A consensus is emerging in law schools across Canada and the US that AI has no place in teaching the core curriculum, because it impedes student learning, especially in first year. Schools are beginning to follow the University of Chicago’s lead in banning AI in first-year core courses. Some profs are also banning laptops in classrooms — taking every precaution to shield students’ developing minds from the corrosive effects of AI.

Michael Plaxton, one of the leading voices in Canada thinking through the many challenges AI poses to legal education, crystallizes the argument:

“The case for law schools must be . . . [more]

Many generative AI tools are relatively easy to access and use. For example, no technical expertise is required to pull up and type a prompt into ChatGPT, and the most basic version is free. This reality has led to a significant amount of “shadow AI” use within organizations; that is, uses of AI that are not formally approved or are even contrary to formal policies. Concerns about shadow AI commonly arise in the context of private companies, with some studies indicating that over 80% of workers report using unapproved tools at work. Much less discussed – and worthy of far . . . [more]

Over the past several years, artificial intelligence has moved steadily from the margins of organizational life toward the centre of ordinary operations. It now appears throughout the systems organizations rely upon and the work their people perform, frequently arriving without any deliberate decision to adopt it. For a growing number of organizations, the question is no longer whether artificial intelligence will appear in some form. It has already arrived, and that development carries real implications for boards of directors.

I have spent a fair amount of my career in and around boardrooms, working on questions of corporate governance, non-profit governance, . . . [more]

At a conference of law teachers at Western in June, I took part in discussions among professors and lawyers about whether facility with AI should be a core competence in a Canadian law degree at this point in time. This gave rise to larger questions about whether law profs now have an ethical or pedagogical duty of some kind to familiarize themselves with AI and develop methods of teaching students how to use it effectively. This, in turn, pointed to the even larger question of what it means to be a competent lawyer in the age of AI.

Put another . . . [more]

Earlier this year, a motion at the Ontario Superior Court paused while everyone in the room went looking for a quotation. The factum on one side quoted a decision of the Court of Appeal, and opposing counsel could not find the quoted words anywhere in that decision. He suspected the factum had been drafted with AI. The judge called a short recess, so the party who filed it could go and find the passage.[1]

The citation was correct, and anyone who looked it up would have found exactly the case named. In this instance, AI produced a fake quotation . . . [more]

Take a moment to thank Eric Appleby, founder of Maritime Law Book, because the Canadian legal AI future announced today by Clio is only possible because Eric was sufficiently frustrated by the lack of access to New Brunswick case law in the 1960s that he decided to start a legal publishing company. No Eric, no MLB. No MLB, no Canadian case law in Clio and no next wave of Canadian legal AI.

You know the saying attributed to Nelson Mandela that begins “the best time to plant a tree is 20 years ago?” Well, the tree now bearing fruit is . . . [more]

Those familiar with my writing will know that I usually write about artificial intelligence in terms of regulation, governance, and risk. This piece is a slight departure. What follows is a set of reflections for young professionals working in AI, or considering work in the field, at a moment when the pace of change, the visibility of the space, and the pressure to find one’s place in it can easily create more anxiety than clarity. I use the phrase “young professional” in a broad sense. It follows a familiar tradition in reflective writing, but I do not mean it strictly . . . [more]

In recent posts, I have been skeptical about using AI to generate certain kinds of legal writing. I’ve drawn a distinction between using AI to edit or revise a document and using it to create one from scratch.

I take the view that even if you can avoid hallucinations, using AI to create a court brief is likely to raise issues of competence. And I’m not convinced it is well suited to drafting opinion or demand letters, because it leads to writing that comes across as flat and robotic, verbose, and overly formalistic.

But there’s another view out there . . . [more]

In the midst of the ongoing concerns about hallucinations, particularly related to citations in documents filed with courts, I wonder if the particular focus on AI generated errors, and the penalties that have been imposed in response, are at least partly due to perceptions of these tools as cheating or aesthetic ideas about how “real” legal writing should happen. And I query the rationales for recent instances of judges issuing sanctions against people who have inadvertently included them. It seems that mistakes in AI generated documents are treated differently from mistakes that can and do appear in any piece of . . . [more]

Michael Geist had a lawyer on his Law Bytes podcast recently to talk about how AI is radically transforming his practice. For this long-time listener of one of the best law podcasts out there, the episode with New York lawyer Zack Shapiro was among the two or three most interesting and informative episodes I think Geist has ever done.

As someone who follows developments in legal AI closely, I found Shapiro’s insights into how to make the best use of AI outstanding. This is an episode that anyone interested in where law is headed — and concerned with not being . . . [more]

Over the past several months, I have had the opportunity to speak with leaders across a range of sectors about artificial intelligence. These conversations have taken place in boardrooms, universities, professional development seminars, and informal gatherings following presentations. The contexts vary and the industries differ, however a common pattern has begun to emerge.

The organizations I encounter are not dismissive of AI. Quite the opposite. Most are experimenting with generative tools, reviewing internal processes, or considering policy development. Many have established working groups. Some have launched pilot projects. Others are waiting for clearer regulatory direction before moving further. At first . . . [more]

What many of us in law, legal education, and other fields still want to know at this point is: what is AI really good for? What does it do reliably well and better than we could do on our own? And when we use it for those purposes, what risks do we take on?

In the early days of ChatGPT, those risks were clear. AI hallucinated authorities and generated biased output grounded in its training data. But as models have improved and we’ve learned to guard against these problems, those concerns have become more manageable.

A different and more subtle . . . [more]