| > By applying machine learning algorithms to data mined from court judgments... And, with that sentence, this post becomes bullshit. The overwhelming majority of disputes do not reach litigation. The overwhelming majority of litigation does not reach judgment. And then a gigantic proportion of those judgments are appealed, and a non-trivial percentage are overturned. Even at that, only on the order of a single digit-percentage of disputes ever reaches a verdict. This is like judging a hospital-system based on its success-rate for transplant surgery. It's just deeply ignorant of what constitutes the vast, vast majority of the practice of law - even in disputes. This article has no value, whatsoever, aside from a witty aside at a cocktail party about how deeply misunderstood the legal profession is. This is particularly shocking given that litimetrics is a legal service provider. > Although A has not faced B, if both have faced C, then we have some information about the hypothetical A and B matchup. This is the same reasoning that allows one to compare tennis players across different eras. The implication is that the lawyer efficacy, based on judgments, is subject to the transitive property? Sweet mercy that is ridiculous. This post is a catastrophe. |
This is a pretty ungenerous reading of the article. Your complaint seems to be mostly about the generalizability of the model (a legitimate complaint, as you've explained) rather than its statistical validity. It still provides some interesting insights about the performance of firms at trial. Notably, there isn't a correlation between favorable judgments in those cases which have gone to trial and traditional law firm rankings. That's surprising, even if it doesn't generalize to overall law firm "success".