Status of Women Committee on Oct. 26th, 2026

[The Chair, Conservative, Dominique Vien]

I call this meeting to order.

This is meeting number 51 of the Standing Committee on the Status of Women.

Pursuant to Standing Order 108(2) and the motion adopted by the committee on Monday, September 21, the committee is meeting to begin its study on the impact of artificial intelligence on women, girls and 2SLGBTQIA+ individuals.

Today's meeting is taking place in hybrid format, pursuant to the Standing Orders.

To ensure the meeting goes smoothly, I would like to make a few comments for the benefit of the witnesses who are with us today, and members.

Please wait until I recognize you by name before speaking. Your co-operation is appreciated. For those participating by video conference, click on the microphone icon to activate your mike and please mute yourself when you are not speaking. If you are in the room and you wish to speak, please raise your hand. For those on Zoom, please use the raise hand function.

I would like to remind witnesses that committee members may ask questions in either French or English. If you will need interpretation, please take a moment now to select the listening channel required so as not to waste time when it's your turn to speak.

A reminder that all comments from members and witnesses should be addressed through the chair; however, I'm a rather easy-going chair who goes with the flow. In other words, unless it's total chaos, I won't intervene.

Before we welcome our witnesses, I'd like to give a word of warning. As you know, we'll be discussing issues related to gender violence. This can be triggering for those who have had similar experiences. If participants experience distress or need assistance, please don't hesitate to let our clerk, Ms. Miller, know.

It's important for all the witnesses and members to recognize that these are difficult discussions. Since we are accustomed to having such discussions and we're pretty good at it, we welcome all your comments with a lot of compassion, empathy and kindness, like always.

Now, I want to welcome our witnesses.

As an individual, we have Indra Kubicek, chief executive officer, Digital Moment. From the Council of Canadian Innovators, we have Skaidra Puodžiūnas, senior director of policy and advocacy, and Daniel Perry, director, federal affairs. From Women's Health Collective Canada, we have Amy Flood, executive director.

Welcome. We will begin with opening statements.

Ms. Kubicek, the floor is yours for five minutes. Thank you.

[Indra Kubicek, Chief Executive Officer, Digital Moment, As an Individual]

Thank you, everyone.

Madam Chair and honourable members of the committee, thank you for the opportunity to appear today.

My name is Indra Kubicek. I am the CEO of Digital Moment, a national bilingual charity that has spent over a decade empowering young people, with a particular focus on girls in under-represented communities, and educators with digital skills and confidence.

We stand at a pivotal moment. Artificial intelligence is fundamentally changing how we work, learn, make decisions and participate in society. While the potential opportunities are extraordinary, we risk the benefits not being evenly distributed unless we act with intention. My concern is that women in historically under-represented communities risk being left behind, not because they lack ability but because we are not creating the conditions for their success.

I want to focus on three challenges.

First, who is shaping the future of AI? Women remain significantly under-represented in AI research, development and leadership roles. This is not simply about equal representation. It is about whose perspectives shape technology and whose needs are being overlooked.

AI is not neutral. It learns from historical data, which reflects existing inequalities. Without safeguards, we risk codifying those biases into systems influencing our lives. We need women from diverse backgrounds and 2SLGBTQI individuals participating in AI design, governance and safety, because diversity isn't just about creating opportunities for women. It's about building better and safer systems for everyone.

Earlier this month, the UN Human Rights Council adopted a resolution calling for greater participation of women and girls in digital technologies, mentioning AI 18 times in the document. Canada has an opportunity to be a leader and turn that commitment into action.

Second, who benefits economically and who is most at risk? Women are disproportionately represented in occupations exposed to generative AI, particularly administrative roles.

Also, consider women returning from maternity leave. I've spoken with women, even highly educated senior leaders, frightened by how much their workplaces changed while they were away, and they often return without the necessary training to catch up. Consider women entrepreneurs. AI could transform their productivity, yet women-owned businesses are less likely to adopt emerging technologies.

We need AI literacy, and it cannot be reserved for technology careers. It must become a foundation for economic participation. Women need trusted spaces to learn, ask questions and build confidence without fear or judgment.

Third, how do we ensure the next generation—young girls—have a different experience? If we want women leading AI in a decade from now, we must invest in girls today. We cannot wait until university, when too many have already decided that they don't think this is a career for them. Girls need age-appropriate AI learning opportunities, ideally before 12 years old, when confidence and perceptions of possibility are taking shape. They need mentors, role models and opportunities to create, question and solve problems, and to see themselves not simply as users but as people shaping technology.

This isn't just an education strategy. It's an economic one. Building this pipeline requires sustained investment, not isolated programs or short funding cycles.

What do I propose the federal government do?

First, invest in inclusive AI literacy starting young and continuing throughout women's careers.

Second, support targeted workforce and entrepreneurship programs, particularly for women facing career transitions and barriers.

Third, unite government, industry, educators and not-for-profits around a long-term commitment to inclusive AI with accountability for addressing discrimination and measuring progress.

Let's set a measurable goal for 2035, a Canada where women are significantly better represented in AI leadership, development and economic opportunity. We are not simply witnessing a technological transformation. We are shaping a societal one. The question is not whether AI will change women's lives. It already is. The question is whether we will ensure they have the opportunity to shape that change.

Let's make sure that the future of AI is built with women, not simply for them.

Thank you.

[The Chair, Conservative, Dominique Vien]

You're very disciplined, Ms. Kubicek. Thank you very much. That was great.

Mr. Perry for five minutes.

[Daniel Perry, Director, Federal Affairs, Council of Canadian Innovators]

Good morning, Chair and committee members.

Thank you for the opportunity to appear today. My name is Daniel Perry. I'm the director of federal affairs at the Council of Canadian Innovators. I'm joined today by my colleague, Skaidra Puodžiūnas, our senior director of policy and advocacy.

The Council of Canadian Innovators is Canada's 21st-century business council. We represent over 180 Canadian-headquartered, high-growth technology companies operating across a number of sectors, including artificial intelligence, big data, defence and digital infrastructure.

Today's committee study comes at an important moment, when building Canadian has never mattered more. The global economy is no longer neutral or rules-based. Leading economies are using industry strategies to secure control over critical infrastructure, value chains and standards. AI sits at the centre of this as a foundational layer not just for economic growth but also for national security.

The government's new AI strategy assumes that adoption follows trust. This is false. According to Statistics Canada, business use of artificial intelligence has tripled since 2024, where during the same time period, trust in AI has stagnated or declined. Canada's challenges are systemic and structural. Canadian firms have been slow to adopt new technology for decades. Trust was never the reason for this.

As the government can make the biggest difference, what is needed is to create conditions that allow companies to succeed while also protecting Canada's most vulnerable people. That is why this committee's focus on regulations is important. Where new rules are introduced, they are needed where they are necessary. They should look to address clear gaps in the current system and examine the current protections. This can be done using standards and setting them here in Canada, as well as by supporting Canadian companies through procurement.

Our recent submission to the AI transparency task force sets out five principles to guide this work.

First, assign responsibility based on who controls what. Developers should explain the systems they have built, while deployers should explain how AI is being used, what data it is handling and when humans are involved. Obligations should also scale with risk. An AI tool that makes payments on behalf of someone requires greater scrutiny than one that is being used to draft internal documents. I look to our membership for this. BorderPass is a great example. This year alone, its AI platform has processed over 12,000 immigration applications. A licensed lawyer oversees the application process, while AI is used for the volume. This ensures that accountability and scale work hand in hand.

Second, the government should help Canadians recognize when AI is being used to deceive them. Firms should disclose their use of AI, and labelling should be focused on content and interactions where a person could be misled or not aware that they're not talking with a human.

Third, requirements should be targeted and able to keep up with the pace of the progression of AI. Using recognized standards such as C2PA for content credentials will serve Canadians better than new binding legislation. These standards are able to keep up with the industry in a way legislation alone cannot. Last week's cabinet directive recognizing national standards and international standards as the default for regulators is a welcome step forward.

Fourth, the government should build on the institutions we currently have. Create new rules that will fill genuine gaps in the system rather than creating duplicate work or adding more to a growing bureaucracy. New AI should genuinely fill this and we have opportunities to do so.

Finally, procurement is one of the most underused tools that this government has at its disposal. Across all levels of government, public purchasing makes up roughly 15% of our GDP. When the government buys Canadian, it validates the technology here and abroad, helps firms scale domestically and also allows Canadian companies to respond to the needs of Canadians.

When Canadian firms own their intellectual property, own their data and their leadership team is based here, they remain accountable not just to their neighbours who are Canadians but also to Canadian law. If Canada is not leading, it will fall behind. AI decisions will be made by other countries and foreign companies that are not keeping the needs of women, girls and 2SLGBTQI+ communities in mind.

Building Canadian means building companies that are owned here and the technology remains here. This is how we ensure AI is safe for all and effective for everyone.

With that, I'd like to thank you. I look forward to your questions.

[The Chair, Conservative, Dominique Vien]

Thank you, Mr. Perry.

Good day, Ms. Flood.

The floor is yours for five minutes.

[Amy Flood, Executive Director, Women's Health Collective Canada]

Thank you very much.

Madame Chair and committee members, my name is Amy Flood. I am the executive director of the Women's Health Collective Canada.

Thank you very much for the opportunity to appear before you today and to contribute to this important study on the impact of artificial intelligence on women, girls and 2SLGBTQI+ individuals.

Women represent approximately half of Canada's population and nearly 40% of our labour force. By 2030, women are expected to control approximately half of Canada's financial wealth. Women also make up 75% of our health care workforce. Women are not a niche population. They are a critical driver of Canada's health, workforce, economy and prosperity. That is why the decisions we make about artificial intelligence matter.

AI has the potential to transform health care, research, education, employment and economic participation. In health care alone, AI is projected to generate billions of dollars in annual efficiencies and savings, yet if these systems are built using incomplete, biased or unrepresentative data, they risk deepening the very inequities they have the potential to solve.

My remarks today focus on women's health and an area where both the risks and the opportunities of AI are especially significant.

For decades, women have been under-represented in health research, clinical trials, health datasets and innovation investments. This has resulted in persistent gaps in our understanding of conditions that uniquely or disproportionately affect women, including not only reproductive health conditions but also menopause, cardiovascular disease, chronic pain, autoimmune disorders and mental health challenges.

These gaps are not only a health issue. They are an economic issue. Research conducted by our partners at McKinsey & Company found that closing the women's health gap in Canada could contribute $37 billion annually to Canada's GDP by 2040 through improved health outcomes, workforce participation, productivity and reduced health care utilization.

The fact of the matter is that AI is only as good as the data it's built on. When that data is incomplete or biased, AI can reinforce existing inequalities, leading to poorer health outcomes for women and gender-diverse populations.

The implications for 2SLGBTQI+ communities are even more concerning. We already lack sufficient sex- and gender-disaggregated data. Without intentional efforts to collect representative data, design inclusive systems and evaluate outcomes across diverse populations, AI risks making already invisible populations even more invisible.

At the same time, AI represents a very extraordinary opportunity. When developed responsibly, AI can accelerate research, improve diagnosis, personalize care, expand access to trusted health information and empower individuals to better understand and manage their health throughout every stage of life. It has the potential to transform how we address women's health challenges from menstruation and fertility, through pregnancy, postpartum care, perimenopause, menopause and healthy aging. We must ensure AI works for everyone.

Women are not a single group and neither are gender-diverse populations. People's experiences and health care needs differ based on factors such as race, age, income, geography, disability, sexual orientation and gender identity. If AI is built using data that doesn't reflect that diversity, it risks leaving many people behind.

Beyond health care, we must also consider who is building the AI economy. AI is reshaping employment, entrepreneurship, research and innovation, yet women remain under-represented in many technology sectors, leadership positions, investment portfolios and commercialization opportunities. Ensuring equitable participation in the development, governance and commercialization of AI is not only a matter of fairness. It is essential to creating technologies that work for all Canadians.

Canada has the opportunity to become a global leader here in responsible and inclusive AI. However, leadership will require intentional action, investment and accountability.

In closing, artificial intelligence presents both tremendous promise and significant risk. If AI systems are built on incomplete data, they may deepen the inequities that women and gender-diverse populations already face today.

However, if built responsibly—

[The Chair, Conservative, Dominique Vien]

Thank you very much, Ms. Flood.

This concludes the opening remarks for now. We'll begin with questions from members.

Mrs. DeRidder, you have the floor.

[Kelly DeRidder, Conservative, Kitchener Centre, ON]

Thank you, Madam Chair.

Mr. Perry, I'm going to ask you a couple of questions.

Skaidra, feel free to chip in as well.

There's a lot of discussion around AI and the risks, including the potential for discrimination. However, AI also has the potential to improve productivity and how decisions are made within companies. Where do you see AI creating the biggest opportunity for workers in Canada?

[Daniel Perry]

Thank you very much for the question. It's a good question to ask, especially as we take a step back to look at this.

AI is transforming how we're interacting, whether that's when we're watching the Olympics and bobsledding—through how it stitches together the camera angles—or how we write and prepare for committee appearances. As we're looking at where it can make the biggest gains, we also need to think about how our companies are adopting it. How are we empowering those inside the companies to use it as well?

That is where we need government to better support our companies, especially Canadian companies, and to provide more opportunities. The best way to do that is to be an anchor customer. As I mentioned in my opening remarks, public procurement makes up roughly 15% of GDP. If we can shed even 1% or 2% of that to companies, think of what that would mean for them. When they get a purchase order from the Government of Canada, it is not just a purchase order from the Government of Canada. It's an indicator to other buyers—here and as they're expanding globally—that the government believes in them. They can also go to the bank and get better bank terms.

Therefore, as the government is looking at productivity, it's important that we have conversations like this with members of our innovator community, especially the ones in your riding, to see how they can best support you.

[Kelly DeRidder, Conservative, Kitchener Centre, ON]

Thank you.

Skaidra, would you like to add anything?

[Skaidra Puodžiūnas, Senior Director, Policy and Advocacy , Council of Canadian Innovators]

One thing I would add is the potential for AI to support regulated industries. There was actually a really great report, which I will send in follow-up. One of our Prairies-based members, Samdesk, did a report looking at how Canadian-regulated industries are adopting AI and the tremendous gaps in making that shift.

When we think about health care, mining and traditional industries that haven't really thought about the intersection with AI, we see there's such a huge opportunity there. There's such an opportunity to gauge how they're in need of using these productivity gains to bring about more high-value opportunities for Canadian workers. To continue with what Daniel was saying, again, it's bringing that focus on Canadian industries and how that can intersect.

[Kelly DeRidder, Conservative, Kitchener Centre, ON]

Thank you so much.

I correlate this to the previous industrial revolution. We're in another one, moving into the technological era.

That being said, we need to help businesses adopt. It's just like in the last industrial revolution, where they leaned out processes and people went from making the parts to running the machines that made the parts. There was upskilling that was required in that as well. Businesses have to adopt or else they're not going to remain competitive.

How can the government assist companies with this transition? It is the same as the previous industrial revolution. I just call this one the technological revolution.

[Skaidra Puodžiūnas]

I can start.

First and foremost, I think the more opportunities that domestic innovators have to be part of key dialogues and forums with our own Canadian decision-makers.... This is super important.

I'll offer a concrete example. When I was a public servant, there was this really big contention between delivering on vendor polling or public polling versus user research. I think it's really important that public officials who are developing public legislation or public regulation actually test out these regulations with those who will be impacted by them. What I mean by this is that if you're going to put out a regulation that will impact the building of that within Canada, make sure it's constantly being tested and iterated upon with those who will be impacted by it—the end-users, as they would be called in product cycles.

Really, I think governments are no different. If anything, there is more pressure and obligation to ensure that the end-users understand how that's unfolding and how that's developing. As we're building these regulations or frameworks that would impact innovators, it's really incumbent upon us that forums are done in consultation and collaboration with the Canadian innovators who would be impacted by them.

[Kelly DeRidder, Conservative, Kitchener Centre, ON]

Thank you so much.

I'm going to focus a little bit on the hiring process and using AI as a tool.

I'm a woman in STEM, and I'm sure people automatically assumed—my name's Kelly—that I was a male because a female engineer in the industry.... Therefore, I would probably get interviews under the assumption that I was a male.

How could AI actually eliminate bias in the hiring process while there's a review of the résumés?

[Skaidra Puodžiūnas]

I think the pertinent framing is that AI is only as good as the people building it. I don't think we'll ever achieve 100% elimination of bias, but I think it's so important to be building the systems and thinking about the people who are engineering them. I think our AI companies will only be as strong as the talent we recruit into them.

I think that's what my colleague was really trying to emphasize in the beginning, that as we build these systems, we're thinking about the Canadian talent that's powering them—the Canadian insights, the Canadian perspectives, the Canadian innovation economy. Really thinking about that at the forefront as we're building them is absolutely integral.

[Daniel Perry]

This is an opportunity where we can develop standards to set the groundwork in that sandbox and the principles around it to be able to shape things when it comes to hiring practices like that. As Canada develops regulations and pieces like that, standards are the way to go.

I'm happy to expand on that in a future question.

[The Chair, Conservative, Dominique Vien]

Thank you very much, Mr. Perry.

Ms. Lambropoulos for six minutes.

[Emmanuella Lambropoulos, Liberal, Saint-Laurent, QC]

Thank you, Madam Chair.

I'll be sharing my time with Ms. Gladu.

Thank you to all our witnesses. This is incredibly interesting testimony. It's very new to me. I'm not going to pretend that I know much about this subject yet, but I'm happy to learn about it. Of course, we want to make sure that we include everybody going forward, and that everybody benefits equally from AI. We heard from all our witnesses that this is the goal here and that this is what we should have as a goal. The government plays a key role in that.

You spoke about procurement, Mr. Perry. You obviously work with many Canadian innovators in AI. I'm wondering what you believe the willingness is of these companies to actually work with government to make it safer for all Canadians and to make sure we're moving in the right direction.

[Daniel Perry]

Our members are very eager to work with government, whether that is through the procurement process or through consultation pieces like that. We were members of the minister's AI task force last November to have that conversation to make sure industry is heard. As my colleague Skaidra pointed out, as the government is thinking about AI and how to implement it, it is important to understand the end-user.

I like to point to the Ontario public service and its deal with Microsoft and Copilot. The number of individuals not using Copilot but instead using ChatGPT or other AI bots is 90%. Only 10% of people are actually using what the government has procured, because it doesn't fit their needs. As an Ontario citizen, it's very concerning that my data might be inside of someone's personal chatbot.

As the government is thinking about procuring pieces, they need to understand the end-user, as Skaidra said, but they also need to know where the data is stored and how it is being used. That's where Canadian sovereignty comes into the conversation. In credit to the government, there have been lots of conversations about that. It's something we need to continue to drill down on.

[Emmanuella Lambropoulos, Liberal, Saint-Laurent, QC]

Thank you.

Ms. Kubicek and Ms. Flood, you both spoke about inequities and about the fact that women are often left behind. They need to be part of creating the AI in order to be included, as with, obviously, many diverse groups of people.

What role does the government play in ensuring that all these voices are at the table in order to make sure nobody is excluded and we're not deepening inequity?

[Indra Kubicek]

I can go first.

[Amy Flood]

Sure. Go for it.

[Indra Kubicek]

For us, it really starts with the government ensuring that young people are provided an opportunity to go into these career paths. That's through the education system as well as through interactions, getting to know industry and knowing where they could be of use to solve some of these problems.

To an earlier question, one of the things we've created is an AI learning lab. We actually bring industry members, young people from diverse backgrounds, an AI expert and university students into the same room to solve an AI use-case scenario problem. This is one of the main things missing for a lot of Canadians right now. They don't have responsible AI use cases in their industry available to them. Working with young people through those diverse backgrounds and bringing their ideas into the room can help design and co-design with industry a solution that they could actually implement.

We see that the government can really provide funding and support to programs like that as well as work with industry to encourage them to focus more on the long-term value of their employees through investing in them to know how to adopt these solutions and build them responsibly. Ultimately, the company will be the one to bear the impact if they're not building solutions for all Canadians.

[Emmanuella Lambropoulos, Liberal, Saint-Laurent, QC]

Ms. Flood, would you like to chime in before I pass the floor to Ms. Gladu?

[Amy Flood]

I absolutely would. Thank you for the opportunity.

I would say two things. First, I think the ask of the government would be to invest in a national sex-, gender- and diversity-disaggregated data strategy. We can't build equitable AI systems using data that fails to adequately represent women. Tangibly, if you look at that from an economic perspective, there is a huge commercialization opportunity that stems from it. Currently, we cannot conduct clinical research trials in Canada within women's health because we don't have the infrastructure or the systems. That's a huge opportunity for us to work with major global and Canadian pharmaceutical companies to test their products, services and systems here.

Secondly, there's a huge innovation white space opportunity that comes from being able to study women, sex and gender-diverse populations. Think of the femtech industry as well. It's a $5.6-billion-a-year opportunity for Canada, but we can't develop and support femtech economic strategies and sustainable systems without the data to feed them properly.

I would say invest in women-led AI innovation, research and commercialization. Not only must women be the subjects of AI systems. They also need to be leaders in designing, governing and benefiting from them.

[Emmanuella Lambropoulos, Liberal, Saint-Laurent, QC]

Thank you so much.

[Marilyn Gladu, Liberal, Sarnia—Lambton—Bkejwanong, ON]

Briefly, my question has to do with the education of people on AI. I'm pretty convinced that younger people are getting more education and training. They're using the tools more. I'm really worried, especially, about women who are out of the school system.

How can the government get at that population, which I think will be really left behind both in the way that AI is created and because of the fact that they're not getting trained?

[Indra Kubicek]

We realize that young people are using this in real time, having not had a lot of formal education. That's just the reality that these tools are available—

[The Chair, Conservative, Dominique Vien]

I'm terribly sorry, but the time allotted to the Liberal Party has expired.

Good morning, Ms. Larouche. You have six minutes.

[Andréanne Larouche, Bloc, Shefford, QC]

Thank you, Madam Chair.

I want to thank the witnesses for coming to speak with us today as part of our study. We're seeing more and more media coverage about the impact of AI. We're going to try to take a closer look at what this actually means for women.

Ms. Kubicek, briefly, do you want to add anything on the issue of education for individuals who are no longer in the school system?

I have another question for you, but I'll let you conclude your answer to my colleague's question, if you can do so in 15 seconds or less.

[Indra Kubicek]

Very quickly, I think we need to decentralize community-based learning spaces for people to get access to this free education outside of traditional education systems, to answer the last question.

[Andréanne Larouche, Bloc, Shefford, QC]

Perfect.

You said that Canada could be a leader, and that the issue of the disproportionate impact of artificial intelligence on certain groups in particular raised concerns at the UN.

I'm a member of the Canadian Group of the Inter-Parliamentary Union for my party, the Bloc Québécois. I have participated in a few missions with parliamentarians from around the world.

My first question might be a bit broad. I'm not sure how you're going to answer it. We can certainly talk about regulations here and what we can do here, but we realize that, when it comes to AI, we're going to need to take a much more global approach, because borders don't stop AI.

What's your response to that?

[Indra Kubicek]

For Canada to fully succeed in any of this, we need to work with our other middle-power partners, and that work is starting to happen already. The way we do that is by building programs with youth that can be shared internationally and developed with other young people in other countries.

For example, one of the biggest issues facing young people today is free access to chatbots, and they're using them in their social and personal lives. We just built a program with the Canadian Commission for UNESCO, working with young influencers to push this AI literacy out on social media. We took it to the UN in Paris so that we can also bring this in and work with other countries to get the word out on awareness through young people and with young people. That's one of the ways we're addressing it.

Absolutely, we can't do it alone, because a lot of the content, access, information and decisions young people are making through AI tools are not primarily and only in Canada.

[Andréanne Larouche, Bloc, Shefford, QC]

Thank you very much. That's very interesting.

I'm going to try to get to each witness.

I'll now turn to the two of you, Mr. Perry and Ms. Puodžiūnas. In your opening remarks, you spoke about the importance of bringing together the various stakeholders to discuss AI.

Do you want to tell us a bit more about that, Mr. Perry? Specifically, which stakeholders absolutely must be brought together? Furthermore, what issues should they focus on together, and in what context?

[Daniel Perry]

Thank you for the question.

Given the technical nature of the question, I will respond in English.

When it comes to stakeholders at the table, it's important to have industry there, especially the ones looking at this every day, because they understand what is working and what is not working. That is the benefit of CCI's membership. All of our members are founded here. They're mined and managed here. They are truly Canadian companies through and through. If we're talking about what will be impacting Canadians, who better to ask than the ones who are building their companies here—the employers in our communities, in your ridings and across Canada?

Canada was a founder of AI. We have a natural advantage, whether that's in our critical minerals or our education system. However, we've seen this story before. We were founders of Ozempic, and now it powers the Danish economy. The question we need to ask here is this: How can we be a part of it but also make sure we're keeping the companies here and growing them so they can be the BlackBerrys of the world and support innovation here?

[Andréanne Larouche, Bloc, Shefford, QC]

Ms. Puodžiūnas, I'll continue my questions with you.

You said eliminating bias was impossible. So, we're starting from the premise that AI has gender bias. We know that, in Montreal, there have been demonstrations showing that AI has racial bias. We've seen clear examples of these biases. Could you tell us a little more about the exact nature of gender bias in AI? Why did you say it would be impossible to eliminate?

Maybe I misunderstood what you said. Could you clarify this for me?

[Skaidra Puodžiūnas]

I said that in the spirit of illustrating the importance, again, of the fact that these systems are being built by humans, and humans, of course, have bias. Therefore, the systems we build are going to be as biased as the data we power them with.

Again, there's such an opportunity to ensure that we are building these systems with the localized perspective of domestic innovators—of the Canadians who will ultimately be using them—in order to ensure that they have a Canadian perspective and a Canadian lens on them.

That was the point I really wanted to illustrate in my commentary on that.

[Andréanne Larouche, Bloc, Shefford, QC]

Perfect.

I have 30 seconds remaining, so I will quickly conclude with you, Ms. Flood.

You said that responsible and inclusive intelligence requires investment. In just a few seconds—we can come back to this during the next round of questions—could you tell us what such investments should prioritize?

[Amy Flood]

I recommend prioritizing a national sex-, gender- and diversity-disaggregated data strategy.

[The Chair, Conservative, Dominique Vien]

That's all you have time for. Perfect timing. Thank you very much.

We will now begin our second round of questions.

Ms. Borrelli, you have the floor.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

Thank you, Madam Chair.

Can you tell the committee more about why the Council of Canadian Innovators favours a standards-based approach to AI governance, and how standards can help reduce bias and discrimination in AI systems?

[Daniel Perry]

That is a great question, and it is one we talk about in our AI consultation paper.

The reality is that legislation moves slowly. We have seen privacy legislation attempted three times now, and online harms legislation twice. In that time, AI has changed. Even as I'm talking now, AI will be a little different by the time I finish this sentence. That's the challenge of legislation. It does not move at the pace of industry.

That's where standards can help. Standards provide that baseline, but they also signal to companies where the government's intentions are. This is at the heart of why we're calling for standards. They are the best way to govern this. As we're building the plane, they would give us the runway and the guidance to move forward on it in ways legislation would not.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

How can the federal government help Canadian AI companies grow while making sure AI works for all Canadians?

[Daniel Perry]

Procurement is the easiest way to do that. Invest in our companies through government contracts. That is how we're able to grow them, and that's also how the government can be part of the conversation. Set out what we need so we can build it specifically for the government.

As my colleagues have mentioned regarding health data, for instance, we don't provide that to our innovators. We provide it to some research institutions but not to business. When we are building our AI datasets in the health care system, they're being built on U.S. or European data. Their health concerns are very different from our health concerns. We need good information and good datasets. That is one way to do it. Provide that. That's something the federal government can do, and we would encourage them to.

That was in one of our recommendations to the minister's AI task force as well.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

Thank you.

To what extent are AI developers responsible for identifying, preventing and addressing biases and discrimination in AI systems during the programming stages and development process?

[Daniel Perry]

I think my colleague might be a little bit better suited for that.

Our view is that the developers should be responsible for explaining how it was made and how it was put together. The deployers, the companies, are responsible for discussing how it is being used, what data is being used on it, how it's being trained and whether a human is involved.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

Indra, do you have any comments in that regard?

[Indra Kubicek]

It's not exactly my background, but I would agree with that. There needs to be an onus on the developer to develop it responsibly so that it's going to work ethically in the way people want. On how it's deployed now that it's in the company's hands and how they're training their users and their employees, they also have to own some of that responsibility if that's where the error or the flaws occur.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

Are there examples of countries that are leading in the development and implementation of AI technologies while maintaining the effective regulatory frameworks that ensure AI systems are safe and do not discriminate against marginalized communities?

Skaidra, do you have...?

[Skaidra Puodžiūnas]

From our perspective, we've been seeing a lot of inspiration from the U.K. government as well as Australia, particularly looking at it through a Commonwealth lens. There is a real move to incorporate more of an MOU approach. Instead of adding yet another regulatory body or another regulatory legislative piece that, again, will take years to pass, there's a real horizontality that we're seeing in some of these models. From an innovator perspective, that's a really important approach, because innovation moves horizontally. It's thinking about different contexts and different use cases.

If our legislative vehicles can look at it from that perspective, connect those dots and perhaps be better wayfinders for innovators navigating our Westminster model, approaches like looking at the Australian and U.K. governments and some of the approaches they've been taking would be a good model for that.

Of course, I am not being very specific, so I will give some concrete examples to the committee after this, but these are two countries that we're looking at for inspiration.

[Kathy Borrelli, Conservative, Windsor—Tecumseh—Lakeshore, ON]

Thanks very much.

Thank you, Madam Chair.

[The Chair, Conservative, Dominique Vien]

It's my pleasure.

We will now move to Ms. Marie‑Gabrielle Ménard.

Good morning and you have the floor for five minutes.

[Marie-Gabrielle Ménard, Liberal, Hochelaga—Rosemont-Est, QC]

Thank you, Madam Chair.

I'd like to thank all the witnesses for joining us today as we begin this important study. We already understand just how many avenues we will need to explore.

For the committee's benefit, I'd like to mention that Ms. Kubicek, whom I had the pleasure of meeting not long ago, was named Woman of the Year by the Montreal Council of Women in recognition of the integrity she demonstrates in her work.

Ms. Kubicek, thank you for joining us today.

I'd like to revisit a statement you made regarding the conditions we should keep in mind so that women—and especially young girls, perhaps even before the age of 12, as you suggested—can develop curiosity in and a commitment to AI. I'd like you to elaborate on this topic. What role can the government play?

When it comes to education, we're always trying to find our place. Since the delivery of education falls under provincial jurisdiction, how can the federal government help drive the process forward?

[Indra Kubicek]

To give a bit more on the kind of the work we do, we start with young people in elementary school under the age of 12 years old. They're usually eight or nine years old. Research shows that young girls in particular, if they're not given opportunity and not shown activities and things that relate to things they care about in their lives—particularly when we're talking about technology—are then most likely to think they're not smart enough and not good enough, and they don't see themselves in those pathways.

As well, as we know already, there are not many women role models and mentors for them to look up to, so we need to start that process with the very young. It is known that young girls tend to gravitate towards wanting to work on projects where they see themselves being able to have a social impact in their communities.

We have created a social innovation lab, where we bring young people together using the UN SDGs as a framework and have them think about what problem they see in their own community, or in Canada or in a larger community, where they'd want to solve the problem and how AI could help solve that problem in a responsible way. That piques their curiosity. As was mentioned, that's where everything starts. In fact, for all of us, if we look back in our lives, it's usually curiosity that drove us to do the things we do today. That is very important.

Yes, the government federally is not in charge of education per se, but we are funded partially by the federal government through the ministry for innovation, through Minister Joly's office at ISED. We have been funded in the past to help flow funds to not-for-profit and civil society organizations like ours, to work both in the education system but outside of education as well. We're very aware that some young people learn best in different settings, and they're not necessarily going to attach to the programs at school as the things they care about most.

To give an example of a data and AI project we did with young people, it was around sports and basketball. We went out onto the basketball court with young people instead of making them sit in a classroom behind a computer. We started to ask them questions about who they thought was going to win the game, and why they thought that. Suddenly they realized that they are data scientists and they know a lot of information. We built an AI model with them to figure out who was going to win the game.

I think there are a lot of creative ways for government to fund youth programs. Libraries are an incredible space, where we could have more of this kind of interactive hands-on learning, because that's how young people are really going to learn best. As well, we ran our first parent and youth event during the All In AI conference in Montreal a few weeks ago, to help build trust in the community, with parents alongside young people.

[Marie-Gabrielle Ménard, Liberal, Hochelaga—Rosemont-Est, QC]

I'll continue the discussion with you, Ms. Kubicek.

Once young girls are engaged in discovering or creating different tools with AI, what's the biggest shock for them? What are their greatest ambitions? Could you give us an overall idea of the situation?

[Indra Kubicek]

As I mentioned, usually when young girls are given this opportunity, they realize that they are able to solve problems for communities they care about. For example, some of the projects they've developed lead eventually into some of the things we're talking about in women's health. How did they use technology to help support different women? They talked about girls who were maybe feeling isolated and alone through social media.

All of this is what they're taking in. It's about how they could create more community for themselves. I think young girls really need to be in spaces where they feel confident, where they feel they can trust and ask questions and, again, where they can address the issues that matter most to them. That is what has unlocked their potential to feel that they could then go into a career.

[The Chair, Conservative, Dominique Vien]

Thank you.

That's all the time we have for Ms. Ménard's questions.

I'll now give the floor to Ms. Larouche for two and a half minutes.

[Andréanne Larouche, Bloc, Shefford, QC]

Thank you very much, Madam Chair.

I'd like to thank the witnesses again for joining us.

As Ms. Ménard mentioned, we're beginning a study that is far from over. I believe we'll have to continue discussing this societal issue for a long time to come—perhaps even for the rest of humanity.

I'd now like to address another topic: the rise of AI and, unfortunately, the whole issue of deepfakes. In fact, this was one of the considerations we had when we were planning this study. We know that deepfakes are a growing phenomenon, thanks to AI. Sometimes, deepfakes leave irreversible scars on the women who are victims of this phenomenon. That said, Bill C‑16 came into effect in July and criminalized deepfakes.

My questions will be directed first to you, Ms. Kubicek.

What are your thoughts on Bill C‑16, which led to the Protecting Victims Act, and what additions would you have made to it?

[Indra Kubicek]

What additions would I have made to the law?

[Andréanne Larouche, Bloc, Shefford, QC]

What would you have added to the bill to address the issue of deepfakes?

[Indra Kubicek]

I'm not as familiar with where they ended with the deepfakes. They said that it would be illegal to create a deepfake that was doing anything...mimicking a person in a dangerous and violent sexual way. Is that the gist of it?

I wasn't clear about the question for me. Was it what I think should be added to the law?

[Andréanne Larouche, Bloc, Shefford, QC]

Correct. What do you think of this legislation and what would you have added?

I think you responded by saying that it's not as big an issue for you since it has now been criminalized. Perhaps we can come back to this later.

Ms. Flood, what resources related to health care are available to women who are victims of AI deepfakes?

[Amy Flood]

I'm sorry, but I don't feel equipped to respond to this particular question at this time.

[Andréanne Larouche, Bloc, Shefford, QC]

That's fine.

I have 15 seconds remaining.

Mr. Perry, I see you nodding. What's happening with the issue of deepfakes? What other improvements could be made?

[The Chair, Conservative, Dominique Vien]

Unfortunately, there are only two seconds remaining. The question has been asked, so perhaps one of you will be able to respond to it later.

Mrs. Roberts, you have five minutes.

[Anna Roberts, Conservative, King—Vaughan, ON]

Thank you very much, Madam Chair.

Thank you to the witnesses.

My first question is for Indra. We're seeing more and more young people turn to artificial intelligence for answers, whether in school, at work or in their everyday lives. My concern is that we're raising a generation that may become increasingly dependent on technology rather than learning to think critically and solve problems themselves.

From your experience working in AI literacy, how do you ensure that young Canadians are using AI as a tool to support their thinking and not allowing it to do the thinking for them?

[Indra Kubicek]

That's a very good question. That is at the heart of all of our work and what we believe in. We need to be ensuring that young people are critical thinkers in this moment—actually, that all Canadians stay critical thinkers and that they use their own human judgment. In all of our programs, this is at the centre of what we're teaching: How do you think critically and not have AI replace your part in the thinking, which you want to keep, but also use it as a tool when it makes sense?

Again, as you mentioned, I think one of the biggest risks is that they're using this in their personal lives. They're asking social, personal questions about their relationships to AI chatbots, in isolation, on their own, at home.

We've created programming, as I mentioned, in partnership with the Canadian Commission for UNESCO, for example. We have young people—because research also shows that young teenagers tend to look up to people just a few years older than them—and we've worked with Canadian content creators in Canada to teach short AI literacy learning experiences through storytelling.

We had, for example, a young Canadian woman in Vancouver who talked about testing, asking a chatbot if she should break up with her boyfriend or not. She actually gave a scenario, and the chatbot told her to break up with her boyfriend. Then she gave the scenario from his view, and it was telling him not to break up with her. The point of the story is that she was trying to explain to young people, “Do not give up your human agency. Do not give up your free will and your own judgment and ask questions like this about your social life to a chatbot.”

Those are some of the creative ways we've been trying to address the problem in real time.

[Anna Roberts, Conservative, King—Vaughan, ON]

I'll tell you why I'm asking this question. It's important to me as well because I'm working on a bill right now that has been brought in front of the House. The education, for me, was speaking to the actual survivors and learning the true aspects of what they had gone through. I don't think AI can replace something like that. I guess that if I hadn't done that and had just used AI, I wouldn't have understood the complexity of the crime.

I don't want the human aspect to be removed. I think people have to understand that, yes, AI is the way of the future, but there's also the fact that compassion and understanding sometimes doesn't come from a computer.

[Indra Kubicek]

One hundred per cent, humans care. Computers do not care about you. This human-centred learning is exactly the kind of thing we're focusing on. What are the human skills that we need to build in this moment?

[Anna Roberts, Conservative, King—Vaughan, ON]

It's true.

I'm going to ask another question because this really concerns me. It's about health care. We heard this last week in our perimenopause study. There's more money funded for research into men's and other diseases as opposed to women's. How is this going to increase the opportunity to get more research done on women's diseases?

Ms. Flood, is it?

[Amy Flood]

Thank you. Yes, I will absolutely, happily, take that.

Yes, I agree 100%. As of now, only 7% of government and public funding goes to women-specific clinical health care and research. The ask right now is to build a national women's health data platform that will harmonize data across the country and give women a full picture of their health. That includes girls. It also includes gender-diverse populations.

Much to the topic you were talking about earlier, women are taking to AI, to social media and to Dr. Google daily to understand and diagnose their own health. Their health care practitioners are not even capable of doing that at present because there's no data; there is no information. That's where the opportunity and risk both lie.

If we can actually have the sex- and gender-disaggregated data that informs AI, we can model that and actually close the women's health gap in Canada. We really need investment and funding into more research.

[The Chair, Conservative, Dominique Vien]

Thank you, Ms. Flood.

Ms. Nguyen, you have five minutes.

[Chi Nguyen, Liberal, Spadina—Harbourfront, ON]

Thank you very much, Madam Chair.

Thank you very much to our witnesses for being here today. I think this is such an exciting and important study that we are taking on, and I'm grateful that you are the first experts we've heard from.

I want to start with Ms. Flood.

I know you didn't have a chance to wrap up your testimony at the start, and you were describing or starting to speak about how responsible AI can better protect and address systemic gaps in women's health. I was wondering if you could share some concrete examples. I'll give you about a minute and a half to wrap that up.

[Amy Flood]

Concrete examples, again, go back to filling that data gap. Right now, women's reproductive health is only 5% of the total picture. We're looking at cardiovascular health, cancer, mental brain disorder, chronic pelvic pain and, of course, that hormonal transition through the menopausal journey. All of these health conditions need addressing from a data and a research standpoint. Again, if we don't have the data because women were not included in clinical trials until 1997, then these conditions will continue to progress, and we'll actually use AI to accelerate the health of men and other populations while widening the gap for women in Canada.

We really need that AI innovation, research and commercialization strategy for Canada so that not only are we getting the data to inform diagnosis, treatment and care, but we can also further that economic potential for innovation in women's health. That's not just Apple watches and Oura rings. You're talking about keeping fetuses alive in utero. You're talking about diabetes. You're talking about cervical cancer cures. You're talking about prolonging people's lives through cardiovascular monitoring. These innovations are critical to the lives of women in Canada, and if we don't have the data, we will not be able to power that innovation.

[Chi Nguyen, Liberal, Spadina—Harbourfront, ON]

Thank you very much, Ms. Flood.

Ms. Kubicek, one of the interventions and pieces you were talking about was the role of supporting women entrepreneurs. I was wondering if you could speak to this and to whether or not some of the government interventions, or work that we could be doing, would allow and support women to become more competitive in technology spaces.

[Indra Kubicek]

Yes. I think one of the things that are known is that women entrepreneurs aren't necessarily technology companies. Women have many different SME businesses that they run as a sole proprietor or as a small business, so the kind of training they need may differ. They're already going to be starting from a later start because they're not running a technology company, compared to what we consider the “normal” kind of entrepreneur.

I think the government really does need to build programs in order to have them figure out how to improve their administrative processes. How can they not need to hire more people into the company if they're running it on their own? How can they market better? How can they find more customers? Those kinds of programs are not necessarily the same things as what we see with the start-up community entrepreneurs, who are in tech, scaling up an R and D technological company. I think that would be of real benefit, government funding programs like that.

[Chi Nguyen, Liberal, Spadina—Harbourfront, ON]

Thank you very much.

To the colleagues from CCI, I want to ask you this: Given your involvement in the AI council, trust is a component that's really critical, and I wonder whether you could speak to what that could look like. I know that I'm hearing from a lot of women who are not there yet in terms of trusting that AI can be serving good. I would love for you to talk about what that looks like and what you're seeing.

[Skaidra Puodžiūnas]

What we're seeing from our pan-Canadian innovator community is that the perspective they're building from is looking at their localized communities. Again, the innovation that they're building is reflective of the needs that their communities need.

One thing that Indra said, which I think really resonated for us, is this concept of decentralized community building, and I think that's exactly what innovators want. They want to be confronted with decentralized problems and outcomes-based opportunities. The more opportunity that innovators have, in the thick of a challenge that government presents, or the more articulated or accessible a problem is to an innovator, the more they'll find ways to tackle it and to solve it, because that's exactly what entrepreneurs do.

For Canadian innovators, it is about having greater exposure to the problems that are facing Canadian legislators and Canadian communities. I really just want to double down on the point of bringing them into the conversation and allowing them access to concrete datasets. I would also totally “plus one” what Amy was saying in terms of the right kinds of datasets. I think those are exactly the kinds of demands and opportunities that would help our innovators do a better job of innovating for communities.

[The Chair, Conservative, Dominique Vien]

Thank you very much, Ms. Puodžiūnas.

I'd like to thank all four of you for making yourselves available today to discuss this important issue with us.

I'll now adjourn the meeting for a few minutes so we can go in camera, and we'll resume immediately afterward.

Thank you very much.

The session is suspended.

[Proceedings continue in camera]