44th Parl. 1st Sess.
November 20, 2023
- 11:14:23 a.m.
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Thank you, Mr. Chair.
The fundamental problem with algorithmic management is that wehave no information. There’s no framework for all kinds of elements. There seems to be a wish to pass this problem on to unions and employers, but unions can’t be the solution for managing artificial intelligence in the workplace, when we know that the unionization rate is around 15% in the private sector. This will require a regulatory framework deployed by every level of government.
Nothing is known. No doubt the clauses in collective agreements relating to technological change were used to address artificial intelligence issues, and that was a mistake. It was a mistake because, often, the triggers for technological change clauses are related to job losses or potential job losses. Unfortunately, that doesn’t address issues related to artificial intelligence, which deals with a multitude of situations that don’t result from job loss.
We hear about artificial intelligence as if it’s something positive that will lighten the load on workers. Unfortunately, there’s a downside, such as reduced autonomy and increasingly intrusive surveillance. Workers are constantly being monitored, since algorithms need data to do their jobs. We don’t know how this data is stored, how it’s analyzed or how it’s reused. The ability to collect data is not regulated. We therefore need to regulate data and what is done with it, but above all we need to regulate and mandate dialogue between employers and employees to understand the whole issue of explainability and transparency. There isn’t any.
For years now, we’ve been using tools that make decisions on behalf of workers, but they haven’t been presented as algorithmic management or artificial intelligence tools. They were simply described as new tools. For example, at Bell Canada, there’s the Blueprint tool for customer service staff. When speaking with a customer, workers are required to follow a decision tree that tells them what to do based on the customer’s stated problems. The employee’s judgment is completely removed from the process. What’s more, the employee must enter data into the tool to ensure that the various interpretation scenarios are effective and appropriate for the customer.
This is done in various industries, such as transportation, where algorithms make decisions for truckers, whether it’s about the best route or the best driving practice to use. This completely eliminates the individual’s judgment and ability to drive their vehicle. They are required to follow the tool’s instructions. They must be managed.
The Organization for Economic Cooperation and Development, or OECD, has laid down four principles: artificial intelligence must be oriented towards sustainable development, it must be human-centred, it must be transparent and explainable, and the system must be robust and accountable. At present, we have none of those things, because there’s no disclosure obligation. In our view, this is the first step that needs to be taken. It’s about knowing the tools, understanding their effects and then implementing solutions that are truly benefiting from the efficiency or added value of technological tools in the company.
We’re in a period marked by a shortage of workers. It is simply untrue that we’re going to transform a customer service operator into someone who will program or manage algorithmic tools. In any case, in Quebec, there’s currently a shortage of 9,000 to 10,000 workers in the IT sector, and our workers who can’t fill the gap. There’s a kind of vicious circle that has to stop, and it has to start with the implementation of mandatory disclosure or mandatory dialogue between employers and their employees.
Thank you very much.
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- 11:27:33 a.m.
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Thank you, Mr. Coteau.
The current challenge is that there’s no discussion with employers about this. There’s no discussion about the potential consequences of integrating a new technology. There will only be discussions if we know in advance that there will be job losses. There is no obligation to discuss how a job will be modified, simplified or made more complex. There is no structure. The labour movement, again—
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- 11:28:26 a.m.
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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.
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- 11:33:22 a.m.
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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.
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- 11:35:54 a.m.
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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.
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- 11:38:36 a.m.
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It’s in its infancy, but it’s inadequate. We’re already lagging.
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- 11:42:16 a.m.
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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.
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- 11:49:56 a.m.
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I will refrain from answering that particular question about the use of artificial intelligence and housing issues. I don’t think I have anything new to add.
However, I will reiterate that we need to learn more about these tools. The way to better understand them is to talk about them, to provide a framework that forces employers to explain to their employees what they want to do, the goal they’re trying to achieve, the changes that will be made to their workplace and the repercussions on people’s autonomy.
In a context where augmented work will occur, that’s terrific. In a context where we’re only getting diminished work results, it’s problematic. It all begins with knowledge. We need to know what we’re dealing with. We don’t even know whether we’re dealing with algorithmic tools for automated decisions or semi-automated decisions or whether they’re symbolic algorithms or machine learning algorithms. Those are things we simply don’t know. Workers don’t know if the algorithmic tool is capable of thinking for itself or if it’s just following a decision tree.
We’re a long way from understanding. We need to develop mechanisms to learn more. Once we do…
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- 11:52:26 a.m.
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Thank you for the question.
Presently, this is not something that’s openly and clearly discussed at the bargaining table. We aren’t discussing it. For example, recently, the St. Lawrence Seaway was closed for eight days. Could an algorithmic management tool one day manage the locks remotely? Very likely. Will this lead to job losses? Quite possibly. Is this being discussed at the bargaining table? No, it’s not on the table at all. There is no disclosure.
It’s like asking workers to use up all their bargaining capital, an expression we use. Instead of seeking to improve their working conditions, they’d be asked to use all their bargaining capital to ask for transparency about artificial intelligence. That’s not something workers are interested in. Employers are not disclosing how such tools are being integrated, or what their future impact will be. There’s a huge demand on workers’ participation to populate the databases of these tools and to correct the margins of error, but they’re not told how this will affect their jobs or the evolution of their jobs.
So the dialogue is non-existent. We have to start somewhere. Of course, the bargaining table is a start, but for all the sectors that are not represented, there have to be mechanisms in place for that dialogue to take place.
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- 11:55:07 a.m.
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Yes, there are plenty of conversations between the groups, because unions are sharing what little knowledge they’ve acquired. We realize that all of this is in its infancy. Certain aspects of technology were introduced 15 years ago, and today, with the advent of artificial intelligence, they’re taking on incredible dimensions.
Unions, not just American and Canadian unions, but international unions too, are exchanging best practices or examples of framework measures that could be included in collective agreements or in legislation.
So there are discussions, but the observation remains the same: our knowledge on this subject is in its infancy. We know nothing. This dialogue needs to take place with employers to devise solutions. The aim is not to limit or reduce the effect of AI-related technologies, but to ensure that they represent a positive addition to the workplace, rather than the opposite.
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- 11:57:36 a.m.
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Bell Canada uses a tremendous amount of data and conducts extensive monitoring in all types of jobs. Everything is recorded. Every activity is recorded in a computer. Every action taken and every gesture made by a worker is known. It’s the same for technicians on the road and people working on the networks. Everything is analyzed and everything is known.
People’s performance is managed on the basis of targets to be achieved. Those are determined by the outcome of data analysis. If a technician is told that it takes 25 minutes to connect a line, but in fact takes 35 minutes to make the connection, he will be penalized. The vagaries of weather, for example, are not anticipated by the algorithm. The technician will be told that he’s doing a bad job because he’s not meeting the targets set by the algorithm. That’s where we stand now.
Has the manager’s judgment been substituted by a ready-made solution from an algorithm? The answer is yes, and has been for quite some time. Again, this is an unknown for us, because we don’t really measure what it takes into account. When we ask the employer to share the criteria used for their management tool, we don’t get an answer, because it’s so specific. We’re not given the information.
The manager is being replaced by an algorithmic management tool. At the end of the day, what is the basis for challenging the decision? This is where the question you raised, Ms. Chabot, is significant. You can’t go before an arbitrator or the courts and ask an algorithmic management tool why it made this decision rather than another. That’s why I mentioned earlier that we need to give ourselves the necessary means to correct the effects of algorithmic management decisions. This is the impression we get from people in the field. Managers today pass on messages, but all the tasks that involve judging a worker’s performance are carried out by this tool.
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- 12:00:55 p.m.
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This is an interesting first step. You certainly have to start with a consultation structure. Employers definitely need to be involved in the process, as well as unions and all the worker associations.
We need plain language. Simple language is needed. This is something that seems so complicated to us that we need scientists and people to explain the impact of these replacements. We also need to reassure workers. The fear is that the machine will replace the individual. We don't see what's going on, but we make the work dehumanizing.
The unions need to be at the bargaining table, but all the workers' associations also need to be at the bargaining table. We'll need plain language in order to fully understand the challenges.
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