But the outcome of high-stakes commercial litigation is much more complex than “win or lose.” Most cases settle, so the ones that result in published legal judgments which can be fed into a machine learning tool are an unrepresentative minority. Participating in this kind of litigation also costs millions and attracts public attention, leading to innumerable second-order effects (eg. public relations damage, law reform) that are hard to predict and may be more significant than whatever specific legal decision a judge makes. So being able to put a numerical probability on the legal opinion “we think the company has a good chance of winning this case” may not be that helpful.
But the outcome of high-stakes commercial litigation is much more complex than “win or lose.” Most cases settle, so the ones that result in published legal judgments which can be fed into a machine learning tool are an unrepresentative minority. Participating in this kind of litigation also costs millions and attracts public attention, leading to innumerable second-order effects (eg. public relations damage, law reform) that are hard to predict and may be more significant than whatever specific legal decision a judge makes. So being able to put a numerical probability on the legal opinion “we think the company has a good chance of winning this case” may not be that helpful.