Course:ELEC300E/CaseStudies/ElectronicMonitoring
Context: Electronic Monitoring Laws
| Electronic Monitoring in the Tech Workplace |
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| Content / Topics |
| Needs and Emotions |
| Engineering Workplaces |
| Labour Rights and Advocacy |
| AI Training |
| Collective Action |
| Relevant Analysis Strategies or Tools |
| Decision Impact Assessment |
| Iceberg Model |
In 2022, the Ontario government introduced the Electronic Monitoring Policy law, requiring employers with 25 or more employees to disclose if, how, and why they electronically monitor workers. This decision emerged in the context of increasing remote and hybrid work, where digital tracking tools—such as keystroke monitoring, GPS tracking, and webcam surveillance—became more common. The Ontario Ministry of Labour, under provincial authority, implemented the policy to address transparency concerns, aiming to ensure that employees are aware of workplace surveillance. However, while the law mandates disclosure, it does not regulate or limit how employers monitor their staff, raising significant privacy concerns among workers and advocacy groups. Many fear that constant surveillance could erode trust, create power imbalances, and negatively impact mental health, especially among lower-wage or marginalized workers who may feel pressured to accept invasive monitoring to keep their jobs. From a technological perspective, the decision reflects the growing use of workplace analytics, artificial intelligence, and data tracking systems, which have become increasingly sophisticated.
While these tools offer efficiency benefits, critics argue they risk normalizing surveillance culture, extending beyond workplaces into education, public spaces, and personal life, further diminishing individual privacy
Case: Electronic Monitoring in the Tech Workplace
A CBC news article interviewed Canadian workers at TD and Bell, which have recently introduced workplace monitoring software.
The monitoring software gathers information about workers' online activity, to gauge and compare the productivity of staff. The workers interviewed raise several concerns, which you can read for yourself in the article.
One notable concern relates specifically to AI training:
She said she's heard from managers that Verint is not only monitoring workers, but pulling their work to train AI systems and offshore workers, which she suspects has factored into recent layoffs.
Note that the suspicion that worker data is used to train AI is not unreasonable. Meta developed a program that recorded staff activities in to train AI models. This program was discontinued after 1,600 workers signed a petition against it, writing:
According to Meta’s Code of Content, Meta is dedicated to empowering and protecting people by "Building AI Responsibly". Meta’s mission is to help ensure that AI at Meta benefits people and society by ensuring that Meta’s machine learning (ML) and AI systems are designed and used responsibly and meet legal and regulatory obligations. We collectively believe that empowering individuals and communities through building responsible AI includes respecting their boundaries and privacy. Any approach to AI that relies on intrusive, coercive, non-consensual data collection contradicts that principle.
Recommended Readings
- 5 minute read, Canadian workers speak out against growing screen time surveillance. https://www.cbc.ca/news/canada/td-bank-bell-workplace-screentime-monitoring-9.7296526
- 2 minute read, Meta pauses employee tracker for AI training amid privacy concerns, https://www.theguardian.com/technology/2026/jun/24/meta-pauses-employee-tracker-for-ai-training-amid-privacy-concerns
Discussion Questions
Here are a few questions to help you begin analyzing the issues discussed in this case study. The purpose of these questions is to prompt reflection and further consideration: there are no right or wrong answer
- Personal response: Take stock of your immediate response to this case study: outrage, discomfort, boredom, confusion, frustration, hope, interest? How might your unique personal experiences and perspectives inform this response? How can you leverage this response in a positive way?
- Contradictory viewpoints and outcomes: What are four concerns or arguments against the monitoring software that are raised by the workers? What arguments might Bell make in favor of the monitoring software?
- Social and Historical Context: Can you see any similarities between the issues raised in this case study, and other case studies or news stories related to worker rights or AI training? Does this case expose a pattern that disadvantages specific vulnerable groups or demonstrates a systemic inequality or power hierarchy?
- Positive action: Meta workers argue that the companies actions with respect to the electronic monitoring contradicted it's Code of Conduct on "Building AI Responsibly". What is your perspective on corporate ethical codes like Meta's? Do you think they are cynical PR tools, or can they be used to hold companies accountable for unethical practices?
- Interruptions and invitations: Based on this case study, what can you do as a worker to protect your rights if they are being violated, or if you object to your employer's practices?
- Physical connections: This case study relates to you personal experiences - while you might not be subject to workplace monitoring, Canvas tracks (and provides instructors) information about your activities. Are you in favor of this data being collected and used, or against it?
- Positive Practices: What is one concrete action that you could take, or a practice that you could adopt in your personal, academic or professional life to address some of the issues, or put into practice one of the approaches discussed in this case study?