Human Resources Committee on Nov. 1st, 2023

[The Chair (Mr. Robert Morrissey (Egmont, Lib.)), Liberal, Bobby Morrissey]

I call this meeting to order.

Committee members, it being 4:30 p.m., the clerk has advised me that we have a quorum.

Witnesses and committee members who are appearing virtually have had their sound tested.

We are good to begin meeting number 86 of the House of Commons Standing Committee on Human Resources, Skills and Social Development and the Status of Persons with Disabilities.

Pursuant to Standing Order 108(2), the committee is beginning its study on the implications of artificial intelligence technologies for the Canadian labour force. Today's meeting is taking place in a hybrid format pursuant to the Standing Orders. Committee members are attending in person as well as virtually.

You have the option to speak in the official language of your choice. In the room, the interpretation is available using your headset. Virtually, at the bottom of your screen you will have a globe icon. Click on it and it will give you the option to speak in the official language of your choice.

If there is an interruption in translation services, please get my attention. Those who are attending virtually, use the “raise hand” icon and I will suspend while it is being corrected. I would also ask committee members and witnesses to speak slowly for the benefit of the translation team.

For those in the room, if you could keep your earpiece away from the mike to prevent popping and possible hearing damage to the translators, it would be appreciated.

Please direct all comments through the chair and wait until I recognize you. As well, when we get the witnesses, please indicate who you're directing your questions to.

As you're aware, because we had a couple drop out today, there's one panel for an hour and a half.

From the Canadian Labour Congress we have Chris Roberts, national director, who is with us in the room.

From the Council of Canadian Innovators we have Laurent Carbonneau, who is in the room.

From the Organisation for Economic Co-operation and Development, appearing virtually from France, we have Marguerita Lane.

Welcome, madam.

From Statistics Canada, we have Vincent Dale and Marc Frenette.

Because of the timeline, I'm going to ask Ms. Lane to begin with her opening statement, and then we will go through the rest of the witnesses.

Ms. Lane, you have the floor for five minutes or less, please.

[Marguerita Lane, Economist, Organisation for Economic Co-operation and Development]

Thank you for being so accommodating with the timing.

I'm an economist in the future of work unit at the OECD. I'm going to use my five minutes to describe, first, what I think makes AI different from previous technologies; second, what impact AI is already having on the labour market; and third, where policy makers should really be focusing their efforts.

First, on what makes AI different from previous technologies, from a labour market perspective, I think we can all agree that the sheer speed and scale of progress is quite interesting. Because AI can essentially learn and iterate, and because it has applications in practically every industry and practically every occupation, I think that in 20 or 30 years, AI will be so deeply embedded in our society and in our work that it will be difficult to imagine life or work before it. We can think of it in the same league as technologies like the Internet or electricity. Unlike previous technologies, AI can perform non-routine cognitive tasks, which means that many high-skill occupations, for instance engineers and scientists, are particularly exposed to AI. These are jobs that have been traditionally more sheltered from automation. They did things that technology couldn't.

I'm not saying that these occupations will disappear, but certainly I think these occupations will be transformed by AI. That's something interesting about this technology.

Of particular interest about AI as well are the many applications it has in hiring and management. This brings new opportunities but also new challenges to the work environment.

I'll now move to the impact on the labour market, which the OECD has been assessing through its own data-collection exercises. We tend to see things through the framework of job quantity, job quality and inclusiveness.

In terms of job quantity, we don’t really see big signs that AI has impacted aggregate employment, at least not so far. When economists have done empirical studies looking at aggregate employment statistics, there's not really any strong evidence of mass displacement due to AI.

In a survey that the OECD conducted last year, which Canada actually participated in, over half of the firms that use AI—that we talked to—told us that it had had no impact on employment in their firms. Among those who reported that there was a change, they were relatively evenly split between those saying that AI had increased employment and those saying that AI had decreased employment.

Why is it that AI doesn't seem to have had a massive effect on employment, or hasn't reduced employment? Firms told us that AI mostly tends to automate tasks, rather than jobs. They tell us that the AI just isn’t quite there yet.

Where AI does automate a job, firms said that they tend to manage this through reallocating workers to other business areas, through relying on slowing hiring, and through attrition and retirement.

Taking all of this together with the fact that employment levels are currently high in most OECD countries, and given what we expect to see in terms of an aging population in many OECD countries as well in the next couple of decades, I don't think that we are so concerned that AI is leading to the end of work. However, I think there is certainly a lot of potential for disruption as workers have to adapt to changing skill needs.

The same OECD survey found positive results for job quality, but also some risks. Workers who use AI were overwhelmingly positive about its impact on, for example, job satisfaction and health and safety. A large part of this, I think, is that AI tends to automate a lot of dangerous and tedious tasks. Also, workers told us that they appreciated when AI assisted them in decision-making as well.

At the same time, most workers who use AI said that AI increased the pace at which they work. Now, this could be AI enhancing their productivity, which I guess would be, in a way, logical. At the same time, we know that increased work intensity can also induce psychosocial risks such as increased stress and anxiety.

Many workers also expressed concern that data collection in the workplace could infringe upon their privacy and lead to decisions biased against them. Many workers supported banning or restricting the use of AI in processes around the hiring and firing of workers.

Then there are some implications for inclusiveness too. Even if it is the case that the highly skilled workers are more exposed to AI than they were to technologies of the past, I think it still remains a big concern whether those with lower skills have the ability and the resources to adapt.

These people might be in more precarious positions. They may have less bargaining power, and they may find it more difficult to re-skill or upskill.

When the OECD—

[The Chair, Liberal, Bobby Morrissey]

Ms. Lane, could you conclude your comments? You can deal with what you missed in answering questions. If you could, just shortly wrap up.

[Marguerita Lane]

That's perfect.

There is obviously a need for policy-makers to act. In some cases, that can be done through existing legislation—for example, the legislation on discrimination, rights to organize and so on—but, obviously, other countries are developing AI-specific legislation and soft law. Training and worker consultation will be extremely important, and of course we need good evidence to track developments in this area, which the OECD will continue working on.

Thank you.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Ms. Lane.

Mr. Roberts is next, for five minutes, please.

[Chris Roberts, National Director, Social and Economic Policy Department, Canadian Labour Congress]

Greetings, Chair and committee members. Thank you for the opportunity to appear here today.

I want to begin by commending the committee for initiating this very important study. The impact of AI on work and employment is increasingly the focus of the attention of unions in Canada.

In 2022, the CLC formed a task force on AI and automation, comprised of unions from the public and private sector and a range of industries and occupations.

When asked, many workers report being optimistic about the potential of AI applications to improve and enrich work. It could do this by automating simple, repetitive tasks, allowing more time and attention to be devoted to non-routine, creative and skill-intensive tasks. This aligns with the OECD research finding that workers report improved performance and even improved job satisfaction following the introduction of AI applications in their work.

It also fits with the view that, as with many new technologies, AI has no intrinsic implications for the quality of work and employment. Technology is shaped by the social structures and power relations within which it is designed, developed and adopted. What matters are the choices we make about the direction of AI research and how AI is developed and deployed.

In the words of one economist, “AI can be a powerful tool for deploying the creativity, judgment, and flexibility of humans rather than simply automating their jobs”, but AI also has the capacity to reinforce existing inequities of income, wealth and power, aggravating the discrimination, exclusion and insecurity that many vulnerable workers face, undermining the privacy rights of workers as producers and consumers, and creating risks of individual and societal harms.

Many workers raise concerns about displacement and job loss. As AI automates not only routine but also non-routine cognitive tasks, the potential for job displacement will rise. Automation has historically had the greatest impact on low-skilled and semi-skilled jobs, but workers in high-skilled occupations now find themselves vulnerable to AI-driven displacement.

In addition to job loss, a significant concern is the potential for discrimination; monitoring surveillance at work; a weakening of privacy rights around the extraction, use and sharing of personal information; and the potential for individual labour and human rights violations. AI deployed in the human resource management functions of hiring, performance evaluation, promotion, discipline and termination is a particular source of worry.

Already, gig workers working for digital platforms struggle with unaccountable algorithmic management and arbitrary deactivations.

Facial and voice recognition technology deployed in workplaces like airports and technologies that monitor and collect information on workers' physical health are troubling.

Workers in marine ports already struggle with unfair and arbitrary decisions around security clearances. Automated decision-making that deploys pattern recognition algorithms could make these decisions even more unjust and arbitrary.

Finally, creative sector workers and those in the performing arts are worried about retaining control over their names, images and likenesses and ensuring fair compensation for their work.

Canada’s unions have one overriding message for policy-makers on AI: As employers deploy AI systems, workers want greater transparency, information sharing, consultation and participation. They want the right to be informed, to be consulted and to participate in the process, and they want access to training and labour adjustment.

Our recommendations to the government include the following. The government should outline a vision and road map for appropriate regulation of AI development and adoption in workplaces. This should include a strategy for ensuring a voice for workers and unions in the regulation and oversight of AI.

It starts with a representative advisory council on AI. This would be able not only to make recommendations about emerging areas of concern for policy-makers but also to identify research gaps, data and research needs and strategies for disseminating this research. Right now, workers have relatively limited rights to be informed, to have access to training and to be involved in the introduction of new technologies.

Access to vocational education and training is highly uneven in Canada, and labour adjustment is comparatively weak.

Chair, I see that my time has come to an end. I will leave my recommendations there and hopefully follow up in the Q and A period.

Thank you.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Mr. Roberts.

Please proceed, Mr. Carbonneau.

[Laurent Carbonneau, Director, Policy and Research, Council of Canadian Innovators]

Good afternoon, Mr. Chair and members of the committee. Thank you for the invitation. I'm very grateful for the opportunity to discuss AI policy issues with you here today.

My name is Laurent Carbonneau. I'm here today as the director of policy and research at the Council of Canadian Innovators, or CCI.

CCI is a national business council representing 150 of Canada's leading technology companies. We are dedicated to advocating for policies that promote innovation, economic growth and long-term prosperity for all Canadians. Our member companies are all headquartered here in Canada. They employ north of 52,000 employees across the country and are market leaders in the sectors of health, clean and financial technologies, cybersecurity, and of course AI.

AI will be a defining challenge of our time for policy-makers. A new, genuinely general-purpose family of technologies like AI could well have impacts on the world of work and the economy like those created by industrialization and electrification. I'll stress here that those transitions posed profoundly difficult policy challenges to governments, challenges that many were not able to meet equitably. It is good that this issue is getting active parliamentary scrutiny.

With that said, I think it is very premature to worry about things like large-scale job losses. Canadian businesses as a whole are facing the opposite problem—low productivity and an immense appetite for more labour. This is not normal for advanced economies. We should take a quick look under the hood of Canada's overall economic picture.

In terms of productivity—GDP per hour worked, by one measure—we recently clocked in under the OECD average, just behind Italy and just ahead of Turkey and Spain. We look much worse than they do on measures of work-life balance, where we're tied at 30th with the United States for leisure time, once again below the OECD average. Our net income, which counts taxes paid and services like health care received, has us 13th in the world, behind rich countries like the U.S. but also behind small economies like Belgium.

Canadians are working a lot to earn modest incomes even after accounting for services like health care and education. According to recent Statistics Canada data, productivity has actually just dipped below where it was at the same point in 2018. There's been no growth over the last five years. There's no getting around the fact that addressing the big challenges of our time—poverty, climate change and reconciliation, to name a few—requires us to be a richer and more productive country than we are now, and to do more with the same or fewer resources.

AI is fundamentally a family of technologies that makes both labour and capital inputs more efficient. Research, development, commercialization and adoption of AI collectively present an important opportunity for Canada to correct our worrying economic trajectory. We should work to make it a priority to adopt AI technologies that make our businesses more efficient and our economy better off overall.

What is important to understand about the economics of AI is that while AI is a novel technology, it does not defy the general way in which the economics of innovations work. Companies that are commercializing new innovations, particularly in information technology, succeed because they own intangible assets like patents that exclude rivals, they control vast amounts of data, and they leverage network effects to make their products and services more useful to users. Because of those fundamental drivers of success, today's innovation economy is characterized by superstar firms equipped with the IP assets, data and networks they need to fend off competitors.

AI is a heavily IP- and data-dependent business. The successful AI-driven businesses of the near future will replicate that winner-take-most pattern. Policy-makers focused on creating lasting and inclusive prosperity should prioritize growing Canadian competitors into global champions and leveraging their success into broad-based gains for the country.

The broad AI sector is currently valued at around $200 billion, and by 2030 will likely expand to around $2 trillion. Canada is well positioned in the industry in terms of highly qualified personnel and leading research, but Canadian companies face significant barriers while scaling. A lack of scaling Canadian companies means that many of the benefits created from public investment and research and training, including intellectual property, are accruing to firms outside of Canada.

For example, nearly 75% of intellectual property rights, including patents, generated through the federal government's pan-Canadian AI strategy are owned by foreign entities, including American tech giants like Uber, Meta and Alphabet.

The Scale AI global innovation cluster recently published a report that identifies barriers to adoption for Canadian companies. Companies face serious issues of access to top talent, despite our impressive research strength, because of lower wages compared with American competitors, among other issues. Canada's AI talent pool has actually shrunk by nearly 20% over the last three years. This is showing up in low rates of adoption: 48% of Canadian companies report not using AI compared with below 36% in the U.S., 38% in the U.K., and nearly 39% in France.

It's still unclear what AI will mean for the future of work and broad employment patterns, but one thing that is most immediately clear is that in a potentially era-defining niche in a winner-take-most sector, Canada cannot afford to move into the future as a late adopter of AI with little domestic capacity. That is a recipe for stagnation. Canada's innovators want to build the next generation of global AI players here in Canada.

I look forward to your questions.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Mr. Carbonneau.

Now, from Statistics Canada, we have Mr. Frenette or Mr. Dale for five minutes.

[Marc Frenette, Research Economist, Statistics Canada]

Mr. Chair, committee members, thank you for inviting us to this meeting. We're pleased to be able to inform you around discussions of the implications of artificial intelligence for the Canadian labour force.

Rapidly advancing technologies can perform some of the work humans do. Automation that is ruled-based and follows predetermined instructions has been capable of executing routine or manual work tasks for some time. More recently, significant advances in artificial intelligence, or AI, which makes predictions based on data, somewhat like humans do, have created new concerns for workers involved in cognitive or non-routine work.

Generally speaking, technology can have pros and cons for workers. Some workers can have their jobs transformed by it or even be completely replaced. On the other hand, technology can potentially boost productivity as workers focus on higher-level tasks that are better rewarded in the labour market, while robots and computer algorithms handle the more repetitive tasks.

More productive workers could help Canadian businesses become more competitive in global markets, which could improve standards of living for Canadians through job creation and increased wages.

Our data suggests that so far, technology adoption does not appear to be associated with widespread job losses, but it does appear to be associated with job transformation. Indeed, between 1987 and 2019, just before the COVID-19 pandemic, Canadian jobs were slowly moving away from routine manual tasks towards non-routine cognitive tasks. This is perhaps expected, as manufacturing and other industries implemented automated technologies to perform repetitive tasks, although other factors, such as increasing international trade, may have also played a role.

The reasons these trends were gradual despite significant developments in both automation and artificial intelligence are unknown. However, some of the possible factors that may have slowed the adoption of the more advanced technologies include the high investment cost required to implement the technology, regulations, and societal resistance to public-facing technologies such as self-driving cars or robotic doctors.

The COVID-19 pandemic may have accelerated the trends in job tasks seen earlier by giving an incentive to firms to invest in automated technologies and AI, allowing them to make their production and delivery processes more resilient to possible future shutdowns. Other factors could have played a role in accelerating these past trends, such as increased demand for goods and services produced by knowledge workers.

The data confirmed that since the onset of the COVID-19 pandemic, notable changes have been registered in the nature of work that Canadians do. For example, the share of workers in managerial, professional and technical jobs, which largely involve non-routine, cognitive work, increased from 32.3% in 2019 to 36.0% in 2022.

This increase over a short, three-year period accounted for almost one-third of the total increase registered over the last 35 years. The increase in recent years was counterbalanced by declines in the share of workers in service jobs, which went down from 21.3% in 2019 to 19.2% of all jobs in 2022, and in production, craft and operative jobs, which went down from 21.8% in 2019 to 20.5% in 2022.

All of these trends were largely similar for both men and women.

The increase in managerial, professional and technical occupations and the decline in service occupations were considerably more pronounced during the pandemic among younger workers aged 25 to 34 years compared with older workers aged 45 to 54 years. This may not be very surprising, as younger workers generally have fewer family obligations and more years to recoup their investments if they choose to retrain for a new career.

In any event, the more pronounced trend among younger workers may be indicative of future trends as older workers leave the labour force, making room for younger workers who are more amenable to taking on modern jobs.

Following the COVID-19 pandemic, another factor that could affect these trends is the very recent and rapid significant developments in artificial intelligence, like large language models such as ChatGPT, for example. Unlike previous technological developments, the implementation of advanced AI could potentially lead to significant job transformation among workers performing cognitive tasks, given the capabilities of this technology.

Whether or not this will occur is difficult to predict at this time, but may depend on the presence or absence of previous constraints facing AI adoption—namely, high investment costs, regulations and societal resistance, as I noted earlier.

Statistics Canada will continue to monitor and report important developments in these trends based on timely labour force survey data. Census data could also help establish trends for demographic groups of workers who may face particularly high risks.

Mr. Chair, this concludes my opening statement. We would now be happy to answer your questions.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Mr. Frenette.

Before we begin the questioning round, I just want to advise panellists that Ms. Lane may have to leave before we conclude, as it is nearing 11:00 p.m. where she is. If you have questions for her, I just want to advise you that she may be leaving.

We will begin with Madam Ferreri for six minutes.

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

Thank you, Mr. Chair, and thank you to all of our witnesses. It's very interesting and informative testimony that I hope we get in writing, too, with lots of stats coming out from you guys.

Ms. Lane, I will start with you.

I think one of the things that folks watching at home, and even ourselves here as members of Parliament, want to know is what is defining AI? What does that look like for you? What is your definition? Is it the self-checkout at the department stores? What is the definition of AI from a workplace perspective?

[The Chair, Liberal, Bobby Morrissey]

Ms. Lane, you may be on mute.

[Marguerita Lane]

We tend to define AI as a computer system, essentially, that can enable machines or programs to do tasks that would typically require human intelligence.

One thing that is complicated in this area is that even AI developers, experts in AI, will actually disagree on what AI is. They will give you different definitions of AI so, as you said, there are many technologies that may or may not be considered AI, depending on who you're talking to.

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

Do you think it would be beneficial to have a definition of what it is when you're looking at legislation, a clear definition? If so, who would be responsible for defining it?

[Marguerita Lane]

I think it does have to be defined within the legislation, and, for example, I know the European Union has struggled with this, with exactly how to define it. I think the definition they chose certainly attracted some commentary. I have to say, though, I wouldn't be in a position to advise on exactly how to define AI.

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

Thank you for that, and thanks for your feedback.

Do you think that self-checkouts—I'll just say at a department store or a grocery store—are considered AI?

[Marguerita Lane]

I think they generally wouldn't be considered AI, because, typically, they are scanning a bar code. However, I would say that if you were in, for example, an Amazon warehouse and there was a machine, for example, doing a visual scan of a product and identifying that product, that generally would be considered as AI. Even when two different technologies essentially do a very similar thing, one might fall within the definition of AI and the other one might not, actually.

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

Thank you, yes. It's pretty hard to even critique it when there's not a definition of what it is. I think, sometimes, that seems to be a bit of an issue.

If I can jump to you, Mr. Carbonneau, thank you for your testimony; there were a lot of stats and interesting insights that you provided to the committee. I like your foresight of where Canada can be versus where Canada is. I was hoping you could expand on that a little. If you think Canada doesn't jump on this inevitable technology that is here—as we say, the toothpaste is out of the tube; the horse is out of the barn—where do you think that will place Canada if we are not competitive in this market?

[Laurent Carbonneau]

I'll point, once again, to the really excellent report that the Scale AI global innovation cluster put together, which does talk a bit about this. The report says that we're at a point right now where they see us as having some start-up strength and really good research capacity, but the reality is that we may end up not having much of an industry here because our scale-up companies are not able to scale because of the various barriers that they face, both technological and broader, in terms of innovation policy that enables the growth of innovative Canadian companies.

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

Can you expand on those barriers? What, right now, is preventing Canadian companies from really sinking their teeth into benefiting from AI?

[Laurent Carbonneau]

I mentioned labour, which is a significant one. Companies are having trouble finding people with the right skill sets. I mentioned that we have good researchers, but lots of those researchers end up going to work for the Googles, etc., of the world, which are able to pay much higher wages—with better weather, it should be said, in many cases.

That's wonderful for them, obviously, and wonderful for the people who get those jobs, but it's probably not great for Canada as a whole. We should be finding ways to help enable companies to make things attractive enough for people to stay. That's one piece.

Other than that, to some extent it's uptake. It's customers and markets. Right at the very beginning these companies have to be global, because the Canadian market is just not big enough on its own to really act as rocket fuel for these companies to grow. That's another one.

I think this—

[Michelle Ferreri, Conservative, Peterborough—Kawartha, ON]

I think I have only 20 seconds left, so I'm sorry.

I just want to jump back to Ms. Lane, if I can, because I know she has to leave.

How are you deciding who to survey? You gave lots of results on companies that you've asked for feedback from around AI, but how are you deciding who you ask, especially if there isn't a defined definition of what AI is?

[Marguerita Lane]

That is a good question.

We talk to firms and workers within the manufacturing and financial industries, so that obviously already steers the conversation towards industries where the use of AI is more prevalent and a bit more mature as well. We talk to firms that are using AI and also those that aren't using AI, so a mix of firms essentially.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Ms. Ferreri.

Mr. Coteau, you have six minutes.