Recap: PBSC x LTEC Lab — AI in Labour & Employment

Authored by: Ajeetha Vithiyananthan, Windsor Law JD Candidate ‘28 & LTEC Lab Research Assistant

On March 18, 2026, Pro Bono Students Canada’s (PBSC) Windsor Law Chapter, in conjunction with Windsor Law LTEC Lab directed by Dr. Pascale Chapdelaine, hosted a public educational event on the growing use of artificial intelligence (AI) in the employment and labour context and its implications for workers' rights, transparency, and accountability.

Four PBSC Windsor Law students shared the insights gained from a months-long research project on these topics: Clara da Conceição Bulhões (JD 2027), Heather Fernandes (JD 2028), Ashlie Dhugga (JD 2028), and Bandna Dhaliwal (JD 2028). They worked under the supervision of Jessica Paglia of Spring Law. Their presentation was followed by a panel discussion with Windsor labour and employment lawyers J.P. Karam, partner at Willis Business Law, and Connor Henderson, associate at McTague Law Firm.

As more and more employers, in their perpetual quest for improved efficiency, rush to incorporate AI into their workflows, workers are becoming rightfully wary of AI’s potential effects on their jobs. Recent graduates worry that their resumes may never reach human eyes. Employees worry about employers monitoring the websites they visit, the emails they send, or the calls they make throughout the workday. At the same time, firms and professionals are increasingly expected to use AI responsibly, balancing productivity benefits with obligations to protect confidential information and exercise independent judgment. 

For these reasons, PBSC Windsor and LTEC Lab brought together legal research and practical experience to examine how AI is reshaping the employment relationship. The event explored how existing employment, privacy, and human rights laws respond to AI-driven workplace issues, where those legal protections fall short, and how lawyers are navigating these questions in practice as AI becomes increasingly integrated into both workplaces and the legal profession.

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Throughout the students' presentation, one thing was clear: Ontario's legislative efforts addressing AI in labour and employment have primarily increased transparency rather than restricting or clarifying employers' use of AI in hiring, workplace monitoring, and decision-making. While recent Ontario legal reform provides workers with greater visibility into when AI is being used, they stop short of regulating how these systems operate or protecting employees from many of the risks they pose. In short, transparency, while valuable, is not synonymous with accountability.

The students organized their research around three areas where AI is already changing the employment relationship: workplace monitoring and employee privacy, the collection and use of personal information, and the growing role of AI in recruitment and hiring. Throughout each topic, they examined how existing employment, privacy, and human rights laws respond to these emerging technologies — and where important gaps in the law remain.

Clara da Conceição Bulhões opened the presentation by exploring how surveillance technology enables employers to monitor productivity with unprecedented precision, from tracking employees' locations through GPS to recording websites visited during work hours and measuring performance through electronic monitoring systems. Although these technologies promise efficiency and oversight, they also risk creating workplaces in which employees feel constantly scrutinized, contributing to heightened stress, reduced job satisfaction, and diminished trust between workers and management.

Ontario's Working for Workers Act, 2022 (SO 2022, c 7) sought to address some of these concerns by requiring employers with 25 or more employees to maintain a written Electronic Monitoring Policy. However, these requirements only promote transparency rather than imposing meaningful limits on employer surveillance. Employers must disclose whether electronic monitoring occurs, how it takes place, when it is used, and for what purposes — but the legislation does not restrict the scope of monitoring itself. Workers, therefore, only gain greater awareness of monitoring practices without necessarily receiving greater control over how those practices are carried out.

These concerns surrounding workplace surveillance naturally lead to broader questions about how employee information is collected, stored, and protected. To answer such questions, Heather Fernandes turned to Canada's existing privacy framework: PIPEDA, the Personal Information Protection and Electronic Documents Act (SC 2000, c 5). PIPEDA is a federal law in Canada that establishes clear rules for protecting personal information that is collected, used or disclosed in the course of commercial activities. It also applies to the personal information of employees who work for a “federal work, undertaking or business” (e.g. bank or telecommunication company) as defined in PIPEDA.

Although PIPEDA does not apply to other employees in Ontario, PIPEDA's ten Fair Information Principles provide a legal framework governing how organizations collect and use personal information that may guide courts or tribunals on the level of protection that employees may expect. By requiring informed consent and limiting data collection, these principles shape how organizations deploy AI systems involving personal data.

Employers are also using AI in ways that impact people before they even step into the workplace, through AI screening of job applicants. Effective January 1, 2026, Ontario's Bill 149, Working for Workers Four Act, 2024 (SO 2024, c 3), has introduced new disclosure requirements for employers using AI to screen, assess, or select job applicants. Publicly advertised job postings from employers with 25 or more employees must now indicate whether artificial intelligence forms part of the hiring process, and employers must retain job postings, applications, and related communications for three years.

Yet, as Bandna Dhaliwal explained, these amendments stop well short of regulating AI itself. Employers are not required to explain how their AI systems function, disclose the data used to train them, or, most significantly, demonstrate that the automated decision-making tools are free from bias. Given that many AI hiring systems are trained on historical employment data, they may inadvertently replicate or amplify existing patterns of discrimination while offering applicants little insight into how hiring decisions are made. 

Ashlie Dhugga looked into how existing human rights protections can address AI-driven discrimination. Although AI technologies continue to evolve, employers remain fully responsible for ensuring that automated systems do not discriminate on prohibited grounds of the Ontario Human Rights Code (RSO 1990, c H.19), such as disability, race, religion, sex, family status, or other protected characteristics. 

For example, employers should be cautious about using productivity-monitoring software, as it may penalize employees who require disability accommodations, observe religious breaks, or experience pregnancy-related health limitations. As employers continue to owe a duty to accommodate applicants and employees to the point of undue hardship, accommodations can include offering alternative interview formats, extending assessment time, disabling facial recognition technology, or overriding automated evaluations that produce inequitable outcomes.

Overall, the students' presentation made clear that Ontario's legal framework is only beginning to address the issues raised by the growing use of AI in the workplace; it has not yet kept pace with the technology. While recent legislation like Bill 149 increases transparency, much of the responsibility for protecting workers from AI’s risks still falls to existing privacy and human rights laws. Until stronger safeguards are introduced, employees will need to understand their rights and remain aware of how AI is being used in their workplaces. 

For more information and resources on what Ontario workers need to know about artificial intelligence, hiring transparency, and their rights in the workplace, PBSC Windsor has created a brochure. Please see below for a closer look.

PBSC LTEC brochure.pdf

Download PDF • 3.84MB

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The panel discussion shifted the conversation from the legislative framework to the realities of legal practice, as employment lawyers J.P. Karam and Connor Henderson reflected on how artificial intelligence is already reshaping workplaces and the legal profession. While both panellists acknowledged AI's undeniable value as a productivity tool, they repeatedly returned to a central principle: AI should enhance human decision-making, never replace it.

Contrary to fears that AI threatens the future of legal practice, both speakers encouraged students to embrace the technology thoughtfully. Henderson noted that many of the tasks traditionally assigned to junior lawyers, such as legal research, document review, and drafting, can now be completed more efficiently with AI-assisted tools. Karam similarly described how AI has become integrated into his own practice, emphasizing that refusing to engage with these technologies is neither practical nor productive. Instead, lawyers must develop the ability to use AI critically, verifying its outputs and treating it as one tool among many rather than an unquestionable authority.

Both panellists also questioned whether requiring employers to disclose their use of AI during recruitment under Bill 149 meaningfully protects job applicants. Karam described the legislation as "largely symbolic," observing that simply informing applicants that AI has been used offers little reassurance if they remain unaware of how the technology influenced hiring decisions. Henderson agreed that while disclosure may make it easier for applicants to identify when AI was involved, it does little to address the broader imbalance of power between employers and prospective employees.

Rather than advocating for outright restrictions on AI, the panellists emphasized the importance of purposeful and responsible implementation. Karam suggested that employers should clearly explain not only that AI is being used but also the specific function it performs within the hiring process. Whether an AI tool is screening for minimum qualifications or identifying candidates with particular experience can make a significant difference in how applicants understand and assess the process. Meaningful transparency, they argued, requires more than a generic disclaimer; it requires context.

The conversation also explored the challenge of regulating technology that continues to evolve faster than legislation. Henderson observed that employment law is often "playing catch-up" as new AI tools emerge, while Karam noted that legislative reforms frequently lag behind technological change and can introduce uncertainty for employers attempting to navigate their legal obligations. 

Both suggested that most significant developments will ultimately come not from legislation alone, but through decisions of courts and administrative tribunals as they begin applying existing legal principles to AI-related disputes. Existing protections under the Ontario Human Rights Code, they explained, remain fully applicable regardless of whether discrimination results from human decision-making or algorithmic processes. An employer cannot escape liability simply by pointing to AI as the source of a discriminatory outcome.

Another recurring concern involved the responsible use of AI within legal practice itself. Both panellists cautioned against entering confidential client information into publicly available AI platforms, emphasizing that lawyers' professional obligations of confidentiality and solicitor-client privilege extend to the use of emerging technologies. Many firms, they noted, have already begun implementing internal AI policies, pilot testing approved software, and establishing safeguards to ensure lawyers verify AI-generated research before relying upon it. These policies reflect a broader recognition that technological competence now includes understanding both AI's capabilities and its limitations.

Perhaps the most practical advice of the afternoon was directed toward the law students in attendance. Rather than discouraging the use of AI, both Karam and Henderson urged future lawyers to develop strong habits of independent legal reasoning. AI can accelerate drafting, improve writing, and assist with research, but it cannot replace careful analysis or professional judgment. Karam illustrated this point by describing exercises he uses with junior lawyers to demonstrate how confidently AI can produce incorrect legal answers, reinforcing the importance of verifying every authority and reading the underlying legislation firsthand. 

As both speakers concluded, technological literacy will undoubtedly become an increasingly valuable skill for new lawyers, but so too will the ability to question AI's conclusions, recognize its limitations, and ultimately exercise independent legal judgment.

By bringing together student researchers and practising employment lawyers, PBSC Windsor and the LTEC Lab created an opportunity to examine these emerging issues from both academic and practical perspectives. As AI continues to evolve, conversations like these will play an important role in ensuring innovation is matched by thoughtful legal advice and meaningful protections for workers. 

A huge thank you to supervisor Jessica Paglia of Spring Law and Dr. Pascale Chapdelaine for their guidance to the students throughout the project, to Elan Foorer (JD 2027), Natalie Cusinato (JD 2026), and Rebecca Zuker (JD 2026) for their amazing work with PBSC, and to LTEC Lab RA Jessica Kabuli (JD 2026) for helping plan the event.

Be sure to follow Windsor Law LTEC Lab on Instagram to see when our next events will be happening! Also, stay connected through LinkedIn for our seminar series and other opportunities to engage with law, artificial intelligence, and emerging technologies at Windsor Law.