John Lemieux is a Partner in the Corporate and Commercial Group at Dentons Canada LLP. This article was written as a requirement for Prof. Pina D’Agostine & Dr. Aviv Gaon’s “Selected Topics in Privacy and Cybersecurity Law” course with Osgoode Professional Development.
Access to justice in Canada is an acute issue requiring urgent action not only from governments but from the legal practitioners in this country charged with an obligation to “improve justice and to continuously create the good.” There are a multitude of avenues for reforming the Canadian justice system in order to improve access to justice, and among these is the integration of artificial intelligence (AI) into our dispute resolution processes in order to decide legal disputes in an efficient, cost effective and expeditious manner.
It is not proposed that AI would be used in every instance to resolve a legal dispute. Rather, AI could be utilized to assist the significant number of Canadians who are unclear as to their legal rights and of the view that seeking redress through the formal justice system will be too costly and time consuming. More specifically, AI can be deployed to help the growing number of self-represented litigants navigate the justice system, and also assist low-income households explore avenues of recourse they may not have pursued without this type of technological assistance.
Darin Thompson proposes the adoption of a basic AI technology, with the simple goal of helping individuals he refers to as “non-expert users” to manage disputes and the justice system in general more effectively. Thompson conceptually describes what he refers to as a Justice Pathway Expert System (JPES), which he imagines as an AI touchpoint for non-expert users needing to engage with the justice system. The design of the JPES is that of an ‘intelligent questionnaire’ interface. The AI system will prompt the non-expert user with a series of questions corresponding to a battery of prepared answers. As the non-expert user works through the questions, the JPES begins doling out information and recommendations that can be acted upon. Thompson’s description of the process is that of (1) an initial problem diagnosis, (2) the delivery of specific information germane to the diagnosed problem, (3) the provision of recommendations for tools or resources that the non-expert user can access and utilize to help consider methodologies to best resolve the problem, and finally (4) a ‘streaming and triage’ functionality that can help guide the non-expert user towards the perceived best resolution process to pursue, whether that be as simple as a mediated settlement discussion between disputing parties or the commencement of a court action.
As noted above, the JPES is not conceptualized as an AI that could be utilized to assist with complex matters. Indeed, it is generally accepted that for the time being AI is unlikely to replace human adjudicators in anything but simple legal matters. The value of the JPES concept is that it could be a meaningful resource for individuals without the necessary expertise or financial resources required to retain and instruct legal counsel to consider and map out a dispute resolution pathway ultimately promoting and enhancing access to justice in Canada.
 Trevor C.W. Farrow, “What is Access to Justice?” (2014) 51 Osgoode Hall L.J. 957 at 983.
 Ibid., at 965.
 John Zeleznikow, “Can Artificial Intelligence and Online Dispute Resolution Enhance Efficiency and Effectiveness in Courts” (2017) 8 International Journal for Court Administration 30 at 30.
 Darin Thompson, “Creating New Pathways to Justice Using Simple Artificial Intelligence and Online Dispute Resolution” (2015) 2 IJODR 4 at 5.
 Ibid., at 9.
 Ibid., at 16.
 Rachel E. Stern et. al., “Automating Fairness? Artificial Intelligence in the Chinese Courts” (2021) 59 Colum. J. Transnat’l. L. 515 at 517.