Anticipating Curveballs

I testified this week and added something new to my preparation routine that proved valuable.

As Jarrod Carter explained during his appearance on the Data Driven podcast, detailed preparation is critical to ensuring you can hit any curveball, knuckleball, or fastball thrown to you on the stand.

“That’s where the experts make their money. If they’re really doing their job, and if they’re really confident and capable, they can handle the curveballs because they’ve already anticipated that curveball."

To get in the best position possible to get the bat on the ball, I typically spend days preparing with the goal of having key testimonial and analytical details memorized and ready to go.

I also anticipate and prepare for potential cross-examination questions. That process is often informed by questions raised during my deposition, discussions with the client, and my prior experience.

Nowadays, though, AI is an excellent tool for brainstorming potential cross. The materials you're willing/able to upload to a large language model (LLM) depend on your company policy, the case, and the AI platform’s terms and conditions.

But if that bridge has been crossed, and after appropriate redaction, modern LLMs can quickly digest reports and depositions and generate excellent cross-examination questions you might not have foreseen.

Moreover, it’s becoming increasingly likely that opposing counsel’s cross-examination will actually be informed by an LLM. This exercise offers an opportunity to glimpse the potential future.

Interestingly, the first line of the questioning during my cross-examination this week was also the first cross-examination question posed by AI. Coincidence? Who could know.

As detailed in this edition of TtP, proceed with caution. It’s still the Wild West, and as far as I can tell, a consistent set of best practices for experts has yet to emerge. I’m hoping to get an AI pro on the podcast before long to offer some expert advice.

Thanks for reading, keep exploring!

Lou Peck

P.S. I dedicated 100s of hours this year to developing an Applied Video Analysis course, and it’s finally available to the public! Click here to learn more.