The current legal system in Canada is not effective in dealing with small disputes.

The laws governing even simple issues are often unduly complicated and not made available to the general public in an understandable way. The cost of speaking with a lawyer to educate yourself about the law will often exceed the value of a claim, let alone the cost of pursuing it.

This was reflected in a leading study that found that 86% of Canadians looking for legal assistance chose not to hire a lawyer. The average person is left without the means to pursue claims and recover damages they are not only entitled to, but may desperately need in order to make ends meet. 

Legal Technology as a Solution to Increase Access to Justice Crisis

The prohibitive cost of acquiring legal information is clearly inequitable, but what can be done about it? Despite recent reforms to improve the accessibility of our courts, there is still a long way to go before all Canadians can equally benefit from our civil justice system.

However, we are lucky that some of Canada’s brightest minds have devoted significant attention to finding solutions. Among these promising solutions, is utilizing artificial intelligence to put the relevant legal information into the hands of people who need it, not just people who can afford it. 

The principle of legal precedent dictates that when dealing with a legal issue, the previous determinations of that issue by the court should be binding.

In practice, this means that the answer to a legal question can be determined by finding cases with the same legal issue and similar facts and then accounting for slight differences in the facts. This task requires significant legal skill and can only be done effectively by someone with legal training.

But what if this wasn’t the only way to solve a legal question? The emergence of AI technology has made this a real possibility.

In theory, an AI algorithm could do a much better job of understanding a precedent and its subsequent treatment in the case law in determining what the outcome of a novel situation should be. This is because a computer has the ability to do complex statistical analysis on how a set of factors fit together based on exactly how those factors have been treated by judges in the past. 

Using AI to predict legal outcomes is a relatively new idea and has demonstrated promise. AI will not replace lawyers, but will greatly increase their efficiency. If a lawyer does not have to spend all day doing research because an algorithm found the most relevant cases in five minutes, it greatly reduces the amount of time they might have to spend on a file. This saves them from doing boring and tedious work and most importantly reduces the bill for a client.

Legal AI algorithms have also demonstrated promise in providing non-lawyers with relevant legal information in relatively simple cases. In some situations, an algorithm can provide a non-lawyer with information about their situation and what the likely outcome would be if they were to proceed with their legal action. Empowered with this information, a person can make a decision that is best for them regarding issues like does it make financial sense to hire a lawyer, is this a good settlement offer and what are my rights?


The Conflict Analytics Lab is a research-based consortium concerned with the application of data science and machine learning to dispute resolution. The first of its kind, the Conflict Analytics Lab comprises a global network of experts drawn from across industry and academia including Queen’s University, McGill University, Cornell University and NYU Stern.

In May 2020, the Conflict Analytics Lab launched MyOpenCourt, an open-access platform designed to help millions of Canadians who recently lost their job due to the Covid-19 pandemic. By answering two questionnaires, MyOpenCourt uses artificial intelligence to help workers understand whether they are an employee or an independent contractor and the reasonable notice period they are entitled to upon termination of an employment contract.

Worker Classification

The “Am I an employee or contractor?” tool helps users identify whether a worker is an employee or an independent contractor. The tool asks questions related to the worker’s specific circumstance, which are derived from the traditional Sagaz Test in 671122 Ontario Ltd. v. Sagaz Industries (2001). Once the user inputs the relevant information related to the ownership of tools, ability to subcontract work, and other factors dictating the employment relationship, our algorithm generates a prediction based on the relevant Canadian case law.

Termination Compensation

Similarly, the “Termination Compensation Calculator” tool helps terminated employees identify their eligibility for reasonable notice prior to termination. Once users are deemed to be entitled to compensation, the tool will ask questions related to the worker’s specific circumstances, which were derived from the traditional Bardal Factors in Bardal v. Globe and Mail Ltd. (1960). Once complete, the tool will predict the final award amount likely to be given by a court, which also factors in the duty to mitigate by the dismissed employee.

Access to Justice provides people with free legal information tailored to their specific issues. The team at MyOpenCourt has pulled data points from all of the relevant cases to create algorithms that can predict the likely outcome of a new legal issue. 

In order to facilitate the use of the legal information we provide, our platforms are designed to help self-represented litigants build a case on their own. The tools provide users with a list of relevant case law and the main reasons leading to the AI’s prediction. Self-represented litigants using our tool can compare and contrast their circumstances to legal precedents should they decide to bring the case to court. Our platforms also facilitate out of court settlements by providing a middle ground to begin negotiations. 

Users are also given an opportunity to schedule a free consultation with a lawyer from MyOpenCourt’s partner firms. If accepted, the lawyer would receive the user’s answers, the predicted results of the tool, as well as the relevant list of precedents, to assist with the lawyer’s preliminary legal research.

Check out these platforms at