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Having done some work in the legal AI field, I wonder how this classifier deals with issues of transparency, explainability and ultimately trust? It’s valuable to have some idea of how a proceedings might unfold but from my experience most competent lawyers have a high bar when it comes to trusting any AI/ML output.
I was worried about explainability, too. If the classifier just spat out "INNOCENT" or "GUILTY," it would be useless -- the legal reasoning has to be part of the output.

Looking at the paper, the classifier definitely does output its reasoning:

"The legal issue at hand is whether the 50/50 royalty split in the 1961 contract binds only pre-existing affiliates or if it also includes affiliates that come into being after the agreement..."

This reads like an ad for Arbitrus.ai. It’s copywriting lingo:

> We built one called Arbitrus. We put it through a mini-Choi test and it mopped the floor with the competition

What kind of classifier is this? I mean is it k-NN (for example), or something else?

Even LLMs can be viewed as classifiers, as the paper (ad?) itself admits.

I love the idea of Arbitrus.ai, but they want $2500 a go to test it. I wish they had a demo version to play with.
The margin and line spacing makes this hard to read. Is this how you're supposed to typeset a paper? Some pages have three, maybe four sentences on them.
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