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AI outperforms law professors in Stanford Law study

law.stanford.edu

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Re: AI outperforms law professors in Stanford Law study

#161

Post by tomjakubowski »

HappMacDonald wrote: post #71
rayiner wrote: post #22

Earlier 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.

This is often called tacit knowledge. https://en.wikipedia.org/wiki/Tacit_knowledge

My favorite example of this is knowing how to untangle a big pile of cables. There are robots now which can untie a single knotted cable, but I don't think any can do a pile of cables yet. https://www.youtube.com/watch?v=vp-94rsherE

Re: AI outperforms law professors in Stanford Law study

#162

Post by em500 »

qingcharles wrote: post #152
causal wrote: post #7

As a software engineer I have some intuition for what the risks are of letting agents do some tasks vs others. I don't have a similar intuition calibrated for what could go wrong when asking AI to draft a legal document. Some things seem harmless, i.e. drafting a will, but I don't really know- our legal system is notoriously rife with footguns.

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 checked automatically, either by the same or an independent agent?

Re: AI outperforms law professors in Stanford Law study

#163

Post by dgellow »

knollimar wrote: post #33
causal wrote: post #7

As a software engineer I have some intuition for what the risks are of letting agents do some tasks vs others. I don't have a similar intuition calibrated for what could go wrong when asking AI to draft a legal document. Some things seem harmless, i.e. drafting a will, but I don't really know- our legal system is notoriously rife with footguns.

I'm afraid since claude cheats in benches, what will it do with law?

The same in every other domains. It’s happening now, not in a future tense

Re: AI outperforms law professors in Stanford Law study

#164

Post by BartjeD »

qingcharles wrote: post #152
causal wrote: post #7

As a software engineer I have some intuition for what the risks are of letting agents do some tasks vs others. I don't have a similar intuition calibrated for what could go wrong when asking AI to draft a legal document. Some things seem harmless, i.e. drafting a will, but I don't really know- our legal system is notoriously rife with footguns.

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 missing recent case-law which handles their exact case. It's unreliable.So it can save you some work; but it can't save you all of the work. And in some cases its mistakes really force you to redo all the work, and more, to be thorough and have confidence in the result.

Re: AI outperforms law professors in Stanford Law study

#165

Post by eunos »

qingcharles wrote: post #152
causal wrote: post #7

As a software engineer I have some intuition for what the risks are of letting agents do some tasks vs others. I don't have a similar intuition calibrated for what could go wrong when asking AI to draft a legal document. Some things seem harmless, i.e. drafting a will, but I don't really know- our legal system is notoriously rife with footguns.

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…

Seems companies like Thomson Reuters or other legal services have incentive to build LLM with RAG over legal cases texts and robust hallucinations detection on reference

Re: AI outperforms law professors in Stanford Law study

#166

Post by tomjakubowski »

keeda wrote: post #154
runarberg wrote: post #125

Earlier quoted context omitted.

The study was conducted by Stanford’s HAI institute, which receives heavy funding from Google (how much I couldn’t find because they don‘t publish their donations in a place I could find it; but I suspect it is alot). And the authors did not declare a non-conflict of interest at the end of the paper.

Wait, where are you seeing the link to HAI? TFA mentions something called "liftlab" which seems to be something under Stanford Law School and separate from HAI. The study has more than a dozen authors from as many different universities but HAI is not mentioned.

The leader of the study, Julian Nyarko, is Associate Director and Senior Fellow at HAI. I can't say whether that means the study was conducted by HAI, but there is at least a connection to it. https://hai.stanford.edu/people/julian-nyarko

Re: AI outperforms law professors in Stanford Law study

#168

Post by [deleted] »

runarberg wrote: post #81
chewbacha wrote: post #40

My best guess is that Gemini was trained on the textbooks that the questions are meant to test against, thus they are probably better at explicit recall of those questions or related questions. This is a pretty limited introductory course based on what it says in the methods of the paper itself.

That and the research is done by Stanford’s HAI institute with an obvious bias and the paper is curiously missing a conflict of interest statement. EDIT: just found out that Google is a major donor to HAI. So this research is at least partially funded by Google. Which is probably the reason the authors fail to declare no conflict of interest.

[deleted]

Re: AI outperforms law professors in Stanford Law study

#169

Post by himata4113 »

There is quite a simple solution for many of the problems described in the comments: Make drafting legal papers a defined interface.

If you think about it and extract sematics of any law you get something that looks familiar, sort of like code. Of course there's some complexities where certain phrases can mean different things, but legal papers in a way are written like they're programming languages already especially when it comes to law.

First we would have to define a language that can handle ambigious operations and we alread y have this with programatic proofs where n should land in x. So in the end I'd assume it would look something like this in a two party dispute:

This is very simplified and pseudo like language, writing out a full contract would be as long as a real contract.

     DEFINE DEFENDANT "A Corp"
     DEFINE PLAINTIFF "B Corp"
     DEFINE CONTRACT  CONTRACT(PLAINTIFF, DEFENDANT, 3054-41-95)

     // attaching extracted requirements, definitions and obligations of contract

     FACT   PLAINTIFF delivered(goods) ON 7054-34-99
     FACT   DEFENDANT paid(0) OF CONTRACT.amount

     CLAIM  breach WHEN obligation(DEFENDANT, "pay") IS NOT satisfied

     PROVE breach:                                                                                                                                                                  
         REQUIRE  PLAINTIFF performed                                                                                                                                               
         REQUIRE  DEFENDANT.paid
Then you would run a proof based LLM to generate it into target language and since we already had an example of this from one of the AI labs we know it works. Automatic citations and supporting proof would be automatically populated from reviewed legal -> DSL extracted papers as supporting evidence.

I am sure that many AI labs are working on something similar already and we will see something like that in the near future as proof based llms evolve.

Re: AI outperforms law professors in Stanford Law study

#170

Post by xyzal »

This contradicts my anecdata.

Recently, I tasked Opus 4.6 to study a new Czech building permit law in conjunction with some waste disposal regulations and the result was disappointing. The model could not stop drawing conclusions from obsolete regulations in its training dataset, even when given the fulltext of the new law. The usual "you are totally right" also applied and its conclusions were most of the time obviously wrong even to a human with cursory knowledge of the subject.

I ended with studying the relevant regulations myself over the weekend.

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