It goes without saying that one of the most critical functions of a law firm is to train its associates adequately. But time constraints and a lack of consistency, as I have previously discussed, make good, sound training of associates problematic in many firms. However, large language models and GenAI, even open models, may offer potential solutions. Provided, of course, that the firm and its partners understand the risks and benefits of these models and how to use them.
The Shortcomings of Traditional Training Methods
Part of the problem with training young lawyers is that, by necessity, it is very experience driven. To paraphrase Abdi Shayesteh, co-founder of the training firm AltaClaro, you can’t learn to swim by reading a book. You have to get in the water. Want to know how to take a good deposition? Watch a good lawyer take some depositions and then take a bunch yourself. Want to learn how to pick a jury? Second chair some trials and then try some cases on your own. This learning through experience was how many of us become good lawyers.
This kind of on-the-job training no longer works so well
But this kind of on-the-job training no longer works so well. Clients aren’t willing to pay for associates to sit in on depositions or trials. Clients aren’t willing to let inexperienced lawyers work on cases. Firms aren’t willing to write off associate time. Partners aren’t as willing to miss out on billable time to shadow and mentor associates on how to practice law. And, of course, there are fewer trials.
The result is more dependence on structured training and the use of handouts, videos, and reading assignments. But a three day workshop or a video doesn’t take the place of hands, in the trenches experience.
Enter Large Language