No sector in 2019 is entirely isolated from the application of scientific knowledge for practical purposes like higher accuracy or greater cost efficiency.
But the legal profession tends to resist such moves when they might result in fewer hours billed by attorneys.
Consider an artificial intelligence company whose founder I met earlier this year:*
His staff lawyers and software engineers collaborate to “teach” an AI-based system in the fact patterns found in selected, high-frequency lawsuit categories.
Like slip-and-fall liability on business premises, or an employment claim for sex discrimination.
They also “train” this AI-based system in the court cases and statutes of the state whose laws will govern the suit.
When one of his client companies / software users is served with a lawsuit — by a document that the legal system calls a “complaint” — they designate local counsel to represent them in the state where suit has been brought. By law, local counsel has to respond with specified documents.
These specified documents consist of tedious replies to alleged facts; point-for-point rebuttals to legal doctrines; and meticulous identification of information and evidence that the lawsuit recipient has the right to demand of the party who brought suit against them.
As any lawyer involved in litigation can tell you from personal experience — myself included — this is “grunt work”.
But it has to be done right. And it has to be done by an attorney.
In the “answer”, you’ve got to avoid making the wrong response to factual allegations. And you can’t afford to miss an “affirmative defense” that might get your client off the hook. Finally, you don’t want to omit anything important from your document demand or other “discovery” requests.
Otherwise, at best, you’ll create unnecessary work, and incur expense, in correcting these errors. At worst — you’ll prejudice your client’s case if the judge refuses to cut you a break and let you correct your mistake.
…
This is where this founder’s AI company comes in.
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Managing Legal
