Curious how they do a “blind” preference test. To any evaluator I’m sure it’s quite clear which answer is AI vs human.
AI outperforms law professors in Stanford Law study
171–180 of 384 posts
Re: AI outperforms law professors in Stanford Law study
#172Earlier quoted context omitted.
I would think that LLMs would be better at avoiding foot-guns. That’s a situation where you have a list of well known rules and potential pit falls, and the work of the lawyer is to apply those to a fact pattern. That’s something that has been hard to automate programmatically, because the fact patterns are similar but different. LLMs, however, seem to excel at applying general principles to differing fact patterns.
I would categorize this in the "expertise that people internalize but never figure out how to verbalize" department, and that is a department we have no way to teach an LLM because if nobody is writing out those unspoken, subconscious rules then the LLM has nothing to read about them in its training data.
> and that is a department we have no way to teach an LLM because if nobody is writing out those unspoken, subconscious rules then the LLM has nothing to read about them in its training data.
I think on the contrary, LLM providers accumulate huge logs of interaction with their users, which elicit that tacit knowledge and mine it and humans cooperate willingly in order to solve their tasks. Just imagine the corpus of sessions for scientific research, education or software development, it is probably the largest such collection ever to exist. Trillions of HITL tokens per day flow into those logs, carrying our perspectives, choices, original ideas and tacit knowledge. I call this the "human-AI experience flywheel". It's the new stackoverflow, next model generation is based on interaction data from previous one.
Re: AI outperforms law professors in Stanford Law study
#173Earlier quoted context omitted.
I've used general purpose LLM AI (e.g. run-of-the-mill Claude, GPT etc) heavily to draft legal documents. The biggest trap is the hallucinated citation. It will easily insert an absolutely authentic sounding quotation from another case that perfectly proves the point you are trying to make, then it'll make up an authentic name for it, e.g. United States v. Shenzhou Electronics Inc or whatever. You can get really comf…
> The biggest trap is the hallucinated citation. It will easily insert an absolutely authentic sounding quotation from another case that perfectly proves the point you are trying to make, then it'll make up an authentic name for it, e.g. United States v. Shenzhou Electronics Inc or whatever. Naive question from an outsider: aren't there searchable databases of cases (with complete text) so that citations could be che…
It depends on the jurisdiction. I'm based in France and all cases here are now freely available online to people and agents [1], but it's very recent for lower courts. However, I recently had to work on Texas case law and we had to purchase access to a (very expensive [2]) database since most of it wasn't public.
[1] https://www.legifrance.gouv.fr/
[2] https://legal.thomsonreuters.com/en/westlaw/plans-and-pricin...
Re: AI outperforms law professors in Stanford Law study
#174Earlier quoted context omitted.
The paper says the professors have a median of 200 comparisons each. It also says they only used 2 models because using more models would require more comparisons and they selected Google models because Google was branded/advertised as being education focused. When you see other models show up elsewhere, that's because they extended the main idea to other models but using LLMs to judge instead of human professors.
Sure, but the biggest problem is they have no statistical significance. Variance is too high. How do you distinguish the signal from the noise? Confidence intervals aren't enough. But is it a surprise law professors aren't great statisticians?
I disagree. 16 isn't necessarily the relevant N here but the number of responses is.
If you have 100 responses from 1 professor, and the AI wins 75% of the time that is very likely a true signal that the AI is better than this prof. It would be incorrect to generalize this to all profs though.
Further, if you sample 16 profs and the AI beats 10 of them you can be fairly certain that the real percentage of profs it beats isn't 10%. Further, when estimating the probability that the AI beats a random prof, it's the relative estimation error that scales with 1/sqrt N. If you have a coin and it lands heads up 16 times, that tells you something quite robust about the coin.
Reasonably estimating confidence intervals at small N and high p is not trivial. But it can be done.
A good heuristic is "add 2 successes and 2 failures" which is due to Agresti & Couli.
See down the page here for source papers:
https://en.wikipedia.org/wiki/Binomial_proportion_confidence...
Re: AI outperforms law professors in Stanford Law study
#175Earlier quoted context omitted.
I've used general purpose LLM AI (e.g. run-of-the-mill Claude, GPT etc) heavily to draft legal documents. The biggest trap is the hallucinated citation. It will easily insert an absolutely authentic sounding quotation from another case that perfectly proves the point you are trying to make, then it'll make up an authentic name for it, e.g. United States v. Shenzhou Electronics Inc or whatever. You can get really comf…
A legal professional can be personally liable for not finding the most recent case-law. The knowledge cut off gap means the models sometimes don't know about the most recent case-law, in a given situation. I've seent his happen multiple times now. Accountants and legal professionals advising clients based on outdated information assembled through chat-gtp, claude and copilot. Professionals drafting letters and missin…
You definitely want your AI to search legal databases, and not draw from "memory". This is where AI offerings from Thomson or Lexis could shine, especially in jurisdictions where case law is not freely available online.
Re: AI outperforms law professors in Stanford Law study
#176I find this study quite suspect. I'd have to dive deeper but there's definitely significant alarm bells that should be going off for anyone reading. Figure 2 (page 6) screams problems. There's only 16 professors (3k comparisons each?!?!) and the professors are all over the place. That's very high variance, suggesting the study has no meaningful statistical power. Poor instructor 16 can't catch a break lol There's als…
But does it really matter? It seems fairly obvious that AI is going to outperform professors. While the studies run, there are three more model releases that change the calculus entirely. I wonder how much we are learning with these studies about what is going on.
Re: AI outperforms law professors in Stanford Law study
#177Earlier quoted context omitted.
I've used general purpose LLM AI (e.g. run-of-the-mill Claude, GPT etc) heavily to draft legal documents. The biggest trap is the hallucinated citation. It will easily insert an absolutely authentic sounding quotation from another case that perfectly proves the point you are trying to make, then it'll make up an authentic name for it, e.g. United States v. Shenzhou Electronics Inc or whatever. You can get really comf…
> The biggest trap is the hallucinated citation. It will easily insert an absolutely authentic sounding quotation from another case that perfectly proves the point you are trying to make, then it'll make up an authentic name for it, e.g. United States v. Shenzhou Electronics Inc or whatever. Naive question from an outsider: aren't there searchable databases of cases (with complete text) so that citations could be che…
It’s a band aid solution because the model can get stuck in a refutation loop, where it argues a point by pulling up a contradicting source ad infinitum. The holy grail, which has not been yet reached, is figuring out how to dynamically align the model to be consistent with all the sources in the first place (and this is a problem of provenance rather than model design)
Re: AI outperforms law professors in Stanford Law study
#178I find this study quite suspect. I'd have to dive deeper but there's definitely significant alarm bells that should be going off for anyone reading. Figure 2 (page 6) screams problems. There's only 16 professors (3k comparisons each?!?!) and the professors are all over the place. That's very high variance, suggesting the study has no meaningful statistical power. Poor instructor 16 can't catch a break lol There's als…
But does it really matter? It seems fairly obvious that AI is going to outperform professors. While the studies run, there are three more model releases that change the calculus entirely. I wonder how much we are learning with these studies about what is going on.
Does it matter if a study is fraudulent or incompetent? Yes.
Re: AI outperforms law professors in Stanford Law study
#179What is the point of this conclusion? That law professors like the tone and verbosity of AI slop? Okay?
Re: AI outperforms law professors in Stanford Law study
#180It is important for society to understand it is not merely programmers and customer support who are at risk of losing their jobs. Clearly A.I can do much more than just program.