Not so long ago, the legalization of recreational marijuana and the practical application of artificial intelligence in human resources seemed like remote possibilities. As far out as they may seem, these developments are a reality and their impacts on the workplace are imminent.

On October 17, recreational marijuana was legalized in Canada but there remain many lingering questions about its consequences for workplaces. HR professionals are particularly curious since they will inevitably be confronted with the challenging question of what constitutes legally-justified testing for employee cannabis use.

To answer this question, and others like it, employers and employment lawyers are turning to a widely discussed and rapidly growing technology: artificial intelligence (AI).

AI’s introduction as a practical and reliable tool for professionals couldn’t have come at a better time. Given the prospect of increased employee cannabis use, HR teams around the country are actively laying the groundwork for the drug testing policies they’ll be introducing or revamping to ensure workplace safety.

Join Lexology and myself on the 31st October to discuss how lawyers, in-house counsel and HR professionals can use AI to accurately predict how courts will decide outcomes of challenging employment law issues.  A timely use-case being the emerging Canadian issue of determining what constitutes legally justified testing for employee cannabis use.  I’ll apply AI to a recently decided case and demonstrate the impacts of key factors, including which factors can swing a decision one way or another.

Register here to attend the webinar:


In the coming months, many HR professionals will reach out to legal counsel to tackle questions such as whether or not prospective employees can be screened for drug use and how to fairly and legally conduct employee drug testing (randomly, targeted, post-incident, etc.); some will attempt to find the answers on their own. However, one notable challenge stands in the way: there isn’t yet a statutory regime that provides a clear and fixed set of rules that outline when employers can mandate drug testing for employees. Until now, judges and adjudicators have relied heavily on the common law; that is, on decisions reached by the courts in similar cases in the past. There are hundreds of past decisions addressing a multitude of nuanced drug testing situations. When trying to determine how a particular scenario should be handled, manually reading through these hundreds of cases is cumbersome and resource-intensive. What’s more, even when extensive research is completed, it can be difficult to obtain a definitive answer that takes into account all relevant factors from all relevant cases.  


At the centre of most cases stand two opposing interests which HR professionals are intimately familiar with: privacy and safety. Many employees feel strongly that what they do outside of work is a personal matter that shouldn’t be subjected to scrutiny by their employer. Drug testing can be invasive, anxiety-provoking, time-consuming, and it can undermine the trust that is crucial to maintaining healthy employer-employee relationships. HR departments, however, have a responsibility to ensure that the workplace is a secure, harm-free environment. If employees know that they will be subjected to drug testing, it may dissuade them from using marijuana at work, fostering a safer workplace for all.

Judges and adjudicators consider a range of relevant factors when assessing the privacy and safety tradeoff. For instance, was the employee in a role where her safety or the safety of others was a primary concern? Did the employee show signs of impairment (abnormal speech, red eyes, odour, etc.)? Was there physical evidence of the employee using drugs at work? What was the extent of the damage to others or to property, if any? Were there plausible alternative explanations for the incident? Did the employer explicitly consider the worker’s privacy interests before requiring a drug test? Was the testing random or targeted based on other factors?


The multitude of cases and the factors addressed in each written decision generates a trail of valuable data, which lawyers use to identify patterns in past case outcomes. These breadcrumbs are also fundamental inputs that AI systems use to provide tailored insights about how decision makers have weighed various factors. For the first time, software is now available that quickly, precisely, and comprehensively analyzes the findings of hundreds of relevant decisions to make predictions about how these relevant factors will impact new cases.


AI sometimes connotes an image of a confusing black box of 1’s and 0’s. In reality, newly available software for drug testing is relatively transparent and user-friendly. It works by first asking for a series of inputs through a short, plain language user questionnaire suitable for lawyers and HR professionals alike. It collects information about the user’s context such as the applicable province, the past disciplinary record of the employee, the degree to which the employee cooperated with the employer, the nature of the employee’s work responsibilities, the specific indicators of impairment, any alternative explanations, and more.

With inputs unique to the situation at hand, the software goes to work, instantly comparing the information provided by the user to all relevant past cases. The result is a report that conveys how likely it is that a drug test would be found to be legally permissible or impermissible, along with a corresponding confidence level (expressed as a percentage). The software also generates a succinct and easy-to-understand explanation for the predicted outcome and a list of past decisions that are most similar to the circumstances inputted. The user can try multiple scenarios and see how the predicted outcome would change given different assumptions. When tested against cases that the system has never seen before, an AI-based prediction system is able to achieve 90 per cent or greater accuracy. The most advanced systems are also updated with new decisions as they are published, enabling the system to improve its predictions and provide up-to-date outputs.


In the same way that software programs have improved internal processes like payroll and tracking employee time-sheets, AI-based tools represent a generational leap forward for tackling legal employment issues. Indeed, software powered by AI is quickly becoming one of the most valuable resources for HR professionals and employment lawyers, making their work smarter, faster, and more thorough. Similar to the introduction of workplace computers in the 1980s, the newness of AI has created a combination of fear and excitement. Although history does not repeat itself perfectly, it does rhyme. It is only a matter of time before it will be hard to imagine working as an HR professional without the help of AI software.