The modern workplace is evolving rapidly. Increasingly, decisions once made by human managers, such as scheduling, performance evaluations, and even discipline, are now being made by algorithms and artificial intelligence (AI). Known as algorithmic management, this trend is reshaping how employers oversee workers, particularly in industries with large hourly workforces, such as retail, warehousing, hospitality, transportation, and logistics.
While algorithmic systems promise increased efficiency, consistency, and objectivity, their use also raises critical legal and ethical questions. In Ontario, where employment law is governed by a mix of statutory, common law, and human rights protections, employers must proceed with caution when implementing these technologies.
This blog explores algorithmic management, how it is being used in workplaces, and what Ontario employers need to consider to ensure they remain onside of the law.
What Is Algorithmic Management?
Algorithmic management refers to the use of automated systems, data analytics, and AI to make or influence decisions about workers. These systems often rely on real-time data collection, predictive modelling, and machine learning to assign tasks, monitor productivity, evaluate performance, or determine schedules.
Examples include:
- Apps that assign delivery drivers’ routes based on traffic, customer ratings, and efficiency scores.
- Software that ranks employee performance and automatically generates feedback or disciplinary notices.
- Scheduling platforms that adjust shifts based on demand forecasts, sales patterns, or attendance data.
- Productivity tools that monitor keyboard activity, screen time, or GPS location to assess output.
In some workplaces, human supervision is minimal, and the algorithm effectively acts as the “boss.” Workers may not fully understand how decisions are made, or even be aware that they are interacting with automated decision-makers.
Why Are Employers Turning to Algorithms?
For employers, algorithmic tools offer potential advantages:
- Efficiency: Automating routine managerial tasks can reduce costs and administrative burdens.
- Scalability: Algorithms can manage thousands of workers consistently across locations.
- Data-Driven Decisions: Employers can rely on metrics rather than subjective assessments.
- Real-Time Feedback: Instant performance data can lead to quicker course corrections.
In sectors like ride-hailing, warehouse logistics, and fast-food service, algorithmic systems have become foundational to assigning and evaluating work. However, these tools can also introduce new legal liabilities without transparency, human oversight, or compliance with Ontario employment and privacy laws.
Legal Framework in Ontario: What Governs Algorithmic Management?
Although Ontario does not yet have legislation specifically regulating AI in employment, several existing legal regimes may apply when employers deploy algorithmic systems. Key areas of concern include:
1. Employment Standards
The Employment Standards Act, 2000 (ESA) sets out minimum standards for working hours, scheduling, breaks, and termination. Algorithmic scheduling software must still comply with rules about:
- Notice of shift changes
- Maximum daily or weekly work hours
- Minimum wage and overtime calculations
For instance, an AI tool that changes shifts with minimal notice may violate provisions requiring employers to give reasonable scheduling notice. Automated termination notices could also lead to ESA violations if they fail to provide appropriate severance or pay in lieu of notice.
2. Human Rights
The Ontario Human Rights Code prohibits discrimination based on age, gender, race, disability, and family status. If an algorithm intentionally or not disproportionately disadvantages certain groups (e.g., parents needing flexible schedules, older workers with slower response times), it may result in discriminatory treatment.
Employers remain liable even if bias is introduced through the algorithm rather than a human decision-maker. This is known as algorithmic discrimination and is increasingly a concern in hiring, performance scoring, and task assignment tools.
3. Privacy and Data Protection
Ontario does not yet have a comprehensive private-sector privacy law, but the federal Personal Information Protection and Electronic Documents Act (PIPEDA) applies to many Ontario employers. PIPEDA governs how organizations collect, use, and disclose personal information.
Algorithmic systems that track workers’ movements, keystrokes, or browser history must comply with PIPEDA’s requirements for:
- Knowledge and consent
- Limiting collection to what is necessary
- Openness and transparency
- Allowing employees to access their data
In addition, Ontario has proposed a Digital Platform Workers’ Rights Act, which includes rules about transparency in how digital platform workers are assigned work and evaluated—an early sign of more regulation to come.
4. Contractual and Common Law Duties
The employment relationship includes implied duties such as good faith, fair dealing, and reasonableness. Suppose an algorithm makes decisions that violate these duties, such as issuing unfair discipline, undermining reasonable expectations, or breaching procedural fairness. In that case, employers may face wrongful or constructive dismissal claims.
Employers must ensure that automated decisions are not arbitrary, irrational, or procedurally unfair. They must also retain a meaningful opportunity for human review and appeal.
Legal Risks of Unchecked Algorithmic Management
The use of algorithmic management systems may seem efficient, but legal risks arise quickly when these systems are:
- Non-transparent or secretive in their operations
- Unable to account for accommodations or employee context
- Based on flawed or biased training data
- Used to make high-impact decisions without human input
Common legal pitfalls include:
- Failing to accommodate employees with disabilities when an algorithm penalizes “low productivity”
- Discriminating against women or caregivers through scheduling tools that penalize part-time availability
- Terminating employees based solely on performance data without providing due process or the opportunity to explain
- Failing to disclose what employee data is being collected or how it is used
In these situations, employers may be liable for discrimination, breach of statutory obligations, or wrongful dismissal—even if no human manager was involved.
Transparency and Consent: Are Employees Being Told the Truth?
A critical legal and ethical issue with algorithmic management is the lack of transparency. Workers may not understand what data is being collected about them, how it is analyzed, or what consequences result.
Ontario law increasingly emphasizes the need for informed consent in data collection and transparency in decision-making. Employers must:
- Clearly disclose the presence and purpose of algorithmic systems.
- Obtain meaningful consent for data collection.
- Allow employees to access their data and contest decisions made based on it.
In unionized workplaces, the use of surveillance or performance-monitoring algorithms may also trigger duty-to-bargain obligations. Employers must inform unions and may need to negotiate how such tools are used.
Best Practices for Employers in Ontario
Given the risks, employers considering or currently using algorithmic management tools should adopt the following best practices:
Conduct an AI and Data Impact Assessment
Before implementing a new tool, assess how it will affect employees, what data it will use, and whether it could introduce bias or privacy risks. Consult with legal counsel to evaluate compliance with applicable laws.
Ensure Human Oversight
Avoid “black box” decision-making. Important employment decisions—such as discipline, termination, or performance evaluations—should include a human review process. Employees must be able to appeal or explain circumstances the system cannot account for.
Disclose and Document
Clearly communicate to employees how their data is being collected, what the algorithm does, and how it impacts their job. Keep detailed records of the decision-making process to support fairness and defend against future claims.
Provide Training
Supervisors, HR professionals, and even frontline managers must understand how algorithmic systems work. Training should include both technical understanding and legal context, especially around accommodation and human rights.
Accommodate and Adjust
Algorithms are not capable of empathy. Employers must retain flexibility to adjust outputs based on accommodation requests, caregiving responsibilities, or other human factors. This includes pausing or overriding automated actions when necessary.
The Future of Regulation
Governments are taking notice. Ontario’s interest in digital platform regulation may soon extend to all workplaces. Federally, proposed privacy legislation (Bill C-27) includes a new Artificial Intelligence and Data Act (AIDA) that would impose specific duties on those deploying high-impact AI systems, including in employment contexts.
Internationally, the European Union’s AI Act and the U.S. Equal Employment Opportunity Commission’s focus on algorithmic discrimination show that broader regulation is likely inevitable.
Ontario employers should expect further legal obligations related to:
- Algorithmic transparency
- Non-discrimination
- Data governance
- Employee consent
Being proactive now is the best defence against reputational, regulatory, and legal risk.
Algorithmic Management in Ontario: Understanding Employer Liability
Algorithmic management is not science fiction—it’s already here, and its use is expanding across Ontario workplaces. While it offers real benefits in terms of efficiency and scalability, it also introduces significant legal and ethical complexity. Employers must not assume that delegation to a machine shields them from liability. If anything, the law increasingly holds employers responsible for the outputs of the algorithms they choose to implement.
Ontario employers should proceed carefully, ensure transparency, and consult employment counsel when adopting algorithmic management systems. With thoughtful policies and proactive oversight, businesses can harness technology’s benefits without undermining their employees’ rights and dignity.
Haynes Law Firm: Helping Employers Ensure Algorithmic Compliance
The rapid adoption of algorithmic management in Ontario workplaces presents both opportunities and complex legal challenges. Proactive legal counsel is essential to safeguard your organization from potential liabilities and ensure compliance with evolving employment and human rights laws. Haynes Law Firm in Toronto is experienced in helping employers navigate these new frontiers, from identifying potential risks to developing robust conflict prevention strategies. We work diligently to protect your interests and provide exceptional advocacy should a dispute arise. To discuss how the team at Haynes Law Firm can assist your business in responsibly implementing algorithmic management systems, please reach out online or by phone at 416-593-2731 for a confidential consultation.
