths in this area, but it remains significantly underfunded. If this committee is considering the needs of Canada's AI research ecosystem, I would urge you to think broadly about what that ecosystem must include.

     Governance is not a constraint on a responsible AI research ecosystem. It is a precondition for it.

     Thank you. I look forward to questions.

     Thank you, Dr. Owen.

    We will now go to Ontario Tech University. We are joined by Dr. Steven Murphy, president and vice-chancellor; and Dr. Peter Lewis, Canada research chair in trustworthy artificial intelligence.

     Dr. Murphy, you will have five minutes for your opening remarks. The floor is yours.

    Thank you, Madam Chair.

     It's good to be back today. I will be splitting my five minutes with Dr. Lewis.

     As we've heard this morning, from a policy perspective AI should always be thought of as a balancing act between innovation and governance—issues of privacy, data management and reducing algorithmic bias.

     The opportunity for Canada, I believe, lies in developing trustworthy, human-centred AI applications in areas that contribute the most to Canadian GDP. We've tended, to date, to centralize funding around clusters that build out large language models. I don't see this as a realistic niche that Canada can own, given the U.S. hyperscalers. I do see a rich potential in applications that engender trust and build the social licence for AI with the public.

     As we diversify our exports, we need to seize the opportunity to develop applications that balance innovation with responsibility in areas that Canada is known for, including, for example, energy, mining and advanced manufacturing, to name an obvious three. In so doing, we can enhance productivity and GDP while building applications that engender trust. This approach also ensures that we don't spread ourselves too thin or forget which industries drive our economy and our exports. It's not just the right thing to do; it's good business, and it fits the Canadian brand internationally. Just think of the global reputation of our banks as they came through the 2008 financial crisis.

     It's my privilege to now turn the floor over to our Canada research chair in trustworthy AI, Dr. Peter Lewis.

     Thank you, Dr. Murphy.

    Thank you, Mr. Chair.

     As Dr. Murphy said, I'm with the Canada research chair in trustworthy AI at Ontario Tech University, and director of our recently launched Mindful AI Research Institute, MAIRI.

     We championed, through MAIRI, a vision for a thoughtful, intentional and inclusive approach to AI research and innovation, bringing together more than 70 professors with expertise spanning the social and the technical, providing us with the ability to tackle pressing challenges around AI in a deeply interdisciplinary way.

     I'd like to express our thanks to the Canada research chair program, the tri-agency research program, the new frontiers in research fund and other federal research programs that have enabled us, for example, to do the research to inform the recently released new federal standard for accessible and inclusive AI—the first of its kind in the world. This standard ensures that the eight million Canadians living with disabilities will have barriers to using AI removed or reduced.

     These programs enable us to do the research needed to understand the trustworthiness of the AI systems being promoted and considered for use in courtrooms to analyze forensic evidence, ensuring that any use of AI enhances objectivity and justice and doesn't undermine or threaten them. They're also enabling us to develop a new generation of reflective AI systems with enhanced social intelligence and safety based on new architectures.

     I'd like to make three main points.

    The first is that, in Canada, I believe we should diversify our efforts. Today, AI is deeply sociotechnical, and research and innovation must reflect this. We need to hear from all sectors of Canadian society, ensure that we include diverse perspectives and lived experiences, and bring multiple disciplines to bear on developing our understanding of the trustworthiness of AI, its impact and how we develop it well.

     The days of AI research being mostly about machine learning are over. Canada's national strategy of focusing on three large machine-learning intensive institutes anchored in major urban centres worked well when the challenge was to get machine learning out of the lab and into businesses and people's lives. Now, as we move to the next phase, the challenge is a different, perhaps a more complex one that requires a new, more diversified approach.

    My second point is about regulation and values. How should Canada lead globally in AI? What should AI leadership look like? What is the distinguishing feature in the Canadian approach to AI? I would argue that AI leadership is about values. It's about showing how to do it in the right way—a way that respects dignity and inclusivity, and a way that promotes equity, sustainability and truth. It's not about speed.

     It is right to acknowledge the pressure to act quickly and to be agile and forward thinking, and we should acknowledge that the world looks to Canada to show how to do this with a values-first approach. Regulation is needed—and it's important—but it's also not enough.

     Finally, I would like us to consider what the post-LLM world looks like. There is a question being asked as to whether we should be investing in competing to build the biggest and best LLMs. The LLM boom may be completing its arc, but through history we see that AI development continues with a new architecture, building on what's gone before and opening up new paths and breakthroughs.

     How do we position ourselves well for the future? I would argue that, just as Canada did in the early stages of deep learning, without necessarily knowing that it would come to all this, we should be investing in the seeds of what's to come next and placing some bets.

     Thank you. I look forward to your questions.

     Thank you, Dr. Lewis and Dr. Murphy.

    We will proceed to our rounds of questions.

    Our first round of questioning will be for six minutes each. We will start with MP Baldinelli.

    Please go ahead. You have six minutes.

     Thank you, Madam Chair.

    Thank you to the witnesses for being with us this morning. I'm going to begin with Dr. Owen.

    Dr. Owen, on October 9, 2025, the Financial Post published an article titled “'Flawed and broken': Critics warn Ottawa's AI task force is too industry focused”, with critics saying that “the government's approach lacks inclusivity and transparency”.

     It's hard to imagine that 28 task force members are enough to cover everything and every aspect and angle there is to know about AI during what was considered a national sprint over 30 days to prepare recommendations to a government. Now that you've gone through the process—I've read the report you submitted—do you believe that other expert areas were adequately represented and/or missing from the task force?

     Yes, that's a good question.

    I think there is a wide range of ways to do these kinds of consultative policy processes. Frankly, this probably wouldn't be the way I would have designed one had I been in charge, but I wasn't.

    There are two things that need to be considered in these processes. First, what is the breadth of expertise and voices that are included? On this one, I think it's very clear, as that letter and many have pointed out—including many on the panel, frankly—that this certainly had a directional focus to it. There were not a large number of governance experts on it, for example, or privacy experts, or even civil society members representing those who are advocating for governance and privacy measures.

     I would suggest that even with regard to AI infrastructure, with regard to the power that would be required, not bringing forward—

    Agreed.

    —individuals such as the Canadian Nuclear Association, OPG or others to bring forward their concerns was a big miss by the government.

    I'm just taking this from your notes. You talked about how responsible AI needs a governance system, and you talked about a “governance gap” that requires action on three fronts: “citizen safety”, “information integrity” and “democratic legitimacy”. In your submission, you talk about how “trust must instead be built in the democratic infrastructure that governs AI.”

    Again, when you look at the concerns that were shared with regard to the task force being industry-heavy.... For example, there was a gentleman, Patrick Pichette, from Inovia Capital, who made a submission. He said Ottawa should declare Cohere, in which Inovia is a major investor, Canada's “national LLM champion, and fuel it with large-revenue contracts”, and that the Toronto-based AI firm should receive deals worth over $1 billion each for applications in the public service and defence.

    Right there, do you not believe that, as a task force report and recommendation, it's a conflict of interest? Are we not seeking input to develop a strategy as opposed to trying to recommend that one's own company receive contracts from the federal government?

     I can't speak for other members or for the intent of this task force.

    What I can say is that comment in my submission was referring to ongoing consultative deliberative mechanisms. As we head into a world where our lives and our democracy are fundamentally upended by a technology—which I believe is about to happen—it is incumbent on governments to meaningfully deliberate on how those technologies will be used and integrated into our society with those who will be affected, not just those building it.

     I don't think that, to date, the government has taken that seriously. I hope that part of a national AI strategy, which we may see soon, includes meaningful and required deliberative consultation as we move through this technological adoption together as a country.

    Again, in your comments, you said that AI investment alone is not a solution to adoption. In your report, you say, “AI systems are increasingly embedded in Canadians' daily lives, shaping what we see, the work we do, the decisions we make, and the services we access.”

    As part of that national sprint, is it almost too late from a regulatory standpoint to catch up and provide for that democratic or governance gap that needs to be filled? Can we still do it in time, or is it too late?

     It's a good question.

     I think this is an ongoing process. I don't think democratic consultation is a single moment. It needs to be embedded in our democratic process, which it is currently not sufficiently in my view. I wish we had started this five years ago, of course. It's not too late, though. These legislative measures—the ones I spelled out specifically in my contribution—could be done quickly and efficiently, and they would have a meaningful impact. Therefore, I would say yes to meaningful consultation beginning as soon as possible. I think the task force was a form of meaningful consultation; it just wasn't sufficient. There are all sorts of ways we need to do this.

     At the same time, we need to put in place the baseline legislative measures that will allow us to minimize what I think are the clear, current risks and harms of these technologies. Doing those two things together, to me, is a bare minimum for a national AI strategy that takes the democratic implications of these technologies seriously.

     Thank you.

    Thank you.

     We will now proceed to MP McKelvie.

    Please go ahead. The floor is yours.

     Thank you, Madam Chair.

     My first question is for Dr. Lewis.

     Dr. Lewis, your research is very much around trustworthiness in AI and its responsible use. Could you share with us what you think the federal government's top priority should be in shaping a responsible AI research ecosystem in Canada?

     Thank you very much for the question. I'll make two main points.

     First, I would reiterate a point we made. Dr. Owen spoke about the importance of broad-based consultation and meaningful, deliberative engagement, as part of the democratic process, with groups affected in different ways by the AI systems in their midst. Some of them have a lot of control over those and have decisions over how they can use them to, for example, enhance their businesses. Other people are much more in a position of being subject to the decisions of AI systems, and areas such as explainability, transparency, auditability and regulation become increasingly important. One priority, then, ought to be to meaningfully understand these impacts.

    I want to be clear that we really do not have a good handle in general, in terms of research, on the impact that AI is having at the moment. There is a lot of ad hoc evidence emerging. In terms of global or general patterns, this is still very much emerging, and we ought to acknowledge that in the way we do this.

     A second point is around the framing of how we think about trust in AI systems. If we're not careful, we can very easily slip into a position of trying to get people to trust AI so that adoption is achieved. This is thinking about it the wrong way around. Trust comes where trust is earned and where trust is warranted—at least it should do this, when we're doing things with the right intentions. Any strategy that is attempting to build and calibrate trust in the general population around AI really ought to acknowledge that people trust systems for different reasons. There are a lot of historical and systemic issues that play into those kinds of questions. There are power dynamics at play. It is not a simple question of how we “drive adoption” when we're thinking about trust.

     I'm happy to talk more about that, if that's interesting. I think there's some real nuance needed in that area.

     Thank you.

     My next question is for Dr. Murphy.

     Budget 2025 announced $1.7 billion to recruit top international researchers. I'm wondering what sorts of barriers or challenges you see to recruiting AI researchers in Canada. Do we need to do more around the recruitment front?

     Thank you for the question.

     I would first commend the government for those efforts. I think they have been very well received in our sector. They offer an immense possibility, especially in this day and age when we see many people who want to be Canadians or see Canadians who want to repatriate from the United States.

     In these areas, when we think about bringing in chairs, taking in the depth and breadth of AI research—so that we are talking about systems based around governance needs, trustworthiness needs, the social sciences and engineering and have the full gamut of people contributing to AI solutions—becomes critical. We can't myopically only hire systems engineers, as great as they are.

    By no means has that been any restriction. I would hope that, going forward, we continue to place value right across the academy in terms of people who can contribute to a technology that really has the potential to be the fourth industrial revolution and is already amongst us.

     Thank you.

    Dr. Lewis, I had the opportunity to meet with some of your students, who are doing really great projects. I'm wondering if you could speak to where they're going afterwards. How can we retain their IP and their brilliance here in Canada? What are we doing to retain that knowledge around artificial intelligence?

     I'm glad you were able to come and visit us in the lab and meet the students we have. I think you're right. There is such a wealth of expertise and real energy amongst the students and researchers being trained under such programs as the ones through NSERC and other funding agencies, including in labs like mine.

    In terms of how we retain, which perhaps I can broaden to how we attract, I really welcome some of the very recent changes around trying to ensure that HQP from overseas are able to come to Canada to engage in graduate study and post-doctoral research. I think this is essential. Anything that can be done to streamline and smooth those kinds of processes in terms of things like timelines is very welcome. It enables us to act in a much more agile way. I think that is crucial.

    In terms of attracting and keeping people afterwards, and where they go next, I think we've seen that things like visas that allow graduate student graduates to be able to stay in Canada, and perhaps stay even in the province they've moved to, are incredibly attractive and incredibly valuable in terms of enabling them to then stay and move into either further research jobs or into industry. We see examples of students who are very keen to move into those kinds of engineering jobs or indeed some of the more business-facing jobs around AI adoption and trustworthiness.

    Even more so nowadays, we're seeing people wanting to move into jobs as AI ethics officers, taking on regulatory roles and being part of that ecosystem—

    I'm sorry for interrupting, Dr. Lewis. The time is up for MP McKelvie. Thank you.

     We will now proceed to MP Blanchette-Joncas for six minutes.

    Please go ahead. The floor is yours.

    Thank you, Madam Chair.

    I'd like to welcome the witnesses who are with us for this important study.

    If I may, I'd be pleased to come back to the central topic of our study, artificial intelligence.

    My first question is for Mr. Lewis.

    If an artificial intelligence system were deployed in Canada and caused serious harm tomorrow morning, who would have the legal authority right now to stop it immediately, in your opinion?

     That's a very interesting question. I would defer to the lawyers. I'm not a lawyer. I would not be able to comment on legal accountability or responsibility for things like this. I think you were talking about the legal versus the practical ability to stop it.

    To your knowledge, is there currently a mechanism within the legal framework to possibly thwart a dangerous attack generated by artificial intelligence?

     I am not a lawyer. I would not like to comment on that.

    Is there a witness with us today who could help us answer that question?

    I see none, Madam Chair, so I'll move on to my next question.

    Mr. Owen, compared to the European Union or countries like the United States, does Canada suffer from an institutional deficit when it comes to independent oversight of artificial intelligence, in your opinion?

    Do we currently have a truly independent authority that makes it possible to regulate and observe whether there are problems, or are there only advisory mechanisms?

    Thank you for the question.

     There is not.

    I think there are various pathways to build one, and to legislate and empower one. One pathway was in the previous consumer protection privacy act, which built in an AI-focused, systemic risk assessment and a risk-based regulator. That was very similar to what the EU AI Act did: create one body to regulate a broad variety of AI capacities and products.

    I'm not sure that's where we're headed, or where many other countries are headed. It's certainly not where the U.S. is going. Instead, what I think we're likely to see are different regulatory and safety capacities—to your previous question—sitting in different types of regulatory bodies that are, in some way, more targeted at the types of AI they oversee and the sectors in which those exist.

    On the consumer safety side, regarding the ways citizens are using AI products in their daily lives, most of that is best done through an online harms regulatory structure, in my view. We already have that model, which has been widely consulted. I think it provides the right risk assessment and transparency obligations for social media platforms and could be applied to consumer-facing AI products.

    That is very different from the spirit of your initial question. I am also not a lawyer, so I don't know what legal emergency mechanisms may or may not exist. There may be some that I'm not aware of, but those would be for a very different set of risks versus what we would have through a consumer-facing risk and transparency mechanism like the online harms act. I think they need to be treated as fundamentally different, just like systemic risks to our health care system, for example, or to our financial system, both of which have existing regulatory authorities.

    If the ability to calculate critical infrastructure basic models is concentrated among a few companies, even foreign private companies, can we continue to say Canada has strategic autonomy?

     It depends on what we mean by “strategic autonomy”, and it depends on what we mean by “digital sovereignty”, which is an analogous frame that's getting used a lot now.

    Think about, for example, the information ecosystem, where most of my work is. The fact that our information ecosystem is now largely reliant on both a small number of U.S. platforms and a small number of U.S. large language models would certainly create difficulties if these were to be leveraged and used against us. Should we be developing more autonomy in both of those respects? Yes, we should be building Canadian systems, and there are many others who can speak better than I can about the infrastructure needed to do that. We also need the ability to govern the ones we use. Right now, we have neither. We have neither our own systems nor the levers through which we can govern the foreign products we use.

    I think that twin deficiency is a real vulnerability, as you point out.

    I just want to go back to something you mentioned.

    As far as you know, there's currently no mechanism to regulate artificial superintelligence. Specialized AI is different from artificial superintelligence.

    There's certainly no existing mechanism that makes this differentiation. Whether there are legal mechanisms to address some of the runaway harms you're alluding to, like superintelligence, I don't know. I suppose there are forms of emergency blocking that could occur, for example.

    Again, that's not my expertise.

     Thank you. You can talk about that in detail in the next round.

    This ends our first round of questioning. We will start our second round of questioning with MP Ho for five minutes.

     Please go ahead.

     Thank you, Madam Chair.

    My first set of questions will be for Professor Kristal.

    I'll say that it's a pleasure to have you here, as a fellow Schulich MBA grad.

    In late 2025, the Liberal government announced a $1.7-billion initiative to recruit up to 1,000 international researchers. That's roughly $1.7 million per researcher. At the same time, many experts, including you, argued that Canada's weakness is not in basic research. It's in scaling and commercialization.

    In your view, has the government misdiagnosed the problem altogether by pouring more money into producing research? Should they be focused on something else?

     As a researcher, I am always in favour of more research, so that is great. At the same time, it's not only researchers. We need to do more. That's the bottom line.

     Also, when you refer to $1.7 million per researcher for 1,000 researchers, over the lifetime of a researcher, unfortunately, that's not a lot of money. I would like to point out that, but as I indicated in my submission, it's more than just research. We need to bring AI to the organizations. Ninety-six per cent of the Canadian economy is based on small and medium-sized enterprises, and those enterprises need support because it's our overall competitiveness. How we do that, from my perspective, is the million-dollar question. It's research, but also more.

     You also mentioned jobs in AI. There are, depending on which report you look at, tens of thousands and potentially hundreds of thousands of jobs that could be lost in Canada due to artificial intelligence. We see multinational companies cutting tens of thousands of jobs because of AI alone.

    Do you think the government has a plan to deal with this transformation?

     I think upskilling is very important. There will be certain tasks that can be done faster by AI systems, which will reduce jobs, but the bottom line is this: In the way I see AI applications, it's not head count reduction. It is more about how we can allow individuals working in any kind of organization to do more meaningful and thoughtful work.

    Do you see any sort of plan? Is the government doing enough to do that upskilling? Are you comfortable that the upskilling is going to occur at a pace that would meet the number of jobs that are going to be lost due to AI?

     I would like to see more AI literacy. The application of AI in organizations is a real problem. The more we can train our society—the people who are working—the more competitive we will become.

     The government recently created an AI strategy task force, on which there appears to be limited representation from the energy and electricity sectors. These are the sectors that will help build our grid and handle all the AI demand we're going to see in the foreseeable future.

    Do you see that as an issue? Do you think that's a potential blind spot in the AI strategy?

    The AI strategy should encompass everybody, because it's not only the electricity grid or infrastructure providers. You have health care, legal and finance, and AI will touch upon all sorts of different things within our lives. The more you can have participation from different walks of life, the better it will be. Creating a coherent nationwide strategy means you need to get input from different parts of the country.

    I just have a little bit more time left.

    The government, in late 2025, discussed doing this AI sprint. Is the government sprinting fast enough, in your view, in its handling of AI?

     We could go faster, but we also need to be thoughtful, because any AI application has resource implications. You want to make sure that whatever you're spending money on...because there is legislation and there are strategies that you're going to build. Once you start implementing those, there is also a cost element to that. What we tell our students all the time is that when you're going to do an AI project, you need to have a clear understanding of your business goals and the ROI attached to it.

     Thank you. I'm sorry for interrupting, but the time is up for MP Ho.

    We will now proceed to MP Rana for five minutes.

    Please go ahead.

     Thank you, Chair.

    Thank you, witnesses, for being here with us.

    Dr. Kristal, I'm very glad to know that you are also a civil engineer. My question is for you.

    You are one of the founding program directors of both the master of business analytics and the master of management in artificial intelligence programs at the Schulich School of Business. I was hoping you could speak to how Canadian academics are responding to the recent surge in AI and whether they are facing barriers to conducting research and ultimately commercializing their research.

    What would help break down these barriers?

     In terms of research, we don't really foresee that many barriers. We have resources. For example, at York University, we got federal funding to create something called “Connected Minds”. That was an initiative between York University and Queen's University that brought together AI researchers, engineers and also social sciences, because there is a need to understand the impact of AI in the society at large. We are doing our best.

    In terms of training, though, we need to train more people. When I was creating the master of management in artificial intelligence, the LLMs were in their initial stage. They weren't as prevalent. We launched the program in 2019. Now everybody has a ChatGPT app on their phone. The game has changed considerably.

    What we are trying to do is teach the foundational AI knowledge and then, on top of it, there is also why we're implementing these technologies in any kind of organization. That understanding seems to be lacking among our students. We want to make the connection, so to speak, to how we can utilize these technologies to be more competitive on the world stage.

     Thank you.

    How are recent graduates connecting with their future employers? What's missing within this pipeline? What would keep graduates and researchers in Canada?

     That's a very good question.

    As in my opening statement, the employers—and I'm not talking about hyperscales; I'm talking about regular organizations and regular companies—are still having trouble understanding what AI can do for them. As a result, when you have this many organizations that don't understand what AI can do for them, it's harder for them to get in touch with students or hire students as interns so they can do projects in their organizations about AI, who then later on turn into full-time employees in those organizations.

    The real barrier that I see is in how we educate and train our executives so they can also understand what AI can do for their organizations. Once they get to that point, they are going to be drawn into the educational institutions and universities because that's where we actually train people who can do these things. The impediment is how aware our decision-makers are of AI capabilities.

    In your research on supply chains, what AI use cases are proving most valuable for Canadian firms? What steps does the government need to take to scale these successes?

     The biggest thing, especially in Canada, is about demand forecasting and logistics. That also ties into the last-mile logistics and reverse logistics. If you take out LLMs...because AI is not only a large language model. There are other applications of AI. They perform well in closed systems, but for those closed systems to work, you need to know what the outcome is.

    Forecasting is one of the trickiest parts where we would like to see improvements. That is going to impact your greenhouse gas emissions, your logistics, your pricing and your inventories. I think that is where the biggest growth can take place.

     For my last question, in terms of artificial intelligence, where does Canada shine?

     In terms of research, we do shine. I mean, I don't need to tell you—

     I'm sorry for interrupting. The time is up for MP Rana.

    We will now proceed to MP Blanchette-Joncas for two and a half minutes.

    Thank you, Madam Chair.

    Mr. Lewis, must any AI system used by the state be technically reversible and capable of being disabled without depending on an external supplier?

     That's a good question.

    I think that's a matter of policy and something that we ought to consult broadly on to understand. From the point of view of national security, we obviously need to have sufficient checks, balances and security valves, if you like, to be able to assert control. This is important.

    At the same time, we need to acknowledge that we live in a global information ecosystem. The Internet itself is something that we could argue is already essentially out of control in terms of how to control it, but we still live with that. What do we do in this situation? We put our best efforts in place to be able to protect vulnerable people and curate and protect the integrity of the information ecosystem. I would argue that we need a similar approach to AI.

    Thank you.

    My next question is for Dr. Kristal.

    In your opinion, is it generally more costly for a country to correct a technological dependency after it has been installed or to invest from the outset in robust institutional architecture?

     Could you please repeat the question?

    When it comes to regulating artificial intelligence, is it more costly for a country to correct a technological dependency after it has been put in place or to invest before putting it in place to ensure that it has robust institutional architecture?

     That's a very good question. Thank you very much for asking it. I was actually just reading an article about that.

     There is a difference between AI-first and AI-native. With AI-first, you're implementing technologies and then using whatever comes up first, but you're not changing your organizational structure to be AI-ready. On the other hand, there is this notion of AI-native. I would like to see our country be AI-native so that how we design our organizations and processes enables AI implementation.

     There is a difference between using the tools versus changing the way you look into how you operate organizations, and I would like us to become AI-native.

     Thank you.

    Madam Chair, I'd like a written response from the witness. I'd like to know if he can answer my questions about the cost. Would it be better to invest before or after? Is there a cost to that?

    If you would like to respond, please send it in writing. Thank you.

    We will end this panel with two minutes with MP Holman and then two minutes with MP McKelvie.

     MP Holman, you have two minutes. Please go ahead.

     Thank you, Madam Chair.

    Thank you to all of the witnesses for attending the committee today. This question is for Professor Kristal.

    Canada continues to provide world-class AI researchers, yet many leave for opportunities in other countries where compensation and compute access are significantly higher. How is the Canadian higher education system trying to prevent this talent loss?

     It's not an easy question to answer. Yes, you are competing against other institutions, and they provide more infrastructure and more opportunities and pay their researchers more. That's why I said I would like to see more investment in research. That's the reality.

     You're competing for talent, and there is not much of this talent. There is a limited amount of talent. You attract this talent by providing people with doctoral students, post-doc students and labs, and you need to pay them. All of these things are not easy to overcome. Our institutional structure is not the same as other countries', especially the United States'.

     Thank you for the answer.

    My second question—hopefully I can get this in during my time—is for Dr. Lewis, regarding the concerns about AI, privacy and civil liberties.

    I support the development and use of AI in Canada. It's critical for innovation, but I have heard how many constituents in London—Fanshawe are concerned about Bill C-8 and its broad surveillance powers. As the government deploys AI systems using sensitive data, what concrete safeguards is the industry utilizing to ensure that AI is used responsibly, with full protection for privacy and civil liberties?

     That's a great question. There are a number of technical safeguards that we can put in place, and research on this is ongoing.

     It is an ongoing, emergent threat as well. I want to be clear about that. This is not a well-defined problem, where we can sit down, develop solutions and then implement them. This is very much an emerging thing that we have to respond to. We need to be able to support both implementers and researchers in order to be able to understand how to respond to these in real time as these threats to privacy emerge.

     We also ought to be very careful in the responses to constituents like yours about what they can realistically expect at the moment, what is being done to support them and maybe where some of those gaps are.

     Thank you. The time is up for MP Holman.

    We will now end this panel with MP McKelvie for two minutes. Please go ahead.

     Thank you, Madam Chair.

    It's clear that we have work to do to ensure the safe, regulated implementation of AI.

     Dr. Lewis, I would like to take a moment to have you outline some of the benefits you think will come from AI and some of the good it can generate for Canada.

     Thank you so much.

    I think we've heard examples in passing, through the discussion, of some of the areas where AI is having some of the greatest impacts. Health care is an obvious one. There is personalized medicine, for example. Advanced screening of conditions is much faster and that means people can end up in treatment cycles or receiving appropriate care quicker. Also, medical professionals can focus on the use of their expertise and be more patient-centred, supported by technology that takes away some of the work that they would normally have to do at the same time as that. I think there are all sorts of benefits in places like health care.

    One of the panellists earlier on brought up the importance of SMEs. I think this is an area that is absolutely ripe for us to take advantage. SMEs make up the majority of the economy, but they're also not the best-placed organizations to be able to rapidly adopt AI and to understand how to do that well. I think there are all sorts of opportunities in different areas—supply chain, manufacturing, energy. I did a project with a window cleaning firm, and they were achieving increased efficiencies for their business and were able to grow in ways that they hadn't been able to because of the opportunities that AI gave them.

    What's needed is the ability to support these organizations to do this well, given the size and scale of what they're able to do and their access to expertise. We've talked a lot about the access to the expertise that we have here in Canada. We really need to make sure that expertise is available to the economy at large and not just to a few very large firms that are attractive as employers.

    I think, yes, there are lots of areas. I could keep talking about education, international students—

    I am sorry for interrupting, Dr. Lewis. Our time is up.

    With that, this panel comes to an end. I really want to thank all our witnesses for appearing before the committee and for their important input into this important study.

    With that, we will suspend the meeting for a few minutes so that our panellists can leave and the next set of witnesses can come in.

    The meeting is suspended.

     I call this meeting to order and welcome you back.

    I would like to make a few comments for the benefit of the witnesses and members.

    Please wait until I recognize you by name before speaking. For those participating by video conference, click on the microphone icon to activate your mic, and please mute yourself when you are not speaking. Those on Zoom can select the appropriate channel for interpretation at the bottom of your screen of floor, English or French. I remind you that all comments should be addressed through the chair.

    With that, I would like to welcome our witnesses for today's panel. We have Jim Hinton, intellectual property lawyer, joining us in person. From the Conseil de l'innovation du Québec, we are joined, via video conference, by Anne Nguyen, chief AI officer. From the Council of Canadian Academies, we are joined by Dr. Tijs Creutzberg, president and chief executive officer.

    Welcome to all witnesses, and thank you for appearing before the committee.

    All witnesses will have five minutes for their opening remarks, and then we will proceed to the rounds of questioning.

     Mr. Hinton, we will start with you. Please go ahead.

     Thank you, Honourable Chair and members of the committee on science and research. Thank you for inviting me to speak today. The work that you're doing is of tremendous importance to Canada's sovereignty and economic prosperity.

    I'm the CEO of Own Innovation, where I'm an intellectual property lawyer, a patent agent and a trademark agent. I'm also a senior fellow at the Centre for International Governance Innovation and a fellow at the BSIA, and I'm an assistant professor at Western University in the faculties of engineering and law. I'm appearing before the committee today as an individual.

    Today's economy is more than 90% driven by intangible assets, including intellectual property, data, algorithms and code, and the intangibles economy has economic impacts. You cannot commercialize what you do not own and control, and there are sovereignty impacts. You cannot govern what you don't own and control. Intellectual property allows you to own and control digital technologies.

    Where does Canada stand in AI ownership and control? AI patenting is a leading indicator of AI ownership. Since 2005, more than 2,734,000 AI patents have been granted globally, with more than 350,000 patents now being granted annually for artificial intelligence. Patenting is not an afterthought for AI; it's a major activity.

    Canada has been doing a very poor job of owning AI. Since the so-called pan-Canadian AI strategy in 2017, Canada's share of AI patent ownership has dropped from 0.81% to 0.54%. Canada went from being a have-not country to a have-none country, and it's not that we don't invent some great AI technology. It's that we don't own it, and because we don't own it, we can't make money from it. For every 2.5 AI patents Canada invents, it owns only one. In comparison, for every one AI patent that South Korea invents, it owns three.

    While important, patenting isn't everything. AI is also protected and commercialized with proprietary algorithms kept as trade secrets, copyrighted code and data, and data is protected as trade secrets and confidential information. Canada does not have a data asset strategy. Canadian companies can't compete in AI if they don't have access to the same quality and quantity of critical data as their global peers.

     Sovereign compute capacity is another precondition to digital sovereignty and economic prosperity. Digital sovereignty is a legal construct, not an emotional one. The legal construct says that to be sovereign means to be a Canadian company with Canadian ownership and control that is out of reach of foreign laws such as the U.S. CLOUD Act. A U.S. company that holds our data and algorithms on Canadian soil is subject to U.S. law, and Canadian justice does not apply.

     Digital sovereignty is not about physical location. Digital sovereignty is not about corporate assurances. Nokia Canada cannot be sovereign AI. CoreWeave, a U.S. company, cannot be sovereign AI. Foreign hyperscalers such as Amazon, Google and Microsoft cannot be sovereign AI. Even Canada's large telcos may not assure digital sovereignty because of their U.S. presence. Digital sovereignty requires exclusive jurisdiction by Canada's legal systems.

    I make the following recommendations to the committee.

    Canada needs to have an actual AI strategy, one that puts economic prosperity and national security at its core.

    We need to stop all funding of talent and research that gets owned by foreign companies.

    We need to build truly sovereign compute infrastructure that is 100% out of reach of foreign control.

    We need to spur an IP economy that allows Canada to own and commercialize critical technologies at home and at scale globally. Specifically, we need to have Canadian firms be global leaders in AI, IP and patent ownership. Finally, we need to create and scale Canadian firms that generate, retain and commercialize data assets.

     Canada's economic trajectory is currently negative. We are projected to be the worst-performing advanced economy for the next decade and the three decades after. That negative trajectory is continuing to this day with things like subsidies for EV manufacturing and adoption and funding of Canadian-based researchers without control over who gets the benefits of that research.

     In today's economy, it is not productive to create technology for somebody else, manufacture someone else's technology or buy someone else's technology. Canada needs to prioritize economically productive activities by owning and commercializing intangible assets and controlling and monetizing data. Canada's current path is one of a developing nation. If we keep it up, we're going to become the developing nation that we're positioning ourselves to be.

    Thank you.

    Thank you, Mr. Hinton.

    We will now proceed to Madame Nguyen for five minutes.

    Please go ahead. The floor is yours.

    Madam Chair and members of the committee, thank you for inviting me to contribute to your work.

    The Conseil de l'innovation du Québec is an independent organization supported by the Ministère de l'Économie, de l'Innovation et de l'Énergie, or MEIE. When it comes to artificial intelligence, its current mandate is to support and advise the ministry and certain government authorities responsible for public policy in this area to consult ecosystem stakeholders in order to use this technological driver for the benefit of Quebec's economic, social, environmental and cultural development.

    We also support MEIE in its efforts to mobilize businesses and organizations and promote responsible AI adoption across the province.

    Turning scientific excellence into tangible benefits requires a fluid continuum from research and experimentation to organizational adoption and commercialization.

    The council also conducted the consultation process Prêt pour l'IA, mobilizing 15 co-leaders, 250 experts, 420 contributions from members of the public and 1,500 participants to formulate 37 foundational recommendations. The council has also supported, with integrity, the following five recommendations that are consistent with the foundations of Prêt pour l'IA and adapted to current realities.

    First, the council recommends leading by example and becoming a customer of publicly funded innovation. To generate value, the government can no longer just fund research: It must adopt and test the solutions it helps bring about.

    A first public contract program would allow Canadian companies to win a first government contract when their solutions resolve matters of public interest. Being an early adopter creates a market, reduces risk and sends a structuring message to the ecosystem.

    Second, the council recommends creating demand and investing upstream in recurring matters of public interest. Several European countries use demand-side policies to drive innovation towards public priorities. This approach complements the legislative and ethical frameworks of Prêt pour l'IA.

    Certain issues like aging infrastructure, climate risk and pressure on public services are becoming so commonplace that the private market cannot bear the risks on its own. A federal demand creation policy would challenge the public, fund emerging technologies and drive Canadian innovation. This is a proven model to move things faster from research to impact.

    Third, the council recommends making AI literacy a national jurisdiction. A Canada-wide AI literacy strategy is essential to prepare the public for the technological shift. It should cover primary education, continuing education and requalification, as well as support for individuals after they cease active work. Qualified people are better prepared to make informed decisions, adapt to changes in the labour market and resist disinformation. Literacy is a pillar of collective resilience.

    Fourth, the council recommends structuring an industrialization continuum. We need to support a coherent path connecting basic research, applied research, experimentation, organizational adoption and commercialization. Investing in this continuum, data infrastructure, joint labs and test environments will translate our scientific excellence into real-world solutions and keep Canada on the leading edge.

    Fifth, the council recommends turning knowledge into a public good and supporting open intelligence and expertise. We need to build on open innovation infrastructure and collaborative AI technical spaces to accelerate applied research, knowledge transfer and responsible adoption across all sectors.

    Great digital advancements have historically relied on shared infrastructure like Linux, Python and other foundational technologies that showcase the power of open innovation. With that in mind, the council launched Brigade IA, a collective intelligence technical space that brings together experts, practitioners, public entities and economic actors to deal with the shared challenges of responsible AI adoption.

    Brigade IA pools scientific and technical knowledge, proven practices, reusable tools and solutions, and models to facilitate secure AI integration. This kind of open infrastructure builds collective capacity to innovate, reduces AI adoption risk and accelerates responsible implementation across all sectors.

    In conclusion, Madam Chair, AI represents a historic turning point. The countries that succeed will be those that turn their innovation into economic, social and democratic values.

    The five drivers presented today—leading by example, creating demand, educating the public, structuring the continuum and making knowledge a public good—can turn Canada into not only a scientific leader, but also a global leader in the responsible industrialization of artificial intelligence.

    Thank you.

     Thank you.

    With that, we will now proceed to Dr. Creutzberg, president and chief executive officer of the Council of Canadian Academies.

    Please go ahead. You have five minutes.

    Madam Chair and honourable members of this committee, I thank you for this opportunity to contribute to your deliberations today.

    My name is Tijs Creutzberg. I'm the president and CEO of the Council of Canadian Academies, or CCA.

    The CCA is an independent, not-for-profit organization established 20 years ago to provide rigorous, expert-led assessments of scientific matters of public interest.

    Our mandate is straightforward: to convene leading experts across disciplines and sectors to voluntarily apply their knowledge and judgment in assessing complex policy topics important to Canada. Our panel members do not advocate, make recommendations or represent political or sectoral interests. Rather, their job is to reach agreement on what the evidence says, with the goal of informing decisions made by you, our elected representatives, along with government policy-makers, public institutions and others.

    Today, I shall speak to some key findings from our recent work that are relevant to your deliberations, beginning with the valorization of AI discovery.

    In our most recent report, a panel looked closely at the conditions supporting the commercialization of advanced technologies in Canada. The findings are not encouraging. Indicators continue to point to the long-standing challenges that Canada faces when seeking to capture the benefits of homegrown scientific discoveries and technologies. Chief among them is the scaling of start-ups' access to capital. Firms often rely on foreign—mostly U.S.—capital to scale up, which can result in the loss of IP and economic benefits. The size of VC deals in Canada is also significantly smaller. Late-stage capital is scarce, and scale-up rates remain low overall. AI also needs talent, and here the panel found that many top researchers leave Canada after postgraduate training for higher salaries and better opportunities.

    For Canada, however, the big economic opportunity is less in the scientific discoveries of AI and more in the use of AI throughout the economy. This goes beyond simple diffusion to reimagining industries altogether—reinventing processes, structures and business models. Here, again, signs are not promising. Business adoption of AI has been low and growing too slowly, especially in contrast to our peers.

    Now let me turn to AI in research.

    AI has tremendous potential in scientific research. It can not only eliminate repetitive scientific tasks but also drive scientific investigation through automated hypothesis generation and experimentation. As it becomes more central, it also brings a number of challenges to Canada's research system. Through its ability to integrate disciplines, AI is blurring the boundaries among those very disciplines and thus challenging how research is typically administered, funded and evaluated. AI also requires that we think differently about research integrity, and about who or what exactly is responsible for research conduct. There remains general legal ambiguity when AI tools contribute to research discovery, error or safety risk.

    As for intellectual property, current IP laws struggle with machine-generated discoveries due to unclear inventorship and weak protection of datasets.

    This brings me to my final point on the protection of AI scientific discoveries. Many nations are seeking to harness AI. With this competition come security concerns, including foreign interference and IP theft. The challenge for AI is that it sits at the intersection between two competing objectives: open science goals—like open datasets, open models and reproducibility—and national security concerns. While Canada has policies in place listing AI as a sensitive technology, thus requiring administrative precautions, our panel flagged the need for Canadian researchers and institutions to go further and embrace a modern research mindset of having awareness of the risks, alongside responsible research conduct. It is one wherein researchers and administrators understand AI's dual-use risks, related geopolitical conditions and the security responsibilities they share to protect Canada and its people.

    Madam Chair and members, I have a final note from the CCA on the use of AI for evidence-based decisions. AI tools are, indeed, exciting, but they introduce many high-stakes risks. When poorly governed or used, AI can amplify bias, mislead and obscure uncertainty. Also, common AI tools only access published knowledge, missing the insights of practitioners, local knowledge, lived experience and linguistic nuance, all of which can be important for complex policy decisions. In short, AI has the potential to result in decisions that harm Canada's people, communities, economy and reputation. The CCA, for its part, is pleased to be part of a thoughtful community working to provide the trusted and unbiased leadership needed to ensure that AI enhances—rather than replaces—sound judgment in evidence for policy.

    Thank you. I welcome questions.

    Thank you.

     Now we will start our first round of questioning with MP DeRidder for six minutes.

    Please go ahead.

     Thank you, Chair.

    Welcome back, Mr. Hinton. My questions will be for you.

    The federal government spent $240 million on the American firm CoreWeave to build a data centre here in Canada. In a time of being in a trade war, we're using taxpayer dollars to fund American firms. In your opinion, through our data, are we also putting our national security at risk to the American firms as a whole?

     Yes. CoreWeave is a U.S. company, and even though the data centre is located just up the street from me in Cambridge, Ontario, it doesn't mean that the U.S. government can't get access to the data and to the algorithms. There's no reason why a Canadian firm wasn't chosen. There are many Canadian companies that could have been chosen. It wasn't because there wasn't capacity. It wasn't because there weren't Canadian companies with the right technology.

    All of those preconditions are compromising our national security and our economic security by design.

     Thank you.

    Microsoft announced a plan to invest $7.5 billion over the next two years for digital and AI infrastructure. In their procurement announcement, Microsoft issued a five-point plan to protect Canada's digital sovereignty. One point was to keep Canadian data on Canadian soil.

    Given that Microsoft is an American company and is subject to laws such as the U.S. CLOUD Act, can Microsoft truly guarantee sovereignty over Canadian data and IP or are there legal limitations that Canadians should be aware of?

     Microsoft cannot.

     In a European parliamentary committee, a legal officer from one of the cloud companies admitted and acknowledged that the U.S. CLOUD Act compels them to share data. France, for example, is moving away from Microsoft. Other countries are doing that because of this glaring gap.

     Corporate assurances won't cut it. We really have to build the capacity. It's not protectionist to build our own ability to protect our data. Even if it's located in Canada, it needs to be controlled and 100% out of the jurisdiction of foreign firms or foreign countries. The CLOUD Act is just one example. There are other policies and other pieces in place, like the PATRIOT Act and other things, that compromise our ability to govern these.

    Sovereignty is a lot more than this. Microsoft just may not be part of that piece of the value chain. They're having to transition out in countries like France.

     Would it not be more effective to strengthen our IP sovereignty by incentivizing Canadian companies such as eStruxture to build domestic data storage and compute infrastructure, rather than relying on American companies like Microsoft, where IP sovereignty cannot be guaranteed? How is that, in your opinion, building Canada strong and sovereign?

     It's not. We have great Canadian companies and we're relying on these U.S. foreign companies because our systems are compromised. We have captured systems by these foreign firms and foreign countries. We need to be standing on our own two legs and we're not. We continue to invest in systems—national defence systems and health systems—that rely on foreign firms, thus compromising the data, the algorithms and our economic competitiveness.

    If we give these billion-dollar contracts, these hundreds of millions of dollars' worth of contracts, to foreign firms, that's a lost opportunity, and our Canadian firms will be even that much further behind. We don't have the industrial capacity because we continue to put Canadian firms far below those global firms.

     Effectively, we're using taxpayer dollars to put our data at risk in terms of our national security and sovereignty.

     That's right.

     If a government does fund sovereign compute, how can it ensure the companies it funds still have the freedom to operate, in your opinion?

     That's a very big challenge. You can't just push out Microsoft, Google or Amazon without having freedom to operate. You have to work with Canadian firms that have a strong IP position in AI and cloud compute to be able to push them out.

    Ninety per cent of the patents issued out of the Canadian intellectual property office go to foreign firms, so even in Canada we have limited freedom to operate. We need things—patent collectives, resources—to be able to capture that IP, generate that IP and then have freedom to operate.

     Another area where we're spending taxpayer dollars is through SR and ED. We've learned in this committee that Huawei got $100 million back in SR and ED credits last year.

    Just because you're headquartered in Canada doesn't mean we're funding foreign nationals with our tax structure base right now.

    Can you explain how that's completely backward and what we should be doing instead?

    Yes. More than half of SR and ED, I believe, goes to foreign firms. All of that value—all of the IP and all of the economic returns—goes to those nations and not to Canada. We're funding our competitors and not realizing that value.

     Huawei still works with all of Canada's universities. I just did a quick search. Since 2023, there were more than 26 patents assigned to Huawei Technologies in Canada, as well as Canadian universities—at least 10 Canadian universities—so it hasn't stopped. It continues.

    I testified before this committee more than two years ago on this very subject, and Canadian universities are still working with Huawei.

    We've banned their technology, but we're funding their research. That's a little bit of a conflict.

    Yes.

    Security guidelines were put out in 2023 purportedly to manage research security. That hasn't changed. On the ground, there's been no impact. It continues to take Canadian research—a lot of those are AI patents and research—out of the country to China, to other jurisdictions and to the U.S.

     How many times have you spoken directly to the current government about what needs to be done here in Canada and have not been listened to?

     I was in this very building a couple of years ago with the then minister of innovation presenting this information. He said publicly, and was quoted in an article in The Globe and Mail, that we need more patents for our AI institutes. That hasn't happened.

    I did a quick search. Do you know how many patents the Vector Institute has in its name? There is one. I said that there were 2,734,000 patents granted and that's just one patent.

    I'm sorry for interrupting. The time is up for MP DeRidder.

    With that, we will proceed to MP Sawatzky for six minutes.

    Welcome to the science and research committee. Please go ahead.

     Thank you very much, Chair.

    Thank you to our witnesses for coming today.

    Dr. Creutzberg, I have some questions around AI alignments and ensuring that the pathway that AI is taking is aligned with our values.

    I was wondering if maybe you could explain in practical terms how you see AI alignments. Do you see any gaps between the direction AI is going and what we consider to be our human values?

     Thank you for your question.

    I'm actually not well prepared to speak to that question. This is not something we have looked at in the CCA or with any of our panels.

    I was wondering if perhaps you could speak to AI deepfakes being used in scams. Is that something that you've researched?

    We have not directly, no. We have looked at online harms and the like, but not specifically....

    Maybe in a broad sense, what does Canada need to do to develop AI responsibly and be a trusted international partner?

    That's a good question.

    Once again, this is not something that we've explicitly taken on, but broadly.... I'll leave it there. These are good questions to be putting to us, but I don't have a ready answer for you on that.

     Perhaps you could give an overview of what you've been researching lately.

     Certainly. We've been looking in depth at the state of our science, technology and innovation ecosystem, including looking at AI. We're looking at how AI is being diffused through the economy.

    We've looked a bit at AI research here in Canada. We've looked at the security environment of research. As I mentioned, that's the tension between open science and research areas of concern, which include AI. We're now looking at geodetic infrastructure and at some of the dependencies we have on U.S. infrastructure.

    Similarly, in the area of meteorological services, we've been looking at our system and some of those dependencies on the U.S.

    Could you elaborate on the security that you mentioned and the sovereignty of the AI infrastructure here in Canada? Are there any gaps that you see right now that we need to address?

     On the AI security, apart from some dependence on U.S. infrastructure, in the context of research there are gaps. The big issue here within the research community is having to learn how to deal with this tension between open science and research security. It's a big mind shift for the academic community.

    We talked about Huawei. The universities are still reaching out to Huawei and still engaged in partnerships. This takes time. The research community needs to be learning about this and changing their mindset as to how they think about their research and the impacts they're having in the broader geopolitical economy. It's something that they have never had to do in the past. It does take time and that's why we're seeing some lags, I think.

     In terms of infrastructure that we can invest in as a government, what is the most important thing that you see right now? Is it data centres? Is it something else?

    That's a good question. Is it specifically in terms of AI sovereignty? Yes.

    I don't know if I can give you a decent answer on that. Again, making recommendations on the infrastructure is not something we've looked at explicitly, so I'll pass on that.

    Thanks.

     No worries.

    Could you speak to anything we can do to keep IP within Canada? How do we attract researchers in the AI sector to Canada?

    The government has certainly made a move to bring talent into Canada. It's not clear to me at this stage how much of that is focused on AI.

    In terms of keeping patents in Canada, we have to improve our innovation ecosystem here. The panel is very clear that the need of Canadian start-ups, whether they're in AI or in other areas, to go to the U.S. for capital means that we lose the IP in the process. It transitions out of the country. We see a net IP outflow going out of the country as a result of those financing arrangements.

    Fixing the capital environment for our small and medium-sized enterprises, which are doing a lot of research at the moment, is a key step to help fix the outflow of IP.

    To dive in a bit further, what can we do to make things more competitive here? Is it higher salaries for researchers? Is it tax credits?

    There are a lot of interdependent pieces to this problem. Without retaining those larger companies in Canada, we don't have the opportunities, and without the talent, we're not able to build out those companies.

     There are a lot of pieces that need to come together in order to make the shift. It's not one thing; it's several things. I think it needs a concerted effort and a commitment in the longer term to pull it off.

    Thank you very much.

    Thank you. Your time is up.

    We will now go to MP Blanchette-Joncas for six minutes. Please go ahead.

    Thank you, Madam Chair.

    I'd like to welcome the witnesses who are with us today.

    My first question is for you, Mr. Hinton.

    Is there a binding legal mechanism to stop strategic AI assets that are, for example, publicly funded from leaving the country?

     No. There are announcements about intentions to put pieces in place, but ultimately we see Canada's AI assets fleeing the country at an alarming pace. Our data is out the door very quickly. Our algorithms and our patents...all of that is there. There's no strategic oversight. There are no mechanisms. We, in fact, have mechanisms to accelerate the ability of Canada's AI technologies to leave the country.

    Public subsidies, or taxpayer dollars, Canadians' money collected through taxes, can be used, particularly in AI, to consolidate the intellectual property of potential foreign actors. Is that right?

     In Canada, we fund our research institutions to exfiltrate value around artificial intelligence to be owned by foreign firms. We know Geoff Hinton—no relation—is a great researcher, but his research is owned by Google technologies. The chair of Google, as he was at the time, said, “Thank you, Canada, for all of the foundational AI research.”

     Do you know how much we get? We get nothing. Ozempic and all of these other drugs come out of the University of Toronto, and we get nothing. It's a trend that we have. We create a lot of great stuff and then we incentivize all of that great stuff to be owned and capitalized. There's Novo Nordisk. Those jurisdictions get the economic rent. We don't.

    I'd like to take advantage of your presence here today and your expertise as a lawyer to ask you this: In your opinion, is there any independent authority in Canada today with legal power that could immediately disable a dangerous AI system?

     No, there is nothing. It's the wild west. It's anarchy.

    Our digital systems do not have any guardrails. There's the Privacy Act from 25 years ago. There are older things from before my time that still permeate, but there is nothing to stop our digital systems and AI systems from doing whatever they do, and that's by design. American firms love the lack of guardrails. That's a policy choice, because it allows them to extract more rent from the Canadian economy—the American economy as well—and other jurisdictions.

    We're implicitly supporting the extractive nature of the data-driven economy by having no guardrails and no mechanisms to take harmful AI and data-driven systems off-line if they cause harm.

    Let's summarize all that. We're heavily funding AI. The government was very proud to do so in the last budget. They even say they want to be the world leader in artificial intelligence. However, we don't have an independent oversight authority, we don't have any clear deactivation powers, as you've just confirmed, and we lack robust guardrails.

    In your opinion, is that a comprehensive strategy or an incomplete strategy? As an expert, how do you see this?

     There was never a strategy. It was a research funding approach to say we need to have researchers who work for foreign firms physically located in Canada, but the value and the IP all go somewhere else. It was never a strategy. We asked Innovation, Science and Economic Development Canada for the strategy document. None was ever provided.

    People have admitted on the record, in a Globe and Mail article in January 2023, that no strategy ever existed. It was an announcement. It was performative, and it continues to be. The consultation that happened in the fall was performative. It was not serious. I know people on the committee, and they made an effort to feed back into it. However, it was performative, not serious, and we'll have similar outcomes with the next process.

    You just said some very important things. There's uncertainty, gaps and no oversight.

    The government tells us that AI could help people. In your opinion, who stands to benefit from this uncertainty and lack of oversight?

     We'll see job losses with AI as people replace somebody making, let's say, $50,000 or $100,000 per year with an AI system that costs $25,000 or $50,000. That $25,000 or $50,000 goes to those who own AI. Canada does not own AI, so we replace a Canadian worker with an AI system. AI adoption is a folly if we don't own the AI technology. We push AI adoption, but then, because we don't own the technology, we're replacing the worker with a digital system where the profits are maximized outside of the country. That's why we're going to become a developing nation.

    Let's look at what's happening elsewhere. Do international best practices recommend a clear separation between economically promoting AI and regulating it? I'm asking you, because right now the minister can do anything. He's attracting investors and regulating legislation, but you're telling me there's already a shortage.

    Based on your expertise, what do international best practices tell us?

    We don't.... I'm not defeatist. We can do well. I look to South Korea as a great example. I look to the Nordic countries as other strong examples. We can make our own sovereign systems, but at the core we have to have Canadian firms that we can control and that we can govern.

    It's like me telling you what you can do with your backyard pool. Google's not going to have ethical AI or unbiased AI if we tell it to. What happened with the digital sales tax? That didn't work. The Online News Act.... We can't regulate these digital systems that we don't own or control. We have to build Canadian domestic firms that we can use to advance our Canadian values. Then, once we have those, there's a huge market globally for them.

     Mr. Hinton, the time is up for MP Blanchette-Joncas.

    We will start our second round of questioning, and we will go to MP Mahal for five minutes.

    Please go ahead, MP Mahal.

    Thank you, Madam Chair.

    Thank you to all the witnesses who came to testify before this committee. I'm going to start with Mr. Hinton.

    AI systems are increasingly trained on massive datasets that often include copyrighted books, music, images and news, frequently without the consent of or compensation to the creators. Canada still lacks a clear legal framework on whether that constitutes copyright infringement.

    From your perspective as an IP lawyer, how exposed are the creators right now? Why has the Liberal government failed to provide certainty for artists, journalists, rights holders, etc.?

    There's no update on what happened. There were consultations that took place years ago, and there's really no result from those consultations.

    Inaction means that Canadian creators and global creators under copyright systems are having their data scraped, taken and then appropriated and value-extracted for those large AI companies, predominantly foreign companies. It's an economic choice to use Canada's economy to extract value. That really is because I think we have captured systems here that would prefer to advance U.S. interests—they have those big AI systems—over Canadian interests.

     Thank you.

    There's a growing confusion around who owns AI-generated outputs, whether it's code, images or written content. That uncertainty makes it harder for Canadian start-ups to commercialize their products or attract investments.

    Does Canada's current IP regime give businesses and innovators the clarity they need, or is Ottawa leaving Canadian firms at a disadvantage compared to the U.S. and other competitors?

    There is no clarity around that from a copyright perspective in Canada and also from a patentable subject matter perspective in Canada. What is patentable? What is not? What is protectable? What is not? Canadian firms are left to the international rules. We're taking what the U.S. patent office says, what the U.S. says, about copyrighted works and AI-generated works. Instead of setting a standard that the globe can adopt and that advances our economic position and our national security positions, we're basically ceding that to the U.S., to China and to other jurisdictions.

     That seems like a gross act of failure on the part of the government.

    We heard from Dr. Creutzberg as well that there is a legal ambiguity when it comes to AI retention. We can talk about the lack of having parallel legislation to the U.S. CLOUD Act and other parallel or friendly legislation in regard to property rights, etc.

    What are your recommendations for steps that we as government need to take to ensure that we have that parallel legislation, so that Canadian data is protected, Canadian integrity is protected and taxpayer dollars are spent in the right direction?

     First, we need to have that capacity. We need to build sovereign capacity, and then we need to switch over to that sovereign capacity.

    From a legislative perspective, we need to build the guardrails that we need to have for our innovation and data-driven economy. We need to have some say, participation and leadership on all of the harms that we're seeing come out of AI. It's across the board, whether it's health, financial, online harms or the rest of it. We need to move swiftly with that based on global standards.

    Earlier in your testimony you mentioned that there have been hundreds of thousands of IP patents issued globally. Can you shine a light on how many we have generated as a country?

     Canada owns about 12,000 of those 2.7-plus million AI patents. We're an insignificant and decreasingly significant player in that area.

     What do you think is the reason behind the contradiction that when it comes to the researchers and innovators, we have the best talent in the world, but when it comes to patent security and generation, we lag so far behind?

    In the fall budget, we said we're going to put $1.7 billion into attracting foreign researchers to Canada. There are no guardrails on who gets the benefit of that research. If you don't say upstream, “Look, we need to make sure we capture these economic benefits”, then we won't get the economic benefits. We don't govern. We don't have any pieces in place to make sure that the outputs of Canadian-funded research end up benefiting Canada.

    I'm sorry for interrupting. The time is up for MP Mahal.

    We will now proceed to MP Rana for five minutes.

    Please go ahead, MP Rana.

     Thank you, Madam Chair.

    Thank you to all the witnesses.

    Mr. Hinton, what are a few changes this government could implement to make it easier for Canadian universities and research centres to scale AI IP in Canada?

    It is this industry and university collaboration that needs to happen. Right now there's a big deficit of trust with Canadian firms and Canadian universities. The advice that I give to companies I'm working with that are looking to collaborate with Canadian universities and Canadian companies is, “Don't do it. It's going to lead to problems down the road.”

     Right now, if you're a small Canadian start-up company and you work with the university, as soon as you get validation, the university will push you aside and look for some U.S. firm to get a $1-million or $2-million funding program. Then, basically all of the work that you've done as a Canadian firm to advance this technology gets swooped up by this large international firm. You're giving your competitive advantage to the university, which then goes and leverages that to work with a foreign firm.

     If the federal government enforces strict expectations and regulations on funding this research, do you foresee any difficulties or trade-offs?

     We look to the U.S. and the Bayh-Dole Act. They have explicit provisions to make sure that the U.S. benefits economically from it. We see this in other jurisdictions, like Finland, that say they need to make sure they have the economic benefit. Other jurisdictions put these rules in place, and we should do the same. We're not going to lose researchers. We're going to increase our competitiveness with other jurisdictions.

    Thank you.

    How are the current R and D support programs, such as the scientific research and experimental development tax incentives and the industrial research assistance program, helping to alleviate challenges for Canadian AI firms. What do you suggest?

    There was a SR and ED review ongoing. I don't know what happened to that. That was a year or so ago. We need to see what happens. We need to augment SR and ED to make sure that Canadian firms benefit. As I said before, more than half of it goes to foreign firms, so we need to have that corrected.

    There's a disproportionality. There are great programs like ElevateIP, the Innovation Asset Collective and IP Ontario, for example—publicly funded ones—and they received renewed funding in the fall. They're subscale, though. We put $57 billion into battery branch plants and then $50 million over five years. You spent more on scaffolding for this building here than we did on intellectual property.

    Are there countries that do a better job than Canada of retaining publicly funded IP that Canada should study and adopt...?

     The Americans do it very well. China does it very well, and we can adopt things from them. However, small, open economies like South Korea do it extremely well. I have a Samsung phone. We have a Hyundai hybrid vehicle. There's no reason. This small Korean country does so well at innovation, so we can do the same thing.

    We have strategic resources and energy resources, and our talent is fantastic. We need to take that foundation, in critical minerals, for example, and then build that in and capitalize on that.

     Thank you.

    Dr. Creutzberg, how attractive is Canada to international researchers? What steps could we take to attract talented researchers to Canada?

    This country is attractive to international researchers. There's no question. We have a very good reputation in research.

    In terms of increasing that, look at some of the challenges facing Canadian researchers in accessing research funds—the funding systems to support their research areas—and make sure we have funding for that.

     In the global context, what does AI leadership realistically mean for Canada?

     What does AI leadership mean for Canada? I'm not sure if I can cleanly answer that. It's not something I'm prepared to answer. I'll leave it at that.

    How do we ensure that Canada remains a leader in AI?

     Certainly, we have to fix our innovation ecosystem. The comments that my colleague made are on the mark. It's tricky. The global economic order is shifting. What made sense 10 years ago no longer makes sense today. We have to adapt and change in the context of the new geopolitical realities, which we don't have the answers to.

    Thank you. The time is up for MP Rana.

    With that, we will now proceed to MP Blanchette-Joncas for two and a half minutes.

    Please go ahead.

    Thank you, Madam Chair.

    I just want to inform you that I will be asking a few questions, but I will stop before my time is up to move a motion.

    My question is for you, Ms. Nguyen. We haven't forgotten about you.

    Is the main roadblock keeping SMEs from adopting AI the lack of structured funding for experimental development, rather than a technology issue?

    Thank you for the question.

    Yes, the challenge around AI adoption is really operational in nature, in terms of literacy. We have to be able to establish a common base. We've talked a lot about research at this meeting, but if we aren't able to identify high-potential business environments, we're really going to miss this historic opportunity to adopt AI that will help us perform better and optimize things. So, on a common basis, we have to succeed in establishing institutions, independent authorities without a competitive position, and then put in place benchmarks, criteria, common languages and tools for all businesses, regardless of their size.

    I should also point out that we have different economic realities, because there are a lot of unions. Today, AI is capable of taking charge of a number of mechanisms and processes from end to end. We have to break down the silos we work in so that we can integrate these tools into our economic realities.

    The first step would really be to make that common base available so that people can rise up. Once they rise up, they will really want to keep innovating.

    Are there any other vital elements you would like to share with us today?

    It's important to understand that there are three types of professions that may be at risk or exposed to artificial intelligence. There are professions in which people can improve their performance, professions that can be transformed and professions that will be at risk if they can't be moved in the right direction. Given that reality, I think it's also important to recognize the impact of the work we're doing thanks to Brigade IA in Quebec. It brings together 95 AI experts at all levels, from research to adoption. These individuals are able to adapt all of that to those realities, so we need talent on the ground—

    Pardon me, but I have to interrupt you, Ms. Nguyen.

    Madam Chair, the national AI strategy will have a structural impact on our economy, national security, critical infrastructure and digital sovereignty. In such a strategic area, it's essential that Parliament and the public have full and complete visibility when it comes to the consultations, the stakeholders and the documents that guided the strategy. Transparency is not optional when you're dealing with decisions that will bind Canada for decades.

    The motion I'm introducing is simply to allow the committee to exercise its oversight role and ensure full and timely accountability. I'll read it now. We also debated this motion on February 2. It reads as follows:

    I am now ready to debate this motion with my colleagues in order to adopt it.

     Thank you, MP Blanchette-Joncas.

    We have a motion on the floor, which has been brought by MP Blanchette-Joncas.

     We will have to suspend the meeting because this motion was debated earlier. Is it all right if we let the witnesses go?

    MP DeRidder, go ahead.

     Before we suspend the meeting, can I put a motion on notice? It's just a notice.

    No, we cannot get into anything. We already have a motion on the floor and we have to debate that. He has asked.

    I just wanted to get the members' permission to let our witnesses go. Is everyone okay with that?

    Some hon. members: Agreed.

    The Chair: Thanks a lot to all the witnesses for appearing before the committee and providing your input. You are okay to leave.

    The meeting is suspended.

     I call the meeting to order. The floor was with MP Blanchette-Joncas.

    Just to clarify, we were debating this motion at the meeting on February 2, and the debate was adjourned. Procedurally, what needs to be done is that if MP Blanchette-Joncas wants to bring it back, he can ask for the debate to resume to start the debate.

    Go ahead, MP Blanchette-Joncas.

    Thank you, Madam Chair.

    I'm simply asking that we resume the debate that was suspended when my motion was introduced on February 2.

     Thank you.

    MP Blanchette-Joncas would like to resume the debate. When the debate was adjourned, we were on a subamendment moved by MP Baldinelli that the amendment be amended by replacing the words “sixty (60) days” with the words “thirty (30) days”, and by deleting the words “and that the information be in compliance with information that would be given via an Access to Information and Privacy request.”

    I will also read the amendment that was moved by MP Noormohamed that the motion be amended by replacing the words “within seven (7)” with the words “sixty (60)”; by adding after the words “all of the following documents” and the words “from September 1st, 2025, to the present,”; by replacing the word “Pan-Canadian” with the word “National”; and by adding after the words “in their entirety, whether solicited or unsolicited;” the following: “and that the information be in compliance with information that would be given via an Access to Information and Privacy request.”

    The copies of the motion with the amendment and the subamendment are being distributed by the clerk to everybody. We are on the subamendment. Thank you.

    MP Blanchette-Joncas has moved to resume debate on this motion for which we have a subamendment, an amendment and the main motion. Now we will vote on whether we resume debate on the motion.

    I will ask the clerk to please take the vote on whether we start the debate.

    Before we call the vote, I would hope that we'd be allowed to have all our members in place here.

    Where is the member? Has he left?

     He just stepped out. My understanding is that my own staffer is going to get him. He was going up to the House.

    Because MP Blanchette-Joncas has moved to resume debate, we need to vote whether we resume the debate or not.

     Someone's going to get him right now.

     Give it one minute. We have to—

    It's just a vote to resume debate. Is that right?

    Yes.

     Do my Liberal friends...?

    I think we should take the vote. If the member has gone out, or.... I don't know where the member is.

    We'll take the vote.

    (Motion agreed to: yeas 9; nays 0)

    The Chair: We resume the debate. We have the subamendment on the floor.

    Are there any comments on the subamendment?

    An hon. member: Do we have printed copies?

    The Chair: As yet, we have not been able to get them.

     You can refer to the minutes of the meeting of February 2. You will see all the information.

    We have the subamendment on the floor. I'm seeing no hands raised.

    Mr. Clerk, can you please take the vote on the subamendment?

    (Subamendment agreed to: yeas 9; nays 0)

    (Amendment as amended agreed to)

    The Chair: Now we have the motion on the floor as amended. Is there any debate?

    Would you mind reading what we're voting on?

    We will suspend the meeting. The clerk has to put that together—the motion as amended.

    The meeting is suspended.

     I call the meeting to order.

    The motion as amended has been circulated to all the members. Now we will proceed to the vote.

    (Motion as amended agreed to: yeas 5; nays 4 [See Minutes of Proceedings])

    The Chair: With that, is it the will of the committee to adjourn the meeting?

    Some hon. members: Agreed.

    The Chair: The meeting is adjourned.