Human Resources Committee on Nov. 20th, 2023

[Olivier Carrière]

In a context where there are no unions, a government structure must require the setting up of workers’ committees to explain to people what we want to implement, how it will affect work and how we will be able to correct the negative effects or unwanted pernicious effects of algorithmic management. If, in the algorithmic management tool, there are features that discriminate unintentionally, we need to be able to correct the application of the management tool.

The management tool is replacing the manager. Workers and employers need to collectively build management tools. If there are mistakes or negative trends, we must give ourselves the necessary means to correct them. This absolutely requires dialogue with workers, through a structure that is not necessarily the union structure. We need to set up such a structure.

[Michael Coteau, Liberal, Don Valley East, ON]

Thank you very much for being here. I think the organized labour voice is very important in this conversation. I appreciate the fact that you joined us here today.

Mr. Lockhart, I have a question for you. You said that 2% of job vacancies that are being published today cite AI skills as a requirement. Do you think that 2% is a true reflection of the actual sector, or is that just the jobs?

Do you think that because it's becoming easier to incorporate AI without specific skill sets—as I think you stated—the 2% is an under-representation of that skills that are actually required?

What tools can be placed in the job without the employee needing those specific skill sets?

I hope I made sense.

[Angus Lockhart]

That makes total sense.

We saw that just 2% of all jobs have any kind of AI skills. You're exactly right in saying those AI skills are traditional tech-based skills—things that require advanced training to use. There is a generation of new, generative tools that take natural language inputs and don't require the same technical skills to use.

That said, there is still a whole range of technologies that require those digital and technical skills to use. The new technologies aren't necessarily replacing them. They're more additive. They're operating in new areas in which the old technologies didn't help. There is still going to be increased demand and need for AI skills, broadly.

The same workers who don't have AI skills and are being asked for AI skills are going to be able to adopt the new tools, but they might not necessarily be able to use any of the older, existing tools.

[Michael Coteau, Liberal, Don Valley East, ON]

Thank you.

I was very fascinated, Mr. Bessen, with how you started off your conversation.

You said there was a lot of media hype around AI and that this is just a continuation of a 70-year process. Hopefully, over the course of the remainder of the time, I can get a little more detail on that. It is a very fascinating and popular subject. I'd like to hear more about why you think it's part of a long story, rather than something new.

Thank you so much, Mr. Chair.

[The Chair, Liberal, Bobby Morrissey]

We'll capture that in another question. The time is out.

Ms. Chabot, you have six minutes.

[Louise Chabot, Bloc, Thérèse-De Blainville, QC]

Good morning, Chair.

I’d like to thank the witnesses for being with us. Your testimony is very important, even if we don’t have all the answers and we don’t yet know all the challenges associated with implementing artificial intelligence in the workplace.

Mr. Carrière, you opened by telling us that the challenge is the total lack of information and guidance. Can you tell us a little more about that?

[Olivier Carrière]

Thank you very much, Ms. Chabot.

Presently, we seem to want unions and employers to find the magic bullet or the magic wand. Instead, I think it’s going to take the federal and provincial governments to put regulations in place, according to their respective areas of jurisdiction.

The first step to understanding the effects of algorithmic management is being aware of what’s going on. Employees must be informed and consulted. This will ensure transparency and explainability. The only effects of algorithmic management that we are currently seeing are negative ones. We see work decreasing rather than increasing.

What we see is a decision-making tool, a computer application, making decisions and diagnosing anomalies instead of the individual. Our impression is that, in unionized workplaces that apply an algorithmic management program, workers find themselves dehumanized. Dehumanization is a strong word. In fact, the individual is clearly told that their judgment is no longer needed, because a computer tool does the thinking for them. That demotivates people, since they become automatons, i.e., they perform a task without thinking.

Currently, people are unaware that they are being replaced. What’s more, they’re being asked to feed data into the tools that are going to replace them. We need to get back to basics. We need to impose, probably through the Labour Code, a conversation about the kinds of technology companies want to use, and we need to determine its impact.

[Louise Chabot, Bloc, Thérèse-De Blainville, QC]

Unifor represents thousands of workers in Quebec and across Canada, in a number of sectors.

Now that implementation has begun in some sectors, have you observed any impact on certain job categories?

[Olivier Carrière]

Yes, there have been numerous consequences. This is hardly a new phenomenon. Technological changes have had such repercussions for many years, even decades.

Take Bell Canada, for example, in the telecom sector. For 15 years, surveillance tools have been capturing and recording all data relating to workers’ production in order to measure and analyze their performance or incompetence, as the case may be. At Bell Canada, for instance, a performance management system based on forced ranking was introduced. Under this system, an individual ranked in the bottom quartile is met by the employer because algorithmic tools have determined that their performance is weaker than that of others. Because an employee is weaker than others, a performance management plan is applied, notwithstanding the manager’s judgment. The manager relies on the algorithmic tool to make a decision. That’s what we’ve seen in the telecom sector.

In the transport sector, every single driver is monitored 24/7. All data is captured and recorded. Once again, algorithmic tools are superseding the judgment and expertise of individuals. These tools will tell a truck driver, for example, where to go to get from point A to point B, because it’s more efficient. We’re completely removing the worker’s judgment and replacing it with an algorithm.

There are several similar examples, but, in general, we’re unaware of it, because it hasn’t been disclosed. If it doesn’t involve employers cutting jobs, it isn’t discussed. And yet, many jobs disappeared five, six or eight years after this kind of tool was integrated. So this dialogue never happens. That’s why we first need to develop mechanisms to inform and consult employees. Then, we need to work together to build the tools. Finally, we need to give ourselves the means to adapt them, if necessary.

[Louise Chabot, Bloc, Thérèse-De Blainville, QC]

Are there any examples of social dialogue in this area?

I’m talking mostly about Quebec. For instance, I'm aware of the Commission des partenaires du marché du travail, a social dialogue forum.

Are there any good practices in workplaces?

[Olivier Carrière]

It’s in its infancy, but it’s inadequate. We’re already lagging.

[Louise Chabot, Bloc, Thérèse-De Blainville, QC]

It’s disturbing to see that we’re moving forward without informing people. In the workplace, we’re just beginning to acknowledge these practices and their consequences.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Ms. Chabot.

Madam Zarrillo, you have six minutes.

[Bonita Zarrillo, NDP, Port Moody—Coquitlam, BC]

Thank you so much, Mr. Chair. This is very interesting testimony today.

I'm going to ask my initial questions to Mr. Lockhart. If I have time, I would like to ask some questions to Monsieur Carrière as well.

I want to talk a bit about the points you made around the increased prosperity and how that's potentially not going to be distributed equitably among workers. My questions relate to protections of workers. You mentioned a responsible framework. I wonder if you could expand on what you think those responsible frameworks could look like on a federal level.

[Angus Lockhart]

I think that's probably a very challenging question to answer in a short time.

What we certainly view as part of a responsible framework is making sure that when artificial intelligence is implemented, it's not being done in a way that's harmful to the workers who are using it explicitly. There are always risks of increased workplace surveillance and facial recognition being used in the workplace, and we definitely want to avoid any kind of negative impacts from that.

Beyond that, there's a huge risk from AI that businesses will be able to implement AI and reduce labour, and that the increased productivity and benefits from that could be concentrated among just the ownership of the business. That runs the risk, obviously, of increasing wealth inequality in Canada. At the Dais we strongly believe that prosperity and GDP growth are beneficial for Canadians, but only when they are distributed among all groups.

I don't think I have an answer for how to make sure the benefits that come from increased productivity for workers are distributed among all of the workers and the people in the firm, but I do know that's going to be an important part of keeping up with AI adoption.

[Bonita Zarrillo, NDP, Port Moody—Coquitlam, BC]

Thank you for that.

Do you think, perhaps, that the federal government could lead an advisory council or a round table? If so, who do you think should be on there? What groups should be represented?

[Angus Lockhart]

I think that is definitely a path that needs to be investigated. I think that when you do that, you need to make sure all groups are represented. Obviously, you need to make sure industry's represented. Having unions there is important.

I think the trickiest part is making sure you have non-unionized workers represented there in some capacity, because a large portion of Canada's workforce is not unionized. If those voices aren't present at the table, then you really run the risk of a two-tiered system of unionized versus non-unionized workers.

[Bonita Zarrillo, NDP, Port Moody—Coquitlam, BC]

Thank you so much.

Monsieur Carrière, I also have a question around the protection of workers. You talked about it.

I'm worried about populating the tools with workers' ideas, skills and experiences, and then those workers never receiving any of the benefits of that. All of their intellectual and cognitive property and even their copyright rights are potentially at risk. I'm wondering if you could expand on how we protect workers' ideas, skills and experiences?

[Olivier Carrière]

As a union, we see that a number of tools exist to make the employee’s job easier. As I mentioned, there are negative impacts. Workers are being stripped of their autonomy and capacity for judgment. We’re turning individuals into automatons following a recipe previously determined by an algorithm.

I’ll use Bell’s Blueprint as a case in point. Communication systems installation technicians are required to enter their objective and all the steps involved in their task into the program. This is a basic step. It’s not a complex process, but workers have to explain what they want to do, and the program tells them how to do it. Workers become mere implementers.

In the job categories we represent, no one holds intellectual property on their ideas, because they’re already performing a job as an implementer. Workers are reduced to their simplest expression. They are stripped of their ability to judge, their expertise and the effect of having a great deal of experience in the sector, under the pretext that an algorithm can take anyone and have them do the same job. The impact is negative for workers. Work is becoming boring and so easy that there’s no challenge. As a result, people are leaving the company to work elsewhere. Artificial intelligence is being used as a partial solution to a labour shortage, but by making the work uninteresting, it’s causing turnover. It’s driving attrition.

It’s not so much a question of protecting workers’ ideas, but of ensuring that human beings are contributing their skills, values and knowledge to their business. Currently, we’re seeing that tools aren’t having that effect.

[Bonita Zarrillo, NDP, Port Moody—Coquitlam, BC]

Thank you so much.

I'm going to use my last less than a minute to ask Mr. Bessen this: We recently experienced the writers' and actors' strikes down in the United States. It had an affect up here in Canada. I'm from B.C. It put a lot of people out of work for over six months. I wonder what was learned around AI with regard to the recent strikes in the acting and writing fields?

[James Bessen]

I'm not sure we've learned much about AI specifically.

There have been a number of studies done on using AI to assist writers. There's some evidence that it helps less-skilled writers do a better job. I don't think that AI's anywhere near the point where it can really replace writers. I think that was being talked about, but I don't see any evidence that it's about to happen or can happen. My own experience—and the experiences of a whole number of other people who have tried to do writing with ChatGPT or whatever—is that there are some huge limitations on using this technology at this point.

[The Chair, Liberal, Bobby Morrissey]

Thank you, Madam Zarrillo.

Mr. Aitchison, you have five minutes, please.

[Scott Aitchison, Conservative, Parry Sound—Muskoka, ON]

Thanks, Mr. Chair.

Mr. Bessen, I'm going to start with you.

I'm actually just going ask a question about housing, frankly. That's my portfolio. I know that there's a huge challenge with housing in the United States, as well as here in Canada. A big part of the problem is the lack of supply and the pace at which things get approved—with plans and all of that kind of stuff.

I'm wondering if you could speak a little to the application of tools like AI to speed up the approvals process, for example, in municipal zoning and that kind of thing. When you made your comments, I kept thinking about how this is a tool to be used, not to be afraid of. It presents opportunities. I'm hopeful that maybe it presents some opportunities in the housing sector.

[James Bessen]

That's certainly an interesting idea and one I hadn't thought about before. I immediately see that it runs into a problem, which is that all of the regulations and requirements that go into approvals are not something an AI system can just ignore.

AI may be helpful. You would like to be able to see ways in which perhaps the various regulators would be able to use AI to analyze the various reports and speed up that process, but they'd have to be willing to do so. You might see ways in which AI could help compile all the various approvals.

There are possibilities for it to work, but I think it's a difficult problem, because there's a big interaction between regulations and laws and the technology. You can very easily see a situation in which AI would be used and then there would be a lawsuit because somebody didn't like the outcome.

[Scott Aitchison, Conservative, Parry Sound—Muskoka, ON]

For an industry that is incredibly over-regulated—I would suggest that housing is generally over-regulated—you made a comment there that made me think that maybe AI is a tool that could be used, as you said, to compile all of the existing rules and regulations. Maybe it could be a tool that could analyze the layers of regulation, the layers of bureaucracy involved, trim the process and eliminate a lot of overlap. Is that a potential perhaps?