Typically when you look at the impact of technology on industry, for example, we look at, let's say, impact on income. We also see it on, like you said, unemployment, job loss and whatnot. Those are very blunt instruments. Is that correct, in your opinion?

That doesn't paint the full picture of the impact of AI on the workplace. Is that correct?

5:45 p.m.

Professor, Department of Informatics and Networked Systems, University of Pittsburgh, As an Individual

Morgan Frank

Yes, absolutely not. In the U.S. context, at least, I can show that there are changes in the probability of receiving unemployment or shifts in job separation rates, at least in terms of estimates from my research, that aren't very correlated with changes in the employment share for an occupation within a state.

I think there is evidence to show that looking at shifts in employment and shifts in wages is missing out on other dynamics that can occur and, in particular, the specifically negative dynamics that we're most worried about with AI.

5:45 p.m.

Liberal

Irek Kusmierczyk Liberal Windsor—Tecumseh, ON

Thanks, Professor.

I have a question for Professor McKelvey.

We just completed a summit here, a caregiving summit, on Parliament Hill. In terms of caregiving, there are eight million Canadians who are caregivers. A lot of them are unpaid caregivers. We also have a large paid caregiving part of our economy. We're talking about nurses, PSWs, home care, child care and whatnot.

I wanted to ask you if you could talk about how AI might impact caregiving in Canada. If you're not able to speak about that in particular, what questions could we be asking to find out what the potential impact of AI is on caregiving in Canada?

5:50 p.m.

Prof. Fenwick McKelvey

Obviously this is not my area of expertise, but I will say that I have been pulled into some of these discussions because, in Montreal, there was a proposal to introduce a robot into a seniors' home as a way of taking care. That led me down a bit of an investigation into what the effect of this is.

The best place to look at as a parallel is Japan. I think there have been a lot of efforts in the automatization of caregiving in the Japan context, but it largely hasn't been effective, because many of these technologies cost as much to maintain as it would to actually properly resource the caregivers in place.

I think there's a kind of shifting of values, where, again, I think it's targeting the cultural impacts of artificial intelligence. They think the technology is going to do a better job than just paying a nurse or a caregiver properly for that function. I would say that, in anything I have seen, the benefits are overstated compared to the potential, and also that, really, this is something that has to fit within a larger holistic system of care that evaluates even the kinds of benefits—which I'm not saying there isn't—within making sure there are actually proper resources to support our fundamental frontline caregivers.

5:50 p.m.

Liberal

The Chair Liberal Bobby Morrissey

Thank you, Mr. Kusmierczyk.

We have Mrs. Falk for five minutes.

5:50 p.m.

Conservative

Rosemarie Falk Conservative Battlefords—Lloydminster, SK

Thank you very much, Chair.

I know that in the past this committee has done a study on precarious work. Precarious work is growing and actually quite prevalent.

I believe it was you, Professor McKelvey, who mentioned the word “precarious”, so I thought I would ask you this question: Do you think precarious work will become more prevalent, more common, when we see AI being developed or even maybe absorbed by business?

5:50 p.m.

Prof. Fenwick McKelvey

Acknowledging my poor powers of prediction, I can't draw a direct correlation between a rise in precarious work and artificial intelligence.

I would say that where we'll see a significant place, and where we want to attend to AI's impacts, is around precarious workers and gig workers, because we know that these are the workers that are already subject to algorithmic management, already subject to new forms of workplace surveillance and ultimately have complicated data arrangements with their platform providers, which are often trying to figure out ways of managing them.

The other part, I would say, is that if we're looking at a shift towards more hybrid environments and changing ways that organizations are being designed, there is certainly I think a push towards trying to create more services that are on demand and that invite, potentially, a kind of precarious relationship because of the type of gig worker. I feel as though what's partially at risk here is that the way shifting platforms are also reorganizing how workforces are taking place could give rise to more plug-and-play types of jobs. That would be something that doesn't have the same risk, because largely you would be contractors.

5:50 p.m.

Conservative

Rosemarie Falk Conservative Battlefords—Lloydminster, SK

Would you say that legislators should take into consideration precarious workers specifically?

5:55 p.m.

Prof. Fenwick McKelvey

Yes. Definitely. I'd commented earlier on asymmetrical bargaining power. If you're looking at online social media platforms, you have real data imbalances there. We have mounds of evidence about workers trying to make content creators online subject to how platforms change their data analytics and how the platform works. Really, that demonstrates a way that the workplace is very tangibly precarious, because their popular solutions can change overnight.

I think that speaks to evidence of a growing part of the workforce but also the lived impacts of what that looks like. If you're dealing with a company that is moving towards more dynamic forms of management through emerging AI strategies, that certainly creates conditions of precarity.

5:55 p.m.

Conservative

Rosemarie Falk Conservative Battlefords—Lloydminster, SK

Thank you.

I know that we have heard at this committee—and for sure I have in my office as a member of Parliament, as I'm sure all members of Parliament have—about how there is a labour shortage in every single industry sector in Canada. It doesn't matter what it is—they need people and they can't find people.

Just quickly from both of you, because I'm running out of time, do you believe there will be industries that will be more prone to job displacement when it comes to AI? As well, how can industries prepare for that?

5:55 p.m.

Professor, Department of Informatics and Networked Systems, University of Pittsburgh, As an Individual

Morgan Frank

I'm happy to go first.

Yes, I think the impact of generative AI and any other technology will be biased towards certain industries. It's not just a blanket impact across the whole economy usually. In the case of generative AI, I imagine that we'll see a lot of advances that are a boon for workers and a boon for capital in tech, but we'll also see new opportunities as a consequence of these new tools that are not necessarily involved in development, such as in the areas of medicine, communications and media.

I think a lot of spillover effects are yet to materialize. There are a lot of people working on it, and I expect that they will produce something.

5:55 p.m.

Liberal

The Chair Liberal Bobby Morrissey

We will conclude with Mr. Fragiskatos, Madame Chabot and Ms. Zarrillo. We lost a little time in the motion, so that's to be fair to everybody.

I have Mr. Fragiskatos for five minutes.

5:55 p.m.

Liberal

Peter Fragiskatos Liberal London North Centre, ON

Thank you very much, Chair.

Thank you to both presenters today.

I'll ask you both the same question. It's a very general question. I like to do this, because it does help summarize what we hear from witnesses, especially when the topic is broad and also very important for public policy. Obviously, we're looking at AI with specific reference to labour, but there are many ways to look at that.

How can we take from your testimony the most important parts? What would you say are the key things that you would want us as a committee to keep in mind when looking at this issue going forward and when we ultimately provide recommendations to the government on the way forward?

5:55 p.m.

Prof. Fenwick McKelvey

First, there is a need to consider this around Bill C-27 and the ways in which we're trying to understand privacy and data. Partially what is really important now is recognizing our data power. What AI demonstrates is that there's power in collecting large amounts of data. You can now mobilize it. Really, it's trying to think about privacy law and data as bigger than the traditional concerns about personal information. That's an important broader shift that we've been witnessing, but it just hits it home.

I think the second thing is then trying to understand these uneven and disparate impacts. Certainly we're going to hear ample evidence about the benefits of artificial intelligence. I think it's incumbent on the government to understand and protect those marginalized and precarious workers who might be on the outside of those benefits.

That's certainly part of what's going on with generative AI. We're trying to understand a different class. That's why there's so much attention right now. It's a different class of workers, typically white-collar creative workers, who are potentially now facing greater competition from automated solutions. That's not to say that the effects are going to be easy to predict, but it's also saying that we're seeing a marked shift. That needs to be taken into consideration in how we're going to understand this relationship with AI and the labour market.

Finally, it's to ensure that we are making sure that we have strong protections for workers and making sure that this is something that we value as a society and part of how we frame our legislative agenda.

6 p.m.

Liberal

Peter Fragiskatos Liberal London North Centre, ON

Thank you very much.

I'll ask the other witness the same question. What is one thing you want us, as a committee, to really keep in mind among all the very important things that were raised here today by both of you?

6 p.m.

Professor, Department of Informatics and Networked Systems, University of Pittsburgh, As an Individual

Morgan Frank

I'd say the most important part of my testimony is that, if you feel blindsided or surprised by what AI can do right now, you're not alone. The research community, economists, computer scientists, we've all been really surprised by what recent examples of generative AI can do. The reason we're surprised is that the tools, the data and the framework we've been using to think about AI and the future of work, at least in my case, are clearly outdated. They aren't dynamic enough to account for what generative AI can do.

Moving forward, I would suggest adapting the data that policy-makers and researchers use so that we can be more responsive to what AI is actually doing and better prepare the workers who are directly in the path of AI with that improved data. Data on skills, I think, would do a lot to help provide insight in both the policy-making and the research domain.

6 p.m.

Liberal

Peter Fragiskatos Liberal London North Centre, ON

Our chair tells me I have time for one more question. Actually, the question doesn't belong to me. It belongs to my colleague Mr. Van Bynen, who wanted clarification on what is meant by “algorithmic management”. Just for the record, that would be helpful.

6 p.m.

Prof. Fenwick McKelvey

Algorithmic management is a broad blanket term to talk about different types of techniques of using computers and AI, predictive analytics, to schedule workers, to talk about their performance, to evaluate them and to assign jobs. I think Uber is a good example of algorithmic management, and it ties in to employee monitoring programs or types of systems tied to HR that are monitoring and evaluating workers' performance.

One of the other examples I know of is, if you're a gig or freelance worker, often, you have to install tracking software that takes screenshots of your productivity over a certain period of time. That's the broad suite of what I'm talking about. They're just new and more invasive forms of monitoring workers and of workplace surveillance, and part of that is tied in to forms of using that data to manage workers.

6 p.m.

Liberal

The Chair Liberal Bobby Morrissey

Thank you, Mr. Fragiskatos.

Ms. Chabot, you have two and a half minutes.

6 p.m.

Bloc

Louise Chabot Bloc Thérèse-De Blainville, QC

Thank you, Mr. Chair.

My question is for both witnesses. I should have time to get brief responses.

The study we're doing specifically looks at the impact of artificial intelligence on the workforce. We could also ask whether these technologies have a greater impact on women and people with disabilities, and whether that constitutes discrimination against them.

At this stage of our study, if you had one or two recommendations for us, what would they be, Mr. Frank?

6 p.m.

Professor, Department of Informatics and Networked Systems, University of Pittsburgh, As an Individual

Morgan Frank

I would recommend seeking out good, detailed empirical information about which workers are actually experiencing disruption because of AI, exactly what that disruption looks like and, therefore, what that means for their job security and their ability to find a new employment opportunity if that's the type of disruption they're facing.

6 p.m.

Bloc

Louise Chabot Bloc Thérèse-De Blainville, QC

What do you think, Mr. McKelvey?

November 8th, 2023 / 6 p.m.

Prof. Fenwick McKelvey

Briefly, I would point to a study by the Immigrant Workers Centre of Montreal looking at the applications of algorithmic management in warehouse management. I think hearing from workers, and from workers who are impacted by this, is an important part in making sense of this and in trying to keep up with what's taking place. Part of the deeper issue is developing capabilities and monitoring technology development through something like the Office of Technology Assessment, as the United States previously had, to try to build capabilities to understand those impacts.

6 p.m.

Bloc

Louise Chabot Bloc Thérèse-De Blainville, QC

Mr. Frank, I'm going to ask you a question about data, because I want to be sure I understood you correctly.

In your testimony, you said that more data was needed. That was also part of your recommendations.

You said that unemployment would provide us with more data, if I understood what you meant correctly. That worries me somewhat. I'm all for using technology to perform certain tasks, but not to replace employees. If it puts jobs at stake, in our opinion, it shouldn't be a solution.

I want to hear your thoughts on this. When we use a new technology, shouldn't we be aiming for requalification rather than unemployment?

6:05 p.m.

Professor, Department of Informatics and Networked Systems, University of Pittsburgh, As an Individual

Morgan Frank

I did not mean to say that unemployment is a solution. Just to clarify, what I meant is that it's often difficult to track why unemployment is occurring. You might see a spike in unemployment in a certain province in Canada and want to understand why that's occurring, and it's not always so easy. You have to dig into other data sources to better understand exactly which industries or which workers in particular are experiencing unemployment.

Having unemployment data that actually gives you insight into who's experiencing that level of disruption will be very helpful in forming a response that is proactive. The way I actually see this playing out is through better understanding estimates for the probability that workers will receive unemployment, given the labour market they are in, their job title.... I can imagine other factors playing a role as well. For example, their level of education and maybe their ethnicity and gender would be interesting additional variables to have—but by thinking about these as unemployment risks, based on where workers are in the economy.