As summer arrives and my grading season has ended, I find myself eagerly anticipating some quality time experimenting with generative AI. After a spring semester filled with teaching a course on AI and the Law and conducting numerous prompting experiments, I am ready to continue my exploration.

This excitement is tempered by the sheer volume of AI programs and self-proclaimed experts emerging in the legal field seemingly on a daily basis. It seems that so many say that they are gurus and geniuses and know so much, but I can’t help but feel like a student and that there is still so much for us all to learn and we need much more time before we make proclamations.

Lately, it feels like I’ve been inundated with announcements of programs promising definitive answers and best practices for using generative AI in law. These proclamations often make me scratch my head in bewilderment. As someone who considers himself a perpetual learner, I find these definitive statements somewhat premature. The reality is that the field of AI, particularly generative AI, is still evolving, and our understanding is far from complete. Seriously, we don’t even know “best practices” for human activities, so I’m doubtful we have reach the “best practices” stage on AI already.

In this post, I want to share my thoughts on how to critically evaluate the ever-growing claims of expertise in legal AI. To navigate this landscape, I suggest adopting a 3 Hs approach: Homework, Hands-on work, and Humility.


The first step is to do your homework. It’s crucial to research and understand the backgrounds of those claiming to be experts. What are their qualifications? What kind of work have they done? When did their AI experience and expertise begin? By digging deeper into their credentials and experiences, you can better determine the reliability and value of their insights.

Hands-on Work:

Next, put in the hands-on work. There is no substitute for personal experience when it comes to understanding generative AI tools like GPT-4. Experiment with these tools, run your own tests, and see firsthand what they can and cannot do. This practical experience will not only enhance your understanding but also allow you to critically assess the claims made by others. I consider this approach mandatory and it is as close as I come these days to calling something a “best practice.”


Finally, approach this subject with humility. Despite the rapid advancements in AI, we are still in the early stages of understanding its full potential and limitations. The legal field, with its unique complexities and nuances, presents particular challenges for AI implementation. A humble approach acknowledges that we are all learning and that there is still much to discover. And a key part is being willing to learn from those outside the legal profession.

I was genuinely surprised to see self-proclaimed legal AI experts making sweeping statements about what ChatGPT-4.0 could do within 24 hours of its release. A bit of a rush to judgment?

I still have a lot of work to do to fully grasp the capabilities and implications of these tools, and I am looking forward to that work.

As we venture further into the era of legal AI, let’s prioritize continuous learning, critical thinking, and a willingness to admit when we don’t have all the answers. By doing so, we can separate the wheat from the chaff and truly advance our understanding of how AI can benefit the legal profession.

If you are in Michigan and are interested in hearing more about my current approaches to AI and experiments, I’ll be speaking at the State Bar of Michigan’s Great Lakes Legal Conference (https://www.michbar.org/GLLC) on June 14 and 15 on Mackinac Island.

NOTE: The phrase “lions and tigers and bears, oh my!” is a famous line from the movie “The Wizard of Oz.” In the movie, Dorothy and her friends chant it as they venture into a dark and unknown forest, expressing their fear of the potential dangers ahead.

[Originally posted on DennisKennedy.Blog (https://www.denniskennedy.com/blog/)]

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