Earlier quoted context omitted.
> To win a discrimination case, you typically need to document a pattern of behavior over time—often a year Where did you hear this? > use ChatGPT to draft calm, non-threatening Slack messages that note discriminatory incidents and keep doing that consistently This is terrible advice. It not only makes those messages inadmissible, it casts reasonable doubt on everything else you say. Using an LLM to take the emotion…
With respect, it seems you haven’t kept up with how people actually use ChatGPT. In discrimination cases—especially disparate treatment—the key is comparing your performance, opportunities, and outcomes against peers: projects assigned, promotions, credit for work, meeting invites, inclusion, and so on. For engineers, that often means concrete signals like PR assignments, review comments, approval times, who gets mer…
>
they will ask an AI to outline relevant doctrines, show how their facts map to prior cases, and suggest the right records to pullThis is correct usage. Letting it draft notes and letters is not. (Procedural emails, why not.) Essentially, ChatGPT Pro lets one do e-discovery and preliminary drafting to a degree that’s good enough for anything less than a few million dollars.
I’ve worked with startups in San Francisco, where lawyers readily take cases on contingency because they’re so easy to win. The only times I’ve urged companies fight back have been recently, because the emails and notes the employee sent were clearly LLM generated and materially false in one instance. That let, in the one case that they insisted on pursuing, the entire corpus of claims be put under doubt and dismissed. Again, in San Francisco, a notoriously employee-friendly jurisdiction.
I’ve invested in legal AI efforts. I’d be thrilled if their current crop of AIs were my adversary in any case. (I’d also take the bet on ignoring an LLM-drafted complaint more than a written one, lawyer or not.)