Just like breaking crypto in the age of cloud is more about cost than time, this will lead to legal attacks based on the same principle. The biggest wallet wins.
This was already always the case. If anything, making this more accessible will reduce the barrier to entry for whether or not it's worth your time to take on a case. Instead of 50 lawyers spending 100s of hours on a case, you can have 1 or 2 lawyers + Astra working on it and if there's a case you can add more real lawyers.
Many lawyers are owners/partners compared with software engineers who are more like cogs in the machine. They also bill hourly/contingency per case compared to engineers who are salaried. If a partner in a firm thinks they can take on more cases because of AI assistance then they will because that's just more money in their pockets.
With regard to certain legal questions this has always been the case. AT&T Fought the US Government for 20 years and eventually won because the government gave up. Without some kind of national anti-SLAPP law we're all one irritated oligarch away from having our lives financially ruined.
I am curious what level of trust established law firms treat LLMs with.
Will these models eventually replace all knowledge work, leaving lawyers, doctors, product managers, software developers, and others out of a job?
If the benefits were shared across humanity, that could bring us closer to utopia. My worry is that we’ll instead end up with a handful of even wealthier billionaires and millions of people out of work.
I mean that's what all of these execs are openly telling everyone: they want you out of work, they want their ai to be the one to bring the world to it's knees, they want to surveille every second of your day, they want killer drones to use, they want to lay all of your cities to rubble and build "paradises" on top of them like in gaza.
They also openly tell you what they are afraid of btw: collective worker power. something that is massively lacking in our industry, although i feel like it would be one of the easiest industries to unionize in terms of # of workers.
Interesting interview I just watched about how powerful and dangerous these "wishes" or "prophecies" are especially in the hands of the ultra-wealthy: <a href="https://www.youtube.com/watch?v=eR7grHa1NR0" rel="nofollow">https://www.youtube.com/watch?v=eR7grHa1NR0
> Will these models eventually replace all knowledge work, leaving lawyers, doctors, product managers, software developers, and others out of a job?
Effectively yes, in the current forms. Those professions will likely evolve, but the traditional forms (ie writing code by hand, writing law filings by hand etc) are all dead.
in that case, legal cases would just come down to who has more compute lol. Many times cases win on their merits, but we've also seen evidence where overwhelming legal pressure can influence cases.
May I just note that there are other jurisdictions on this planet that are less money-biased than than the US one but will be disrupted by law-LLMs as well?
It seems much more probable to me that these LLMs will make good things worse than that they will make bad things better.
Writing a brief by hand isn't the knowledge work of being an attorney, it's knowing what to write. The writing it down is the most trivial part.
If we have enough energy and raw materials to keep building, yes, it will be an utopia made real. But if there is energy scarcity, then other two outcomes can arise.
Doubt it. When someone can go to Astra MD for 75% of what they used to go to the doctor for, then the remaining doctors only have 25% as many visits. When doctors only have 25% as many visits, they have to compete on price and they make less per visit.
Same argument for plumbers. Everyone always jokes about what a good time it is to be a plumber. But what happens when all the software engineers turn to plumbing? Suddenly it's not such a good time to be a plumber anymore.
What happens when the AI makes a mistake with a diagnosis? I can hear it now 'Oh how perceptive you are, yes that pain in your knee could have been a torn meniscus'.
Genuinely wondering (aka not snarky): Has anyone found frontier models to provide useful research in the context of European civil law systems?
Your comment made me wonder if there are any halfway-acceptable model benchmarks for law tasks? Specifically I’d love to know how the frontier models’ abilities compare between common law vs. civil law systems. My guess would be that an AI in a common law context should have a clearer idea of how a specific case is interpreted/accepted by (common law) practitioners, whereas trying to rely on AI in a civil law context, like Germany, can be daunting. In a few Germany-specific recent examples, the models feel like they present only (maybe too stubbornly?) the “civil law”-based laws. All while negating much of AI’s research benefits because civil statutes are portrayed as being absolutely accurate, binding, and their enforcement (and thereby the legal reality) being uniformly applied. Am I making this interpretation up? If so, how can I prove myself wrong?
I don't know of anything that is working yet, but I know some people working on it (intentionally vague).
Roman law, on which the legal systems of Germany, most of Europe, Turkey etc. are based relies more heavily on statutes than Anglo-American case law, but cases do play a role there, too. That's why a practically useful system also needs to have access to court decisions, commentary etc. - and while the statues are in the public domain, a lot of the other knowledge is owned by specialist publishers (such as: C.H. Beck, Nomos, Mohr Siebeck, De Gruyter, Otto Schmidt, C.F. Müller, Manz, Verlag Österreich, Schulthess, Stämpfli, Dalloz, LexisNexis, Lefebvre Dalloz, Giuffrè Francis Lefebvre, CEDAM, Giappichelli, Il Mulino, Aranzadi, Tirant lo Blanch, Marcial Pons, Dykinson, Tecnos, Lefebvre, Almedina, Gestlegal, AAFDL, Kluwer, Boom juridisch, Wolters Kluwer, Larcier-Intersentia, Anthemis, Sakkoulas, Nomiki Bibliothiki, Universul Juridic, Hamangiu).
Internationally, legal systems appear to undergo a sort of convergence, which means statutes increasingly matter in the U.S. and cases increasingly matter in European law (according to a law partner friend).
Hi,
As for benchmarks for law tasks: I also have a concern regarding how the more popular benchmarks (like the tasks in Harvey Legal Agent Benchmark) can accurately reflect actual work done by lawyers. Not only in civil law systems, but also in non-BigLaw type of work areas.
Most of the law tasks should inherently reflect the legal system they are based on. It is an oversimplification that lawyers in one country tend to do the same legal work as lawyers in another, that's a form of dishonest framing from LLM providers working in this area (it is that important for them to be able to scale and disregard traditional fragmentation of the legal services).
The legal systems of common law countries are quite similar in both how they do legal training and in many areas that are important for business. Like in contract law or tort. That means not only similar concepts and foundations (things first taught to law students), but also a similar approach to what is seen as a legal problem, and what kind of answers people expect from a lawyer. Also, what they understand under "legal research" - what do you actually research and what is expected from a qualified lawyer to know by heart, how are you expected to find the legal default in a detailed question, how certain that default is, what is up to professional judgment.
But even the differences within common law systems is huge in other areas that go beyond these basics. Like those affected by statutes, codes (like CFR or NYCRR) or even local regulations etc. The popular legal benchmarks do not dare going into these more detailed legal work directions. And these laws change frequently, and they are very different from one jurisdiction to another, even within the US, let alone in other countries building on English legal traditions.
(Nobody I know of is building a benchmark that affects these areas of law.)
And the diversity is even bigger within legal systems lumped together as "civil law systems". Even those based on Roman law, or on German jurisprudence in the 19th century... There is not much common in how French and German students study law, even if both are members of the EU and many areas of law are harmonised or subject to the same legal acts of the EU and the same EU Court of Justice.
If your LLM has access to up to date legal databases of those countries, commentaries etc., the answers are still surprisingly useful in research. That said, no professional should rely on those LLMs that merely use public legal databases, scraping latest laws and cases via self-operated MCP servers.
I think the main difference is how lawyers from a civil law system use the LLMs compared to someone from a common law system - and that is based on the different training they receive as law students, how they see "law" etc. Maybe there is no such a thing as absolute accuracy in the civil statutes either, but at least civil law lawyers have a stronger notion of "law is knowable". There is a higher likelihood of having one "correct" answer, even when talking about more lifelike, detailed questions.
(I'm qualified in both a civil and a common law system but not specifically in German law.)
So those lawyers will likely want to know about the likeliness, strategies to adapt, and overall mitigations for hallucinations considering that. It might be helpful if the company launching this product including such information in their blog post rather than ignoring it in a field with such a high cost of getting it wrong.
Does hallucination matter for this application? We've moved beyond raw recall being that important, it seems like for law specifically all relevant facts will be cited and checked easily by humans.
> all relevant facts will be cited and checked easily by humans
I've talked to a lawyer about how they handle this. They do indeed double-check everything, since it'd be embarrassing (or worse) to send hallucinated statements to opposing council or to the court. They still find the assembly a huge time saver
But based on stories in the news on the subject, not everyone has this same level of diligence
Sure but just like generating 100x more code, someone has to review it. So you are wasting everyone in court's time (defendants, prosecutors, judges, staff) by making them parse through what is quite often a bunch of hallucinated slop. Time that could be much better spent on parties who prepared and reviews their own arguments.
The lawyers I know are very fixated on the problem of hallucinated case citations which is amusing to me as a onetime programmer, since case citations have a well-defined syntax and would be relatively easy to check programmatically.
Which makes it all the more bizarre that LLMs have this problem. Claude Code runs the code it generates through a compiler, why can’t an LLM run its product through a cite checker? I’ve seen LLMs fabricate citations.
Interesting to see the callout to companies like harvey in the post itself as consumers rather than competitors? I guess openai isn't quite willing to step into those customer relations themselves?
I already use them for that, they are pretty excellent at it. Much better than the terms of use generator products that used to exist. That said, nobody cares to sue your business for the most part until you're big enough to be worth it. By that time, you'll have a team of legal analyst to assist you... or agents should I say.
Then again, nobody will have money to buy anything at this rate, so in all liklihood, this is a total non-issue.
I'd expect they could indemnify you against hallucinations or similar if this gets good enough for that to be a very rare occurrence? Or you could buy insurance on it that's cheaper than hiring a lawyer (not a high bar to clear). I wouldn't rely on it currently, though.
The product isn’t meant for you or me it is for lawyers. If you can’t take on personal liability for a badly written contract then you shouldn’t be using it.
People that are saying OpenAI is screwed because a lack of profit, I'm not of that opinion. They are encroaching on every industry they can. They have name brand recognition, a huge user base and are showing they can be a valuable tool to all types of businesses.
As much as I hate to see it. They are now threatening industries like Engineers, Game Developers, Accountants, 3D modelers, 3D animators, Video Production, Audio Production, Therapist, Tax Auditors, Journalists, Authors, Artists, Mathematicians, Product managers, Every type of analyst and pretty much any other job that can be done behind a computer screen.
I used ChatGPT the other day to resink a CPU with termal paste, replace a PSU in my PC and snake my kitchen sink from the wall. I didn't exactly need it's help but wanted someone looking over my shoulder so to speak. It can help you repair all types of stuff, but as far as county / building codes and such, that probably isn't far off. It seems to understand things quite well.
By that point money ceases to have value, because the value of money comes from the motivation it gives people to work. If AI does everything, then money is useless (unless AI like money for some reason).
There will still be a need to distribute and exchange ressources, goods and services.
Real estate, food, energy, mobility.
That will be done with money. Or violence. Either way, a scary future to people when labor doesn't provide any value. Elon promises abundance, but what can he do against greed?
Yeah could get interesting. Things like legal, programming, math, etc. are going to be relatively cheap / free. Meanwhile something like natural resources, building things, yardwork, etc. may go up in value. Or perhaps we end up with a relatively "spiky" economy since 90% of people are just doing physical jobs (the only human jobs with value), and the AI owner class of course gains all the value from intellectual products (with value diminishing towards cost of electricity). Thinking as human value may be roughly as valuable as it ever was (which is to say nearly non-existant other than the ability to solve an immediate physical problem). Might also be that physical strength and stamina are the highest value mating traits, since they will be able to protect and provide. Physically weak intellectual types will have little value since they can't out-think the machines, and they also can't provide for a family by doing valuable physical tasks. IQ overall begins to drop as mating favors intelligence less and less, as it can actually be an impedance to being productive.
For a short time in history, the ability to obsessively focus on intellectually interesting abstract concepts was highly lucrative, but just as quickly we returned to the laws of nature: those who can lift and move succeed, those who can only think are automated out of existance.
We go from a species increasingly seeing themselves as "brains with bodies" to "amazing bodies with weak brains". The limitation of robots and AI in the physical realm, power hungry, mobility limited are contrasted with human values: energy efficient, highly mobile and dexterous, extremely good strength/speed/size ratios. The brain on the other hand, while energy efficient, is completely outclassed and seen as we see our swimming/jumping abilities: a novelty for sports, but nothing we seriously consider a defining human trait.
The smartest humans can fill weekends with novelty pursuits like building circuits, games, programs, etc. But they are about as useful as whittling and hobby woodcraft, something to pass time, but ultimately of no economic value.
there are always be next frontier of problems which require creativity, unless AI become supersmart completely make humans redundant in all cognitive functions.
Most HNers are clueless that if you have Top Talent + Capital you already have an insurmountable moat. OpenAI, SpaceX, Anthropic all have that and none of the regular guys can compete against them (if they choose to attack that industry)
<a href="https://en.wikipedia.org/wiki/Productivity_paradox" rel="nofollow">https://en.wikipedia.org/wiki/Productivity_paradox GDP does not grow with computers, why should it grow with new software, i.e. genAI?
Creating virtual products get cheaper, so shouldn't it even decrease if everyone vibe codes their app for less than a dollar instead of hiring a dev team for 50k or ordering a white label app or spending 3 dollars to buy an existing app?
Why the hell are they not fighting fire with fire? This is not sustainable. But it is annoying that the AI labs get to play arms dealer, selling to both sides.
It'll be like radar detector detector detectors, which were a thing for a while. Each side (cops, speeder) buying detectors to detect the detectors.
They don't have a choice. If you're a firm and you work with IE a bank, the bank uses AI, their whole supply chain uses AI- your counterparty uses AI- it's a classic arms race with even more social pressure involved (since daily news keeps banging on about AI).
you could probably write a cool little gotcha of an SF short story about a barren wasteland of a planet that keeps broadcasting out legalese that's revealed to just be LLM chatbot lawyers pedantically arguing with one another about xeno legal doctrine
The legal system, which is a machine/technology by itself, will be eaten out. I wonder what will replace it. Botnet law arbitrage? – Personal assistants constantly negotiating with each other to avoid permanent civil lawsuits?
the cost of making a legal argument can collapse while the cost of reaching an enforceable, legitimate decision may go higher, which will gate the "justice" system even more.
You presented the concern from my adjacent comment perfectly (“LLM performance: common law vs civil law” essentially). So is AI possibly just growing the “Reverence for Professional Experience” factor that plays such a big role for legal compensation here in the US?
Why stop there? The bottleneck is not some immutable force of nature. The number of judges is determined by legislative action. It is within the Senate's power to allocate new judicial seats, and likewise at the state level with the equivalent lawmaking body. Why don't they do so?
Because federal district court judges have a tremendous amount of power. You both don't want 10,000 of them running around and you don't want to water down the qualification for the position--if you did do that, then that would devalue their judgments, everyone would appeal, and you'd just shift the bottleneck up to the appellate courts.
At the end of the day, litigation is conflict resolution. You don't just need a decision, you need a decision from someone authoritative enough to bully Fortune 500 CEOs into submission to accept the judgment.
I find the idea that people can use LLMs to exercise their rights as citizens appealing however. Many people aren't aware of the rights they have, and LLMs are pretty good at surfacing some stuff without having to pay lawyers. Having to hire a lawyer is imo actually a huge way of gatekeeping people from exercising their rights. I heard a lot of local German public institutions are currently being flooded with people arguing their case with the help of LLM that they previously weren't really realistically able to do. So I don't see it all as bad.
>are pretty good at surfacing some stuff without having to pay lawyers
They are also really good at making stuff up as evidenced by the many, many, many examples you read in the news about actual lawyers using AI to write briefs that are full of errors and hallucinations.
In civil courts, you'd likely get more sympathy from a judge if you represented yourself and admitted your lack of understanding, rather than try to appear as someone you're not because you wrote some prompts and copied the output.
Current court systems around the world are just not built to handle the flooding of cases from the citizens.
The stupidest analogy is open source projects having a hard time accepting LLM generated PRs from the masses, because review process is the bottleneck.
No idea how to fix this, to be honest. In coding world, with some mental gymnastics, I can see code not being reviewed by people anymore. In courts, things generally have more consequences, and you can’t really roll back decisions that easily.
Then the solution is to add AI to the courts as well. Or something else, if you don't like AI. But definitely not limiting the right of the people to sue.
I don’t know in the USA but in France, if it’s deemed that you launched a lawsuit knowing very well it wouldn’t succeed, you are susceptible to get a 10k€ fine. Even jail in serious cases.
Yes. And you(r lawyer) can collect lawyer's fees and you can be made to pay the court fees, if you lose.
IME the American legal system is set-up to discourage litigation, though. A common tactic is to bury your opponent in the threat of heavy damages or jail-time to get them to settle for what you were originally after, which courts are perfectly happy to facilitate because it gets a potentially lengthy trial off their dockets. They'll punish (or be biased against) whichever party seems responsible for not accepting a "reasonable" settlement.
Algorithmic abuse of the system to extract payments already exists in the form of the debt collection industry.
A common tactic is to bury your opponent in the threat of heavy damages or jail-time to get them to settle for what you were originally after, which courts are perfectly happy to facilitate because it gets a potentially lengthy trial off their dockets.
That's not how litigation actually works in this country. Unless the plaintiff can actually prove damages, there's no threat of "heavy" damages. The primary economic concern is spending a lot of money on legal fees, which is the primary trigger for getting businesses to settle instead of litigate. It doesn't work so well against people though.
They'll punish (or be biased against) whichever party seems responsible for not accepting a "reasonable" settlement.
That is false and any judge caught doing that would be removed from the bench, immediately. The judge does not exercise any judgement over what a "reasonable" settlement is as they don't and wouldn't know what is reasonable until the facts have been presented...at trial.
Algorithmic abuse of the system to extract payments already exists in the form of the debt collection industry
The debt collection system doesn't use the court system at all. Assuming you are referring to individual debts, not corporate debts, debt collectors have a very low success rate in court since (a) they have to prove the debt is valid, (b) that they now own the debt contract, and (c) they did not violate any laws in the pursuit of collecting on that debt. A and C are actually really hard for a third-party debt collector to prove.
> API customers including Harvey and Legora will be able to build on Astra for Law, bringing this intelligence into their own products and workflows.
In other words: "no, no, we're not eating our children to prep for the IPO. Don't worry."
> By using the legal search index, Astra for Law can search U.S. case law, statutes, regulations, court rules, and administrative decisions across a corpus of more than 230 million URLs, with sources added daily. Our work with Free Law Project, the nonprofit behind CourtListener, brings its case-law collection covering more than 99.9% of published U.S. precedential case law (opens in a new window) into this research experience.
Yeah, it should be freely available, you have to be able to know the rules you're supposed to obey in order to obey them well. I've been making a free API for US law search, you can point whatever model you want at it: <a href="https://law.agentlookups.ai/" rel="nofollow">https://law.agentlookups.ai/
Very much a work in progress, only federal and state so far, no municipal codes yet, and no case law yet. Big hole, I know. Also working on making the search ranking work better.
Right now it's just a bunch of crawlers for the individual states. If there's interest, I could periodically stand up snapshot torrents or something. That something you'd be interested in?
Alternatively, if someone else knows an all-in-one option that exists, I wouldn't mind retiring those crawlers...
Not op, but that's a very interesting proposition. While the law and legal code are technically property of the people, I'm not aware of any single point of download for it all.
There’s no single point of download for it all because there’s thousands of autonomous entities that issue law and adjudicate cases, at least 51 of them distinct sovereign entities.
We could enforce (suggest?) a common format / api at the federal level. Especially if it’s incentivized with funding that more than justifies the cost of maintenance. Similar to how federal interstate funding is only available to states with a 21+ drinking age.
There is none, not for statutes and definitely not for case law; even at the appellate level where you have multiple federal circuits, then 50 states, then territories, military, tribal and a whole host of other niche courts. And the appellate court systems can be split into districts, and by lower and higher levels.
Then if you want to really get into it, The People should also be able to access trial court level, and at that point you have over 3000 distinct court systems with their own access systems, usually requiring logins and CAPTCHAs, and half of them not even having anything accessible online at all, and the other half only having recent stuff online and the rest rotting in a flooded basement.
We have hosted bulk case law at Free Law Project for over a decade: <a href="https://wiki.free.law/c/courtlistener/help/api/bulk-data" rel="nofollow">https://wiki.free.law/c/courtlistener/help/api/bulk-data
Max Junestrand has consistently said Legora treats the model layer as swappable, selecting across frontier providers rather than building the product around one.
OpenAI didn't need to name Legora and Harvey in the second paragraph of the launch post.
They are pre-empting the obvious interpretation of Astra for Law: that moving this far up the legal stack puts them in direct competition with their biggest legal AI customers.
“Don't worry, they can build on us” is a pretty conspicuous message to include on launch day.
They have clearly thought about some pessimistic outcomes.
>Max Junestrand has consistently said Legora treats the model layer as swappable, selecting across frontier providers rather than building the product around one.
Vendor-neutrality for LLMs is such a weak thesis all around, whether for providers or consumers. It weakens the product by being promiscuous and gains no material benefit at all.
LLMs are magic byte(byte) functions, it doesn't make sense to say "we have different providers for magic".
Different flavors of magic require different ritual components and in the name of all that is stable and production worthy, please don't get a necromancer to do your civil construction magic.
Vendor-neutrality helps reduce lock-in, and OpenAI and Anthropic are big enough that the reduction is valuable.
Switching from ChatGPT Enterprise to Legora at my firm was a godsend, it's so much better for legal work, even with the frequent changes to the underlying models.
They are cutting into their market. They can dress it up however they want, they might not be competing for enterprise contracts yet (hence the fluff statement), but they will.
the thing is a lot of the legal work which will go through this is drafting 100 and 1 variations of draft versions of standard contracts not containing any trade secrets where the contract can be drafted with "replacement/place holder names"
the kind of work mostly done by juniors not yet through their final exam and other "non" lawyers etc.
so it's a slippery slope of "lets just use it for <this> things where it doesn't matter" and then out of laziness and convenience it creeps into all the other places (at least for drafts).
open-ai have proven they can make good / decent models but business strategy is just spray and pray.
they need to pick a lane and optimize for it. coz at their size they can't serve the application layer (a.i startups who can fine-tune models will eat their lunch)
if they gonna do a consumer play - then go ham on that.
otherwise they're gonna get caught in the dreaded middle valley.
I think the comparison is unfair. Google had/have a product that was 10X better than anything else at the point of release (search then chrome). And they have several money making products like YouTube and android that are either singular or in a duopoly.
OpenAI doesn't have any of these things. They have products that they're paying for customers when the market they're in is rapidly converging on fighting for API reasoning as part of enterprise systems and fighting a race to the bottom for fickle consumer solutions that will be eaten by open source.
They have a lot of compute, so I think it makes sense to spray and see what works. Anthropic is limited in that regard, and focused in coding/tech, but OpenAI don't need to do the same. They even got the lead without having to focus in coding only, which is remarkable.
Enterprise is eventually get caught (if it isn't already) by the Microsoft/Google. Because with office/teams/suite they were already in every enterprise, and that just added a new tool to existing offerings.
Provisioning and contracts and data retention was just an extension to review of existing ones.
Nobody serious is going to risk sending sensible data to OpenAI/Anthropic, etc because "the benchmarks have shown +8% performance there and +2% there". Irrelevant.
They can't be seen to commit to strongly to a specific product experience, because if they are understood as a regular tech product business that has way different financial scaling considerations than "superintelligent everything-factory"
I suspect that half-assed announcements like this are a result of different people internally with conflicting incentives resulting in a split-the-baby solution.
Perhaps, but then someone would do the same but bill you for 7 hours, someone else would undercut them again, until the price reaches a lower equilibrium.
the same way every legal rule is enforced / checked: people look and if it seems iffy they examine/complain, and if a problem is found people get fined/jail.
Wouldn’t this and similar efforts to centralize bureaucracy make AI the new gatekeeper? Without reliable transparent models we’re just trusting OpenAI instead of a hundred top legal firms.
Unless it materially moves the needle, it’s a waste of the company’s resources. On paper, Atlas Browser and Sora seemed to have greater potential than this and yet, they’ve been discontinued.
i hope that someone can come up with something catchier than "thing-slop" or "slop-thing". the word has become basically meaningless from overuse.
So much for caring about the spirit of the law. Now we'll start an arms race for abusing every possible letter of the law.
It's analogous to crypto. Started from some noble anti-authoritarian ideas and morphed into machine that removes any friction for capital - whoever has the most money will keep gaining the most.
Now there will be even less friction to horribly abuse the law. To democratize the law we would need to move in the opposite direction - to always keep it simple and aligned with our intuitions.
The more intricate and complex legal arguments become, the more abstracted they are from their original purpose and spirit.
Hence the crypto analogy - it was also supposed to "democratize", but the opposite happaned - it only further empowered the most powerful. Imagine legal case so purposefully complex that only those with access to best models have chances to participate and win the dispute.
It's shoved down the world's throat from some central think-tank, despite the carefully constructed illusion of "deglobalization". Someone is very hell-bent on making the whole humankind plunge into this dystopia.
A headline from Russia to consider:
The Supreme Court approves the plan to deploy AI in Russian courts: the document states that by 2030, more than 95% of judges will have to use AI regularly. The risk matrix cites AI hallucinations and opposition from the judicial community.
Any lawyers here who have used AI agents heavily for their work? From what I've heard, they're currently very good at searching, analyzing and drafting documents like contracts and patents, but some say they suck at interpreting the law.
They are excellent, especially the latest models. That said, (a) I wouldn't feel safe filing something without a real lawyer looking at it; (b) it can't (easily? legally?) do oral arguments for you; and (c) a lot can happen in the hallways outside the courtroom to move a case forward that the AI can't easily do.
I’m sure there are a wide variety of experiences out there, but here’s my perspective as a former biglaw associate and current solo litigator:
I have had some success using frontier models from the last 6ish months, but only when I can break up my work into discrete and verifiable tasks. For example, I had ~15k pages of discovery I needed to dig through for a summary judgment motion. Instead of just asking Claude to find the best evidence, I asked it first to run a clean, high quality OCR pass (it was almost entirely PDFs). Then I had it generate embeddings and write some reusable python scripts to make keyword and semantic searching easy for agents. While I was writing the brief, I would routinely ask my agent (Claude Code) to use both keyword and semantic searching to find the best evidence supporting whatever assertion I was trying to make. I trusted it because there were traces I could follow.
In other cases/situations, I’ve tried just giving a model access to all the docs and saying “write a brief arguing X,” but it’s always terrible at this. It writes briefs with lots of evocative jargon and rhetorical flourish, but a low signal-to-noise ratio.
Again, I’m sure others’ experiences differ based on workflow, legal area, etc.
Agreed. Six months ago, it was basically a gloried grammarly.
But lately, I’ve been taking hints from the “company brain” models, where it develops a running model of the case, and assesses each new piece as it comes in and updates the file.
I’ve also been using “Ralph Wiggum”-type models where you pass letter or contract drafts back and forth between agents with different goals (rules compliance, grammar, conciseness, ai slop detector, an opposing counsel critic, etc.). After a few rounds, it’s not perfect — but I start with a very good first draft in my hands.
In my experience it basically doesn't even try to interpret the law. It just summarises the publicly available law/guidance out there and, if there is a question about how to interpret some provision, might set out the arguments for each interpretation. It doesn't really take a position. It is pretty good at drafting though. (Legora)
Interesting! In other unrelated domains, models seem more willing to take a position. It may be nuanced, but they do tend to take a stance. I think it's good that it leaves the interpretation to humans, but I wonder if this is also some sort of a guardrail to minimize liability...
I've always said this will be when we get the real Butlerian Jihad, when the AI firms start trying to liquidate the legal profession.
If you automate lawyers out of a job, you can absolutely automate lawmakers out of jobs next. (Not that this would be a bad thing? Maybe pervasive agents for everyone can be the gateway drug to a "this time it's different!" workable direct democracy)
I really hope the bar associations continues to hold lawyers to high standards but I have feeling they may not be ready to handle fallout of AI slop-law.
The need for actual lawyers will persist I think from my own experience. I attempted drafting a contract with some points myself using AI, but after several edits I wasn't sure if it was correct. Sending it to an actual lawyer ended up in so many corrections I couldn't imagine the first time. One big thing was the overly excessive protective clauses which didn't make sense for reality or conflicted with another.
Its just like code I suppose, if you can read and understand and validate, you can use it to scale and otherwise it could end up being a vibe effort.
LLMs are the first genuinely useful legal tech since the Internet. I'm pretty shocked, though, at the delta between how competent Claude is on code versus legal work. It's good for research and data organization, but terrible for drafting. I wonder if this is a structural problem with the lack of feedback loops. In law, there's no compiler to check for logical or continuity errors in your brief, and there's no unit tests to check for correctness or performance.
Even without that, I think it'll be extremely valuable to clients to allow them to answer simple questions without a lawyer, figure out the lay of the land so they can supervise their counsel, etc.
I have found that it’s useful generally speaking to get the intent of contracts and red lines, but actual drafting I agree is where I lose all confidence. My guess is that the significance of the difference between using a word like “and“ or “or“ can be so meaningful that that level of nuance can often be lost. But I know nothing I’m not in the space, I just pay too much money for lawyers.
> LLMs are the first genuinely useful legal tech since the Internet
That is an incredible statement that could not be further from the truth. Large scale adoption of email, searchable document databases like Westlaw, LexisNexis, PACER, etc.. , OCR Software, electronic signatures, and tons more have had a much more defineably positive impact on the legal profession since the internet came about.
The internet came well before both of those. And none of the example I gave have lead to lawyers regularly being fined in court because of "hallucinations"
You should know - for coding they make terrible mistakes as well.
But programmers have this concept of a "code review" where another person looks at the code to look for problems.
We use this same technique with our LLMs. Most mistakes are caught by having a second LLM look at it. Doesn't even need to be a different model - just make sure it has a different context.
Programming has a long standing culture of accepting the code to be somewhat wrong, so we have various tests, linters, reviews and error handling. Also in programming there are many ways to do something and it's the end result that matters most.
Not so in other knowledge work. There's no test harness for a contract and error is non-recoverable. Likewise in finance. There are specific ways of doing things and these ways are many times set in regulations. LLMs can assist all day, sure. But replacing the human, in highly regulated, zero tolerance for error environment?
You could say the Salvatorian Clause in contracts is like exception handling:
a "catch (all)": even if some clauses in this contract are illegal,
the remaining contract stays in place.
Logically, this actually doesn't make sense strictly speaking because the sentence creates a paradox: doesn't it make clear whether it includes itself or not, and each reading ends up in trouble. There is a "tradition" in law around the world to accept the only benign reading of such clauses, which I always found funny given that in all other ways lawyers adopt the most adversarial mindset imaginable.
The highly regulated, zero tolerance for error environment is a huge problem because anyone doing these jobs is more like a small sample size LORA than a general model.
It doesn't matter how smart someone is, they need specialized training to be good at these jobs. Specialized training in the area the company specializes in.
There is a category error in all this that is hard to think about because of the normal discourse and ordinary language. We say people work in "finance" but no one works in just "finance". They work at a company that has a specialization within "finance", inside a hierarchy that has specialization on top of specialization.
What we really need is exactly what we don't have and aren't going to get. A type of LORA that generalizes the task specific intelligence needed from a very small sample size and that in practice makes so many less mistakes in a highly regulated, zero tolerance for error environment that it is irresponsible to not use the model.
I have worked in this type of environment for 3 years and I have made zero mistakes in 3 years. The people that make even a small number of mistakes get fired.
Any real automation in this area is going to be incredibly slow and piecemeal over a long period of time because even an amazing model would need a long time to prove itself against what the human standards for error rates are.
> Doesn't even need to be a different model - just make sure it has a different context.
I find that the number of issues discovered is noticeably higher if you do use different models though. I'm doing some very finicky things (formal semantics) and find that there's value in review panels as large as 5 different models from different families. It gets even more profitable if you set it up as a truly agentic panel where after writing their own separate reviews they get to see what others have said, and adjust their positions or defend them etc. Some models are not that good by themselves but can be surprisingly good at finding flaws in others' reasoning (Grok for example).
I'm trying to understand why I'm getting replies basically saying "they'll never be good lawyers" when all I said is that you can improve the output by getting them to check each other.
I reckon law and medicine are really premier use case for llms since those areas are all about having vast knowledge(knowing all about obsure cases in law or about an very rare disease the average doctor wouldn't have heard about)
I've heard this argument (basically, you can just have good legal skills and adapt your practice to more areas of law) but we're still pretty far from a layperson confidently navigating court (you could say the same about code).
That's exactly it. You basically can't set up deterministic regression tests, which makes development of (legal capabilities) even more abstract and messy.
> The need for actual lawyers will persist I think from my own experience.
The outcome of a case shouldn't depend on someone's fallible ability to recall facts or convince other people or point their index finger*
Law should generally be deterministic. One's CHA stat should have no bearing on justice.
There should still be human judges, but the middleman between the judge and petitioner could easily be removed, and have generally been seen as leeches since forever anyway.
Though, like how the USA opts to remain in the Stone Age with regard to tax filing because of lobbying by tax software companies, this faction of society will flail the hardest before they admit they're obsolete.
----
* What's a lawyer's favorite programming language? Objection C.
Yep, just yesterday, Nike removed one leach middlemen called retailers and sell directly through their app. Turns out working out very well for them too.
The ability to clearly and effectively communicate, and the ability to know and recall the facts of a case is always going to be important. It'd probably be a more fair system if judges and jurors couldn't see the attorneys or even the people they're representing. Now that many cases are handled over video calls it'd be pretty easy to make that change.
A lot of communication is conveyed through more than the words themselves though and even though it's often misinterpreted people put a lot of value in that information. I suspect that even if we took away the ability to see the people involved judges and jurors would still find bias in the tone/quality of people's voices. Even if everything was reduced to text they'd find bias based on word choices, phrasing, spelling, and grammar.
An Amazing Lawyer not winning an unwinnable case = a good thing.
A Mediocre Lawyer not winning a winnable case = not a good thing.
Say a starving child steals a loaf of bread. The law says all theft is at least 1 year in prison. But the judge can see that the child is actually destitute and it was his first time. The judge could shorten the sentence to 1 week; that's fine, there should be room for interpretation and leniency.
But it should NOT depend on whether that child had a persuasive lawyer or not.
A good "AI Lawyer" would simply behave as how ALL lawyers SHOULD: Simply present the facts, the laws that apply to those, offer suggestions for the verdict, and the possible long-term consequences for each possible verdict, without injecting dramatization, exaggeration, or attempts to pull at heartstrings etc.
The typical pattern is called “deskilling”. It doesn’t usually mean a skilled profession will disappear overnight. Instead, the job might be done by less expensive folks like paralegals.
An example is in the banking industry, where making a loan used to require deep analysis of a person’s credit worthiness. Now they use an algorithm (credit scores) which means someone with less experience can do it.
If law follows the same pattern, a job done by someone making $500/hour might be done by someone making $50/hour.
i don't think that's the point anybody is making. "good lawyers" is not the profession at risk here. a top tier courtroom lawyer won't be replaced by AI.
but how much of the revenue of the average law firm comes from that, vs the day-to-day "we need this relatively routine contract reviewed" sort of work?
> Instead, the job might be done by less expensive folks like paralegals.
So who is going to define your strategy, represent you in court, adapt the strategy to changing circumstances, negotiate with counter-parties on a mutually accepted settlement? A paralegal? An AI model? Please
Very little of corporate law is in court. The mass of things is “does this contract look good?” And “what do we need to change in our business when regulation X comes into force?”
Again, lawyers. That isn’t going to be replaced by AI.
But this is the same story that has played out in other industries. The top tier isn’t at risk. The artist who commands $100k for a commission is still making money. But the artist who makes a living creating background images for corporate presentations doesn’t have a revenue stream anymore. The software developer who makes novel, high-complexity applications is still making money. But the guy churning out Wordpress templates has lost his job. The law firm doing 90% boring corporate boilerplate is next.
Former attorney here. A good paralegal is worth 3-4 junior attorneys. A good paralegal with AI should probably still have a senior attorney oversee them but this will absolutely hollow out firms.
Not being snarky here but I've encountered some really crappy lawyers and they seem to be doing great ($$$).
It really sucks one cannot publish something like "this guy charged me $5k, wrote my name wrong and forgot important paperwork the day we showed up to court" as that could make you liable for damages. There should be a safe harbor for that.
Assuming you are in the US, there is a safe harbour called "opinion based on disclosed facts" for that. You could also fairly argue that the conduct of a lawyer is a matter of public concern
> It really sucks one cannot publish something like "this guy charged me $5k, wrote my name wrong and forgot important paperwork the day we showed up to court" as that could make you liable for damages.
That's pretty much what bar associations are for, filing a complaint against an attorney at the bar seems like a pretty standard procedure.
>There should be a safe harbor for that.
A safe harbor would be the opposite, it would be immunity for the lawyer.
If you don't have the resources to defend yourself then it's probably not wise to publish things like this but you can tell others of your experience.
Also for those things you could sue for damages or lodge a complaint for malpractice.
Yes. But this option still exists in addition to reputation which I mentioned.
With AI models this option does not exist. I can't sue OpenAI because the contract that I got ChatGPT to draft carelessly exposes me to some type of financial loss. I can't contact the state bar and have Open AI banned from drafting up contracts or doing any other work that lawyers are licenced to perform. Even if I could it would not compare to a lawyer loosing their license to practice for life. If I tell a friend or acquaintance about my negative experience they will still likely use OpenAI for professional work and chalk up my experience to a skill issue or premature use of the technology.
Also note the use of the word "professionals". I was referring to doctors, engineers, accountants in addition to lawyers.
Except it doesn't, particularly as far as lawyers are concerned. There are almost a million and a half active attorneys in the US. Just 500-600 are disbarred every year, and almost always for money-related violations, not bad advice. Public discipline is also relatively uncommon (about a quarter of 1% of attorneys every year) and usually related to issues like financial impropriety, neglect, undisclosed conflicts of interest and failure to communicate, not disagreement over the quality of advice.
If a lawyer drafts an agreement that causes a loss, a bar complaint will not help you recover your money. You'd need to sue for malpractice. This costs a lot of money and takes a lot of time. Because you're going up against a lawyer, expect the defense to be vigorous, especially, ironically, if you hired an attorney at a good firm. The full weight of the firm will back the attorney and you might find it difficult to find an attorney, as many won't want to be involved in suing a fellow professional in their market.
I don't disagree with your fundamental premise about the value of human responsibility, but these professions have been structured to protect their members and the ABA in particular basically functions like a cartel today.
Not trying to be dismissive here but a lawyer will always edit your proposal. I do think lawyers will persist but not as many. And they will work very differently, much like we already use claude / codex to code - a big part of the contract probably won't be read by the lawyer.
I would rather argue they SPECIFICALLY will read everything. However, they'll likely often just be like "I'd phrase this differently but that works, too".
The best writer I know of was an associate attorney. He didn't have the technical background nor the in depth computer related knowledge, and relying on the information I fed him. But man the briefs he filed to the court were amazingly good. Reading them I would have been convinced his side was right if I were in the jury.
Law LLM will surely help competent lawyers in their fields with greater sources of knowledge not in their core area of expertise.
The salaries are a result of the insane hours they have to do. Biglaw needs to pay those salaries to keep getting young associates in the door because burnout is a real problem in the industry. If salaries were lower and hours/stresses were lower, you would probably still find people wanting to be lawyers. A different kind of person, maybe.
(Not that I think AI will necessarily have that effect. We just don't know yet)
Salaries are about scarcity and leverage, they have little to do with working hours. Nurses pull insane hours as well and they still don't get paid as much as doctors.
Very few people, if any, are going to bust ass in law school or medical school if they're not going to get rich off it. Better to do literally anything else.
In Biglaw, the scarcity is driven by the hours and stress. If it was a chilled 9-5 job you would certainly have more people willing to do it, even if it paid less.
It’s a professional organization that only allows so many people to pass the bar per year so I don’t see that changing anytime soon… if anything if they need fewer lawyers they will just pass fewer people to keep their wages high
As costs for legal work drop we might expect demand for that work to increase. For example, it may be the case that legal help becomes accessible to entire segments of the population that had no access previously.
I was in a similar situation and tried a different approach.
I had start with asking for a contact with some details I provided. But then I ask the model to be an experienced corporate lawyer and ask me a series of questions to gather the details it needed and then write the contract. The result covered a lot of details that were highly relevant but were absent from the original attempt.
The key insight is that you can lean on the model to cover your unknown unknowns.
Your comment is a great example of the phenomenon where people think AI is an expert in areas that are not because they have no way to determine if the seemingly good looking result is genius, gibberish, or somewhere in between.
Here's another techniqe that gets you (even) more out of LLMs:
run each prompt several times and compare the various outputs. It is not uncommon for models to contradict their own advice, and also you will get additional insights not included in previous runs.
This is due to the fact that LLMs are statistical processes that rely on pseudo random numbers in chosing what to say and how to say it to a substantial degree.
I want to take a step back and observe that you're saying expensive specialists will continue to be required if two parties want to make an agreement. That seems like something worth fixing rather than just accepting.
It's probably somewhat of a zero sum game. Both sides lawyers have AI tools which probably just keeps them on a level playing field rather than actually making anything cheaper or faster.
I spoke to a very very high up corporate lawyer specialising in tech - so knows Ai is real. And they said AI contracts are the bane of their existence. They’d rather you arrive with no idea what you want than a contract partially written by AI. They said it usually takes longer with an AI starting point than starting from scratch.
> I want to take a step back and observe that you're saying expensive specialists will continue to be required if two parties want to make an agreement.
A lot of contract-lawyering involves getting ahead of when things go south and the two previously agreeing parties find themselves in disagreement.
Same for SWE. AIs will churn out happy path vibe slop and fail when something unexpected happens by swallowing errors or having a bunch of terrible "fallbacks".
In my experience, those expensive specialists help me protect against things me and the counterparty cannot even imagine when making an agreement. Do you mean that this would be fixed by AI or by making simpler agreements?
When it can imagine real risks and not hallucinations, I am sure it will be better than having a human lawyer write the agreement. I am not convinced that we are there yet.
Millions if not billions of agreements are made every day without the involvement of lawyers. Lawyers are only needed for particularly complex situations and even there they are generally only "needed" in the sense that parties feel they would add value.
Yeah, and you can already get fill in the blank legal forms for a lot of basic situations, including leases, wills, employment agreements, etc.
The interesting question is whether AI can fill a niche these can’t — or, alternatively, help a layperson evaluate a contract they’re asked to sign better than they could themselves.
Contract law has evolved because transfering the ownership of things is fraught with difficulty. Ownership as a concept itself is notoriously hard to define.
Consider housing - when you buy a house you own that land. Except if its an apartment, you just own the internal walls. Or when the government aquires your land through eminent domain. Or mineral rights - which don't belong to you, you just own the top 5 feet of topsoil. Or if you neglect a property and some squats in it. Or if you were given a fraudulent payment, and they take back the property.
Just getting people to agree is notoriously difficult when people have different often conflicting desires.
Most people dont appreciate that the world is a complex place. Nothing is ever simple, sure concepts can be extremely simplified but the nuances and details are lost. These details are the important parts, just ask a surgeon or rocket scientist etc.
And to add to your last point yes it should also be like code: where the costs of development are coming down. Legal costs should trend down if law firms are effectively leveraging LLMs to accellerate their procedures (though I won't hold my breath)
In my recent experience, it seems like LLMs may even increase need/demand for actual lawyers (more ideas + more words = more lawyer time). I expect lawyers will generally adopt the technologies that will benefit them, rather than the technologies that would increase standardization and trust
The same has happened with modern finance. Despite more technology that has power to drive more transparent/efficient markets, we have less perfect information sharing and a larger group of middlemen capturing a growing share of profits of the economy
I think you're onto something, but it'll be more of a reshaping of practitioner distribution to match the mode of work (perhaps fewer employment lawyers, many more litigators/ip litigators, etc...)
>The need for actual lawyers will persist I think from my own experience
At the very least because the attorney monopoly assigns a 5ish year of training as PoW and natural personhood as Identity as protection for Sybil Attacks.
If anything, the exclusive right of attorneys to represent clients in court, file motions, and enjoy professional secret, is more valuable, as it's not something AI can ever compete at. (Barring a wild recognition of machines as humans, or an overturn of the impossibility of companies to appear in court.)
I agree. But, we will need a lot fewer of them. My small company called our lawyer a lot more before the advent of AI. Mostly to clarify a few things or review simpler contracts. Now, for simple things, we do not call them at all.
I anticipate an effect on society that troubles me:
(1) Rich people will use human expertise and "the rest of us" will use AI models to get by. This could happen in law, but also in medicine (in particular in societies that - like in the US - do not have universal healthcare).
(2) A positive effect in both domains may be that access to knowledge will be broader and cheaper.
I hope I will be wrong about (1) - I would not like to live in such a two-class society.
(1) already exists. A more banal example is rich people get their kids private tutors. Poor kids lean more on public resources, wiki, the youtube and the internet. Economic forces will always dictate this kind of change.
> One big thing was the overly excessive protective clauses which didn't make sense for reality or conflicted with another.
>Its just like code I suppose, if you can read and understand and validate
I share this, when I asked an attorney for a contract, they were much simpler when compared to self redacted or AI redacted contract, it was as if I were rediscovering lots of concepts and I HAD to put them in paper, even if they were defaults and were essentially no-ops.
Comparable to:
> Mkdir $PWD/path
instead of
> mkdir path
or conditions so rare that they don't merit including.
> x = 0
> if x!=0:
> raise Exception("Bit flip by solar rays or otherwise")
Our entire world is about reducing the friction of conducting a transaction
How to fix the lack of trust which is needed to conduct a transaction
Contracts affix a moment of trust in time, so even when trust is lost between parties the contract has guardrails for behavior and consequences for acting outside those rails
There are many transactions that are completely inaccessible to most people because the need for a contract or lawyer is too high
LLM use allows for those inaccessible transactions to decrease, and get people further along to the point where a lawyer is accessible as well, and economically viable to use
I'd correct this to "The need for actual GOOD lawyers will persist I think from my own experience."
I have worked with many lawyers in my career. The bad ones will look at a contract and tell you fifty things that can be improved. Meanwhile, you take the same contract to a really great lawyer and they tell you that's it's not worth fighting over the changes and to just keep it as is. It's kind of like how a beginner or intermediate software engineer might tell you how you can build out a k8s or auto-scaling fargate cluster for your project and a really senior engineer might look at the same thing and explain that it's not worth worrying about scalability right now.
I find that when I feed contracts to ChatGPT (which I do all the time) it will try to find 50 things wrong with it. For example, as a test, i fed chatgpt an employment offer from a US government agency. It came back with 1152 words and 14 recommended (some of them substantial) changes. Meanwhile, any half-decent employment attorney would probably laugh at me if I asked them to redline an employment offer from the State Department.
I’ve found that good lawyers are about getting things done. You could nitpick the terms of a contract, but would you rather buy the house or have a perfect contract? Once I realized that, my view of lawyers changed (for the better).
> Meanwhile, any half-decent employment attorney would probably laugh at me if I asked them to redline an employment offer from the State Department.
That might not be due to the contents but rather due to the fact that they won't negotiate I'd presume
"the hierarchy of knowledge", right. A bad or insecure speaker will ramble about insubstantial minutae whilst a good one will get straight to the key points that form an argument. Basically the confidence to prioritise information.
Also, unlike SW engineers, lawyers control their industry and will quickly circle the wagons to protect themselves. Paralegals are probably screwed, but lawyers will do fine. I'm considering law as my post-ai-SWE-apocolypse career path.
I’m thinking asking the same lines, but also looking into research / lab chemist so I can hang out with my best friend. If im going to change careers so drastically, I might as well enjoy the company.
"law" and those who pratice "law" have managed to place itself largly in a monopoly. This is a huge drain on the economy. Law is expensive and irrational.
you can't in imagine the same way you couldn't imagine generating the text from your initial prompt. when will the hubris end?
some variant of "oh i am capable of generating text i know nothing about, but it helps to have a human i can rely on to tell me more about the text i know nothing about."
pick up a bachelors degree worth of books to humble yourself
Yes the probabilistic smudging machine does not make many redlines with confidence, unless A) directed or B) it's a painfully out-of-distribution argument.
You should never rely on just one model. Use Opus Max for review and Sol Pro for drafting, then Gemini, CoPilot for additional "junior" reviews. Once passes make no material difference, feed it again to Sol Pro for review. At the end still worth checking with actual lawyer, but this way you might get document as good as it can get. Depending on the domain of course.
We need a term for the dark pattern of zooming into just that part of the y-axis where the two closely competing benchmarks sit, to make the top one appear maximally better.
this essay details how law firms became sweatshops from 80s. They charge hundreds of dollars to do make busy work by the junior most staff. LLM will kill the goldengoose of the law industry.
Astra isn't doing well on bullshit Benchmark <a href="https://petergpt.github.io/bullshit-benchmark/viewer/index.next.html?domain=legal&q=Ast&access=closed" rel="nofollow">https://petergpt.github.io/bullshit-benchmark/viewer/index.n... and is even worse in Legal department.
I'm not familiar with the Vals AI Legal Research Benchmark. But their website has other frontier models' scores, and the scores OpenAI is now revealing for "Astra for Law" are slightly less than Claude and Muse:
> The top is a three-way tie: Muse Spark 1.3 Max, Claude Opus 5, and Claude Fable 5.1 all reach 55.29% all-pass accuracy, a clear ~6-point step ahead of the next model. [Astra for Law reached 54.0%]
> Under partial-credit scoring, Claude Opus 5 reaches 90.58% weighted pass rate but 55.29% under strict all-pass grading, where every rubric check must pass. The gap shows models often get most of an answer right but fail on one or two required elements. [Astra for law reached 90.0%]
"Due to a spontaneous loss of alignment, JustitAI 2.3 pleads the government guilty of war crimes, launches ballistic missiles at several bunkers and tropical islands"
I've had top SV lawfirms whos partner charged our company $2000/hr and still couldn't get the right docs in the signature packet. and another getting share counts wrong during raise.
frustrating that law firms have no liability for these mistakes
no, but they are responsible for all work being done under them. What is the point of paying a partner $2000/hr if the work of their subordinates is wrong?
Most interactions with big tech firms involve 4-5 people so a basic phone call is $5k-10k. It shouldn't be unreasonable to expect after paying $80k for a financing round that they issue the right docs to the right people.
Since the cost of building software is now cheap, there is nothing stopping them from building everything imaginable. They'll soon have an app store with every app built by them and they'll say its for security reasons. Nothing is stopping this coming monopoly
At a certain point why would they sell anything other than services and products their eventual (actual) AGI/ASI builds in literally every market.
When opportunity cost isn't a thing anymore because it reaches every corner of the planet simultaneously faster and builds better than any human can.
There's no reason to let others build on top of AI, except if the AI determines that it needs capitalism to continue because it's paperclip goal is to maximize shareholder value.
The most interesting use case in my mind is skipping law suits. Obviously you need lawyers in court. But lawyers are people you are basically paying to fight for you.
Instead, if you resolve your dispute outside of court, you don’t need a lawyer. If both parties use ChatGPT to find the relevant laws or read contracts, they could come to an agreement without expensive legal fees.
I find the watermarking dynamic to be really interesting in the legal space, as more large model providers provide increasingly powerful legal capabilities, and adoption (presumably) also increases. Attorneys aren’t the same as developers as their work can be traced back to them, and there are personal bar licenses and reputations at stake. I wonder if knowing the likelihood that AI generated something helps or hurts in that respect.
I also see a lot of watermark removal services popping up as a result.
I wonder if this is willful sabotage on the part of the model. In other words, if you ask the model to craft a defense for a morally questionable case, will the model execute the defense in good faith? Or will it apply a training or system prompt bias in subtle ways?
Context compaction? I noticed llm seem to forget partially or completely the original task when context compaction happens. The problem is more serious with local llm with low context size.
LLMs bleed context from the conversation/attachments into the output. This has always been a problem with no real solution other than some crafty iteration/loops.
There is a lot of stuff here that I don't understand, but the concept of law firms giving user reviews is quite funny to me. Those reviews are going to be the most non-legally binding reviews ever written lol.
"Felt like a significant step toward legal-focused AI."
"Showed strength across key aspects of legal research."
The grifts continue... imagine something as consequential as Law being advertised as being solved by a statistical word generation engine that regularly gets basic things wrong. Anyone who isn't a lawyer won't know any better but you draft a single document of any appreciable detail and send it to an actual lawyer and it's littered with problems.
The most interesting part about this to me was how they bench/compare it, like in the example with Fable:
"Given the same prompt, Astra for Law returned two closely matching precedents; in the litigation example, Claude Fable 5.1 returned a holding that had been reversed on appeal, while in the transactional example it reported finding no such case."
It made me wonder if a good deal of law is about finding a way to work in statements with clear precedents without your opposition noticing and then later drawing upon them in court (as settled precedents, in your favor) after the opposition (perhaps implicitly) accepted it. That would clarify a lot about why some lawyers need to spend so much time pouring over and memorizing past cases (even ones that are only tangentially related); because anything they miss could be used as a potential trojan horse by the opponent.
If this is true that must mean there are a good deal of cases settled using precedent "gotchas" where both sides knew that without the "load-bearing" precedent the outcome would've definitely been the opposite. (i.e precedents almost always trump even valid arguments)
So OpenAI is partnering with Latham Watkins, Freshfields is partnering with Anthropic and Kleiner Perkins is building their own. It'll be interesting to see which wins out here, I don't see how those partnerships can end well for the law firms unless they're making an assumption they'll be sucked dry of USP but the revenue split from the AI labs will make up for it. Why would I pay a premium for Latham Watkins when every other firm can get their expertise and experience in a subscription, and add their own on top?
They'll be operating under a ZDR. Labs will still get some data but I wouldn't go as far as sucked dry of USP. Firms are very aware of the value of their USP.
I know someone who works in law and deals particularly with an area of US benefits and healthcare law. One of their workflows for lower-level employees at their firm involves taking in documents from healthcare plans and organizations, analyzing them for certain kinds of data, and then importing that data into an internal system they use to analyze and provide guidance on plans. The internal system can contain hundreds of documents for an individual client. All of the documents have the same information (roughly) but in totally diverse formats and styles. Once it's in the system, it's easy to compare and analyze across documents and the research process is much faster.
They recently bought a Claude subscription and began using Claude to do the initial read of the documents and output JSON they can import into their internal systems. The work still must be reviewed by an attorney - Claude is nowhere near making the kinds of judgments a lawyer would make about this content - but it has increased their throughput from 2-3 documents an hour to 8-10 documents an hour by killing the busy work.
LLMs have great advantages for this kind of work - but not for decision-making. I just don't see OpenAI ever admitting that.
(I've left some details intentionally vague because this is a very specific area of law and I don't want my friends to be identified without their consent.)
If an expert produces a result which other experts agree is of good quality, and then they find a way to produce those same results faster (and the other experts continue to agree it's good), how does that not constitute proof that amongst those with expertise, the fast process is good?
It's an incredible level of hair-splitting to say "well, all these people who know what's good agree it's good, but that's not technically PROOF".
I'm just a guy on the Internet posting comments. It's tautological that I can't "prove" anything if what you want is hard evidence right in front of you. What's the point of pointing it out?
I'm thinking back to some of my interactions with corporate lawyers and you know what? My bar (<- pun) for trusting Astra more than a lawyer is pretty low.
Visit a developing or corrupt country and you will realise the LLMs of today analyse better than the judges from purely precedence and literature review POV
"Write a python script that breaks down this PDF by X feature" would not hallucinate anything in the PDF. Certainly you could trivially double check that all text in the extracted JSON was in the text layer of the PDF.
How much experience do you have with LLMs exactly? It would be consistent with my experience if Claude stuck in a line of python that just emits a JSON literal with no justification, potentially buried in a large program where an untrained person might not notice it. I don't even trust them if the output consists of structured data paired with source images from the PDF, because I've experienced LLMs fabricating the source rectangles to match the output. I only use tools like this by asking for programs, because as you note LLMs are good at that, and the verification process consists of tool calls to legitimate PDF manipulation tools so I have some confidence everything is above board. Even then I only do this for hobbies, not anything that matters.
Lawyer here. I used to trust Claude as hallucinations are near non-existent now. However for large volume tasks such as due diligence exercises, they still happen.
We also tried Legora's tabular review, there were also numerous halucinated provisions in our due diligence exercise.
And when they do, you can train them or fire them, and they learn not to do it.
LLMs change not a whit, and there's no one to take responsibility for the failure (and thus no way to fix it).
As the new variation on the old theme has it, "A computer can never be held accountable, and so very many people are trying to get them make management decisions."
You can’t train people to never make a mistake, particularly when doing highly repetitive work like this. You must build your systems to account for that regardless.
Yes, exactly. Humans are non-deterministic as well, just in different ways. A tired human can make all sorts of errors for example, regardless of how much training they've had.
That's a recipe for disaster in my experience. I tried it (with Claude) on a simple tabular bank statement PDF, and it transposed two amounts, placinh each against the other's description. And the bot assured me the result was cotrect. The chance of a human checker catching such corruption is low.
Doing similar-ish things with Claude, it's helpful to have something to ground it.
For instance, if you can say:
"Refer to the database schema in x.sql as your source of truth for the database structure we want to import int. Do not invent data, tables or columns that do not exist. Carefully match all output against this database schema and do not create output that doesn't exist if it does not match the schema, simply skip it."
You will end up with a far better result in my experience.
But it gets it right like 99% of the time so human attention can be put towards catching the 1%, not entering data from one table to another and then catching that human’s mistakes.
Few things are. It also doesn’t require standards. “Stamp this diff” culture is everywhere even before AI. A stamp is literally easier than anything else.
Whether that is useful measurement I suppose depends on the circumstances.
Yes, remember that these are effectively random PDFs in various different designs and formats, some of them not editable or even OCR'd.
It took a human attorney 20-30 minutes on average to manually copy-paste data from these PDFs into a spreadsheet (while also fixing any errors they found in the document and re-checking for quality).
Now, the AI copies everything into the spreadsheet in a small amount of time, and then the human reviews it. It takes maybe ~5-7 minutes to scroll to the appropriate pages in the document, read the lines vs the spreadsheet, and make corrections. So you've gone from 2-3 items an hour to ~8-10 items an hour.
Maybe you could pay someone to develop an OCR/ML application that could do this. But that project would never be profitable, even with the time savings. At the cost of a couple Claude subscriptions, it makes sense.
I'm doing some public court records processing for bankruptcy cases (interested mostly to seek out corruption in big national cases), and yes, the "variousness" of random PDFs is exactly the issue. Trying to get the cost for a whole case down to a minimum.
Sample is around 300 court dates, shy under 1k files.
Does the human find enough bugs that they stay on guard, or just rubber stamp everything without really looking at it? It’s hard to stay vigilant when stuff looks plausible.
This is what bag scanners at airports do - the hit rate is so low and the job so boring the software projects fake contraband onto the imagery. Fail to spot the knuckledusters and expect a chat with the manager.
> Maybe you could pay someone to develop an OCR/ML application that could do this. But that project would never be profitable, even with the time savings. At the cost of a couple Claude subscriptions, it makes sense.
A better use of these Claude subscription would be to develop the app (which it can pretty much do at that point) and you could iterate to make the workflow even more efficient than your current one.
Nobody working there has the requisite experience to do this in a reasonable amount of time. These are not particularly tech-savvy folks, Claude use aside.
Yes. And it might not even be worth it, as the AI agents gets cheaper and cheaper.
Keep in mind that the task is fixed, so as the frontier of AI advances, you can switch to a cheaper trailing edge system and still get the same or even better performance for this task.
> These are not particularly tech-savvy folks, Claude use aside.
The difference between a tech-savyy person, and a non-tech-savyy person has always been mostly in the later's head, but this is even more true now that we have pocket assistants who can answer pretty much all of our questions in a language tuned to our level of understanding.
Thanks for sharing the details. Does the attorney check that the AI copied the data accurately? Or is it just assumed to be correct?
Your experience mirrors my own. AI is great for parsing data that can take up a huge amount of time. My only concern is whether or not it’s done accurately. I wouldn’t use it for anything where mistakes cause serious consequences.
I see problems in LLMs doing research, making drafts, etc.
I see 3 kinds of potential users.
1. Non legal background people trying to avoid going to a lawyer. They should definitely NOT use an LLMs.
2. Fresh out of law school graduates.
They think they can do fast work, draft quick replies, do fast case research, enh. They should go the traditional route of interning, learning the "art", they probably won't need it because they will learn "how the law works"
3. Established attorneys.
They usually have templates made for most things, over their career, they have established routines of making things fast, maybe it can help them but to say replacing good chunk of work or offloading to LLMs isn't probably going to go well.
There is a reason why interns are made to do grunt work. The "chain of command" is built so they learn on basic stuff, learn to make decisions, etc. Without these basic decisions under their belt, an intern can't take bigger decisions later on. They just won't know....
Might be true today, but I still feel pareto principle applies. These points also sound like gatekeeping a bit and I hope future AI versions prove that law is also essentially something that can be made as programmable as possible for most common answers if the underlying principles and constitution are organised such.
If there is no precedence for X happening when Y , Z, P, Q, R are special combinations , the judge decides and sets precedence. But if another judge interprets it differently with similar set of circumstances it is not considered incorrect I presume especially if in different jurisdiction unless overridden by a higher court. This is my layman understanding but I think this design is wrong and essentially where human subjectivity controls the system.
Subjectivity is not totally avoidable in law but the goal of the legal system should be reduce it as much as possible along with ambiguity.
Your understanding is correct, but where your understanding goes astray is thinking that that's a bug. The subjectivity is a feature. It is not possible to specify what should legally happen for all possible circumstances the entirety of humankind faces. Like, literally not possible. We humans can't even create rigorous specifications for what our programs should do that keep up with their evolving requirements, and you want to make life-ruining decisions set in stone based on a rigorous set of predetermined rules about all possible circumstances the entirety of humanity could face any time in the future in an evolving world?
Law is intentionally not code. The world is not something you can program.
Isn't achieving a rigorous, unique specificarion what civil law tries to achieve? Not that it is a success, but the idea behind it. Sorry if this is a silly question, but this is how I understand it.
No, it doesn't. It aims to provide a fairly comprehensive framework within which judgments can be made, but it is absolutely expected that there are edge cases and ambiguities which are resolved by human judgment of the circumstances.
Since this is a thread about using ChatGPT for law, I should note that this is actually one of the most important reasons you'd rather hire a lawyer than ChatGPT to represent you. A good lawyer or firm will know the local judges and how they tend to lean on ambiguities in their area of expertise, and will be able to use that information to both advise you and tailor their arguments to appeal to the judge's sensibilities. There is an element of unfairness to this, to be sure, but you'd find much more unfairness really quickly with machine-generated judgments because of how messy and non-compressable real world circumstances are.
> Non legal background people trying to avoid going to a lawyer. They should definitely NOT use an LLMs.
In my experience, it is incredibly hard, practically impossible, to find a lawyer who will even talk to you. I think this is a valid use case to get at least some understanding what the next steps might be and if it even makes sense to seek legal representation.
Agree. Now imagine the same thing in less developed and/or less well off countries.
There was a post here a few weeks ago about a UK court being inundated with some kind of claims (unfair dismissal?). To submit a claim you do not need a lawyer, but the process is (intentionally?) vague and very complicated, so it takes a lot of effort to figure it out yourself. But AI makes that kind of stuff easy.
AI is not going to replace layers billing big corporate clients millions a month, but it will replace things that are fairly standardized processes, that don't require a lawyer, but today are just too complicated for regular people.
> To submit a claim you do not need a lawyer, but the process is (intentionally?) vague and very complicated, so it takes a lot of effort to figure it out yourself.
I'm not sure there's quite accurate. The form is really not that difficult to complete.
It's basically: Party details, type of claim, particulars, damages
Obviously knowing these details requires some legal knowledge but I actually think ET claims are easy enough to bring if you've got the time to do a little research and build your case. Almost all ET judgments are public so there isn't the usual difficulty with research as you get with law reports being restricted either.
> In my experience, it is incredibly hard, practically impossible, to find a lawyer who will even talk to you.
Really? I find them quite talkative. But I'm not sure what kinds of questions you are pestering them with?
In any case, the whole discussion reminds me of people using LLM to replace medical professionals.
For both: unless you have a doctor or a lawyer always on standby, you have to make a decision on whether to even go and seek out one of these professionals. By definition, you make that decisions without professional help. I think LLMs can help you there with the initial research to decide whether it's even worth it to contact the professionals.
There are 3x as many lawyers per capita in the US as we had in the 1970s. Credit agreements that used to be 50 pages are now 500. This increase in volume has not lead to any increase in actual value. The legal profession is a metastatic cancer on our society. Un-fuck this situation and maybe I'll think about taking your advice of not using a LLM.
>Non legal background people trying to avoid going to a lawyer. They should definitely NOT use an LLMs.
I used LLMs to replace a lawyer this year to great effect. I successfully advised myself as to the right strategy and drafted an immigration petition in the correct language. Granted it wasn't 100% LLMs (I also supplemented it with "traditional" online research and wrote the letter myself using the LLM version as rough guidance), but still, I certainly would've gone to a real lawyer in 2024 for this stuff but didn't.
Professional advisory work can be divided into two types:
1. Once you know the rules of the game, the next move is immediately obvious.
2. Knowing the rules is not enough to know the next move -- that requires judgement and experience.
LLMs in the hands of someone smart and savvy can easily replace the first type of work.
If it is at all possible to replace a lawyer with an LLM, it should always be the preferred choice. Using a lawyer is not a zero-sum game, using an LLM is.
Lawyers nearly universally tend to: convince clients they need a lawyer; promote extreme views; charge legal fees (that ultimately result in financial damages to the client). There are no winners in this game, except for lawyers, who are having a lovely time. Even if you won the case, you've lost, because the pie got smaller due to lawyer fees.
You’re managing risk and what you pay for is derisking yourself. You be the judge of what that is worth to you, but it’s not zero and it’s not always your attorney’s fee either.
Retaining an attorney is a little bit like feeding a shark in order to catch a ride on its back and do some jousting with your opponent, while your opponent is entertaining a possibly bigger shark or two, and has possibly infested the place with piranhas.
There is a chance of de-risking yourself, but the chance of a bloodbath is even higher.
And yeah, the sharks are trying to convince you that they are "your" sharks, while it is quite clear that their mates are the other sharks.
I do think non legal background folks can use LLMs today to sense check legal ideas, like for instance, "what are my legal rights in this situation?"
These situations usually are not ones that an individual can justify the time or money to contact an actual lawyer, but then if they do decide to contact one they will come in with better questions and more of a sense of what they are expecting.
This is similar to medical. Should you use LLM to diagnose yourself, treat yourself with prescription drugs you buy from shady gray market online sellers? No. But you can use it very well to know when it's time to go to the doctor and what to ask.
Yes. Unless you have a lawyer or doctor on standby, you have to make the decision whether to contact them. And by definition you have to make that choice without professional help.
LLMs can help with that. I don't think they are worse at this than me trying to figure this out all by myself.
You can replace "laywer" with "software engineer" in your post and it holds equally true. I think this also applies to other factions.
> There is a reason why interns are made to do grunt work. The "chain of command" is built so they learn on basic stuff, learn to make decisions, etc. Without these basic decisions under their belt, an intern can't take bigger decisions later on. They just won't know....
That might be true, but that doesn't mean you benefit from training up juniors.
You sound much like software engineers sounded when the first coding agents dropped.
"You can't trust the output, it doesn't understand bigger systems"
"Its an art, you need to learn the ropes of it to truly write good code"
Its a very dangerous line of thinking. Software engineering will never be the same, as writing code has basically vanished from the daily workflow. Not for every specialized usecase, but for many.
> They recently bought a Claude subscription and began using Claude to do the initial read of the documents and output JSON they can import into their internal systems. The work still must be reviewed by an attorney - Claude is nowhere near making the kinds of judgments a lawyer would make about this content - but it has increased their throughput from 2-3 documents an hour to 8-10 documents an hour by killing the busy work.
At my company we're also in the process of deploying a system that does exactly that. And what's interesting is that you absolutely do not need a frontier model for that, a small VLM (vision-language model), with optionally a little bit of fine-tuning, gives you the same output quality at a fraction of the latency and cost.
I'm wondering if the bottom is going to fall out of frontier models when people start to realize this. Sure, as an experienced programmer you can tell the difference between a compact free model and the ones that are 100x bigger and cost billions to train, but 90% of busy work is dead simple: turn a PDF into json fields, or do the inverse and fill out a form. As the tools for this conversion become more widespread you can also imagine an economic shift toward efficient information brokers that make frontier models less necessary.
It's also not really clear if everyone is going to want a frontier model when the real implications sink in. Maybe we'll get sick of incomprehensible code optimizations and people wile tire of reading AI prose that feels ever-more-human. There might be a few use cases, but who is going to pay for this when providers start charging enough to be profitable.
I think this is the long-term reality of LLM tech and one of the objectives of engineers implementing solutions, finding the right fit for the job - the right model and cost to achieve high enough accuracy at the lowest price.
But that's phase two, phase one is finding localized problems to solve using LLMs and productize them. I'm reminded of cloud tech, where phase one was changing software to run in the cloud, and phase two was optimizing costs.
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This was already always the case. If anything, making this more accessible will reduce the barrier to entry for whether or not it's worth your time to take on a case. Instead of 50 lawyers spending 100s of hours on a case, you can have 1 or 2 lawyers + Astra working on it and if there's a case you can add more real lawyers.
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1) Lawyers are not as naive as software engineers and will fight being replaces by new laws.
2) If they are replaced, OpenAI will take a cut commensurate with the amount in dispute (OAI, please credit me for the idea in the IPO brochure).
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I am curious what level of trust established law firms treat LLMs with.
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If the benefits were shared across humanity, that could bring us closer to utopia. My worry is that we’ll instead end up with a handful of even wealthier billionaires and millions of people out of work.
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They also openly tell you what they are afraid of btw: collective worker power. something that is massively lacking in our industry, although i feel like it would be one of the easiest industries to unionize in terms of # of workers.
Interesting interview I just watched about how powerful and dangerous these "wishes" or "prophecies" are especially in the hands of the ultra-wealthy: <a href="https://www.youtube.com/watch?v=eR7grHa1NR0" rel="nofollow">https://www.youtube.com/watch?v=eR7grHa1NR0
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Effectively yes, in the current forms. Those professions will likely evolve, but the traditional forms (ie writing code by hand, writing law filings by hand etc) are all dead.
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this is more likely to democratize the legal system by reducing the cost of a good legal team
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It seems much more probable to me that these LLMs will make good things worse than that they will make bad things better.
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there will still be writing initial and incremental prompts by hands, until and if LLMs surpass humans in all intellectual functions.
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As it stands, it seems far more likely to result in a wonderful life for a few, and an absolute catastrophe for most.
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Same argument for plumbers. Everyone always jokes about what a good time it is to be a plumber. But what happens when all the software engineers turn to plumbing? Suddenly it's not such a good time to be a plumber anymore.
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<a href="https://artificialanalysis.ai/models/gpt-6-astra?omniscience=omniscience-hallucination-rate" rel="nofollow">https://artificialanalysis.ai/models/gpt-6-astra?omniscience...
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Your comment made me wonder if there are any halfway-acceptable model benchmarks for law tasks? Specifically I’d love to know how the frontier models’ abilities compare between common law vs. civil law systems. My guess would be that an AI in a common law context should have a clearer idea of how a specific case is interpreted/accepted by (common law) practitioners, whereas trying to rely on AI in a civil law context, like Germany, can be daunting. In a few Germany-specific recent examples, the models feel like they present only (maybe too stubbornly?) the “civil law”-based laws. All while negating much of AI’s research benefits because civil statutes are portrayed as being absolutely accurate, binding, and their enforcement (and thereby the legal reality) being uniformly applied. Am I making this interpretation up? If so, how can I prove myself wrong?
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Roman law, on which the legal systems of Germany, most of Europe, Turkey etc. are based relies more heavily on statutes than Anglo-American case law, but cases do play a role there, too. That's why a practically useful system also needs to have access to court decisions, commentary etc. - and while the statues are in the public domain, a lot of the other knowledge is owned by specialist publishers (such as: C.H. Beck, Nomos, Mohr Siebeck, De Gruyter, Otto Schmidt, C.F. Müller, Manz, Verlag Österreich, Schulthess, Stämpfli, Dalloz, LexisNexis, Lefebvre Dalloz, Giuffrè Francis Lefebvre, CEDAM, Giappichelli, Il Mulino, Aranzadi, Tirant lo Blanch, Marcial Pons, Dykinson, Tecnos, Lefebvre, Almedina, Gestlegal, AAFDL, Kluwer, Boom juridisch, Wolters Kluwer, Larcier-Intersentia, Anthemis, Sakkoulas, Nomiki Bibliothiki, Universul Juridic, Hamangiu).
Internationally, legal systems appear to undergo a sort of convergence, which means statutes increasingly matter in the U.S. and cases increasingly matter in European law (according to a law partner friend).
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The legal systems of common law countries are quite similar in both how they do legal training and in many areas that are important for business. Like in contract law or tort. That means not only similar concepts and foundations (things first taught to law students), but also a similar approach to what is seen as a legal problem, and what kind of answers people expect from a lawyer. Also, what they understand under "legal research" - what do you actually research and what is expected from a qualified lawyer to know by heart, how are you expected to find the legal default in a detailed question, how certain that default is, what is up to professional judgment. But even the differences within common law systems is huge in other areas that go beyond these basics. Like those affected by statutes, codes (like CFR or NYCRR) or even local regulations etc. The popular legal benchmarks do not dare going into these more detailed legal work directions. And these laws change frequently, and they are very different from one jurisdiction to another, even within the US, let alone in other countries building on English legal traditions. (Nobody I know of is building a benchmark that affects these areas of law.) And the diversity is even bigger within legal systems lumped together as "civil law systems". Even those based on Roman law, or on German jurisprudence in the 19th century... There is not much common in how French and German students study law, even if both are members of the EU and many areas of law are harmonised or subject to the same legal acts of the EU and the same EU Court of Justice.
If your LLM has access to up to date legal databases of those countries, commentaries etc., the answers are still surprisingly useful in research. That said, no professional should rely on those LLMs that merely use public legal databases, scraping latest laws and cases via self-operated MCP servers.
I think the main difference is how lawyers from a civil law system use the LLMs compared to someone from a common law system - and that is based on the different training they receive as law students, how they see "law" etc. Maybe there is no such a thing as absolute accuracy in the civil statutes either, but at least civil law lawyers have a stronger notion of "law is knowable". There is a higher likelihood of having one "correct" answer, even when talking about more lifelike, detailed questions. (I'm qualified in both a civil and a common law system but not specifically in German law.)
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that all typically comes in pages of terms of service, purchase contracts, SLAs, and that sort of thing. not in the initial marketing post.
i would like to think any lawyer wanting to use the product will either get that information or choose not use the product.
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Don't be too sure about that. [0]
0: <a href="https://www.damiencharlotin.com/hallucinations/" rel="nofollow">https://www.damiencharlotin.com/hallucinations/
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I've talked to a lawyer about how they handle this. They do indeed double-check everything, since it'd be embarrassing (or worse) to send hallucinated statements to opposing council or to the court. They still find the assembly a huge time saver
But based on stories in the news on the subject, not everyone has this same level of diligence
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You can get an effectively-zero hallucination rate with the right setup already.
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Then again, nobody will have money to buy anything at this rate, so in all liklihood, this is a total non-issue.
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You. Don't take legal advice from a word calculator.
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That will be a decacorn product or more.
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I don't think you can. What I get from this article is that this is not a product they're going to sell to average consumers.
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<a href="https://commonpaper.com/standards">https://commonpaper.com/standards
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And yes, even contracts drafted for millions of $ have oversights and unlawful or unenforceable terms.
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As much as I hate to see it. They are now threatening industries like Engineers, Game Developers, Accountants, 3D modelers, 3D animators, Video Production, Audio Production, Therapist, Tax Auditors, Journalists, Authors, Artists, Mathematicians, Product managers, Every type of analyst and pretty much any other job that can be done behind a computer screen.
We have big problems for humanity.
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The biggest problem is that we're conditioned by a paradigm that frames these as problems.
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Real estate, food, energy, mobility.
That will be done with money. Or violence. Either way, a scary future to people when labor doesn't provide any value. Elon promises abundance, but what can he do against greed?
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For a short time in history, the ability to obsessively focus on intellectually interesting abstract concepts was highly lucrative, but just as quickly we returned to the laws of nature: those who can lift and move succeed, those who can only think are automated out of existance.
We go from a species increasingly seeing themselves as "brains with bodies" to "amazing bodies with weak brains". The limitation of robots and AI in the physical realm, power hungry, mobility limited are contrasted with human values: energy efficient, highly mobile and dexterous, extremely good strength/speed/size ratios. The brain on the other hand, while energy efficient, is completely outclassed and seen as we see our swimming/jumping abilities: a novelty for sports, but nothing we seriously consider a defining human trait.
The smartest humans can fill weekends with novelty pursuits like building circuits, games, programs, etc. But they are about as useful as whittling and hobby woodcraft, something to pass time, but ultimately of no economic value.
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[0]<a href="https://www.technologyreview.com/2026/06/04/1138391/courts-coping-ai-lawsuits/" rel="nofollow">https://www.technologyreview.com/2026/06/04/1138391/courts-c...
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You dropped this /s
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Creating virtual products get cheaper, so shouldn't it even decrease if everyone vibe codes their app for less than a dollar instead of hiring a dev team for 50k or ordering a white label app or spending 3 dollars to buy an existing app?
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Jordan-117 · · focus · HN ↗
<a href="https://www.ftrain.com/nanolaw" rel="nofollow">https://www.ftrain.com/nanolaw
mt_ · · focus · HN ↗
the cost of making a legal argument can collapse while the cost of reaching an enforceable, legitimate decision may go higher, which will gate the "justice" system even more.
pbkompasz · · focus · HN ↗
alexfringes · · focus · HN ↗
WolfeReader · · focus · HN ↗
iphonecorridor · · focus · HN ↗
JumpCrisscross · · focus · HN ↗
rayiner · · focus · HN ↗
10000truths · · focus · HN ↗
rayiner · · focus · HN ↗
At the end of the day, litigation is conflict resolution. You don't just need a decision, you need a decision from someone authoritative enough to bully Fortune 500 CEOs into submission to accept the judgment.
sva_ · · focus · HN ↗
giarc · · focus · HN ↗
They are also really good at making stuff up as evidenced by the many, many, many examples you read in the news about actual lawyers using AI to write briefs that are full of errors and hallucinations.
In civil courts, you'd likely get more sympathy from a judge if you represented yourself and admitted your lack of understanding, rather than try to appear as someone you're not because you wrote some prompts and copied the output.
tokioyoyo · · focus · HN ↗
The stupidest analogy is open source projects having a hard time accepting LLM generated PRs from the masses, because review process is the bottleneck.
No idea how to fix this, to be honest. In coding world, with some mental gymnastics, I can see code not being reviewed by people anymore. In courts, things generally have more consequences, and you can’t really roll back decisions that easily.
soco · · focus · HN ↗
aucisson_masque · · focus · HN ↗
I don’t know in the USA but in France, if it’s deemed that you launched a lawsuit knowing very well it wouldn’t succeed, you are susceptible to get a 10k€ fine. Even jail in serious cases.
underlipton · · focus · HN ↗
IME the American legal system is set-up to discourage litigation, though. A common tactic is to bury your opponent in the threat of heavy damages or jail-time to get them to settle for what you were originally after, which courts are perfectly happy to facilitate because it gets a potentially lengthy trial off their dockets. They'll punish (or be biased against) whichever party seems responsible for not accepting a "reasonable" settlement.
Algorithmic abuse of the system to extract payments already exists in the form of the debt collection industry.
gamblor956 · · focus · HN ↗
That's not how litigation actually works in this country. Unless the plaintiff can actually prove damages, there's no threat of "heavy" damages. The primary economic concern is spending a lot of money on legal fees, which is the primary trigger for getting businesses to settle instead of litigate. It doesn't work so well against people though.
They'll punish (or be biased against) whichever party seems responsible for not accepting a "reasonable" settlement.
That is false and any judge caught doing that would be removed from the bench, immediately. The judge does not exercise any judgement over what a "reasonable" settlement is as they don't and wouldn't know what is reasonable until the facts have been presented...at trial.
Algorithmic abuse of the system to extract payments already exists in the form of the debt collection industry
The debt collection system doesn't use the court system at all. Assuming you are referring to individual debts, not corporate debts, debt collectors have a very low success rate in court since (a) they have to prove the debt is valid, (b) that they now own the debt contract, and (c) they did not violate any laws in the pursuit of collecting on that debt. A and C are actually really hard for a third-party debt collector to prove.
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Revanche1367 · · focus · HN ↗
pampas · · focus · HN ↗
alansaber · · focus · HN ↗
piker · · focus · HN ↗
> API customers including Harvey and Legora will be able to build on Astra for Law, bringing this intelligence into their own products and workflows.
In other words: "no, no, we're not eating our children to prep for the IPO. Don't worry."
forrestthewoods · · focus · HN ↗
elpakal · · focus · HN ↗
Found that to be very interesting
rayiner · · focus · HN ↗
ericd · · focus · HN ↗
Very much a work in progress, only federal and state so far, no municipal codes yet, and no case law yet. Big hole, I know. Also working on making the search ranking work better.
manyatoms · · focus · HN ↗
ericd · · focus · HN ↗
Alternatively, if someone else knows an all-in-one option that exists, I wouldn't mind retiring those crawlers...
timschmidt · · focus · HN ↗
rayiner · · focus · HN ↗
datsci_est_2015 · · focus · HN ↗
Something1234 · · focus · HN ↗
ericd · · focus · HN ↗
qingcharles · · focus · HN ↗
Then if you want to really get into it, The People should also be able to access trial court level, and at that point you have over 3000 distinct court systems with their own access systems, usually requiring logins and CAPTCHAs, and half of them not even having anything accessible online at all, and the other half only having recent stuff online and the rest rotting in a flooded basement.
mlissner · · focus · HN ↗
ericd · · focus · HN ↗
rzzzt · · focus · HN ↗
- <a href="https://okfn.de/en/projekte/bundesgit" rel="nofollow">https://okfn.de/en/projekte/bundesgit
- <a href="https://github.com/bundestag/gesetze" rel="nofollow">https://github.com/bundestag/gesetze
ericd · · focus · HN ↗
tfehring · · focus · HN ↗
ericd · · focus · HN ↗
teiferer · · focus · HN ↗
alansaber · · focus · HN ↗
jmkd · · focus · HN ↗
OpenAI didn't need to name Legora and Harvey in the second paragraph of the launch post.
They are pre-empting the obvious interpretation of Astra for Law: that moving this far up the legal stack puts them in direct competition with their biggest legal AI customers.
“Don't worry, they can build on us” is a pretty conspicuous message to include on launch day.
They have clearly thought about some pessimistic outcomes.
TZubiri · · focus · HN ↗
Vendor-neutrality for LLMs is such a weak thesis all around, whether for providers or consumers. It weakens the product by being promiscuous and gains no material benefit at all.
LLMs are magic byte(byte) functions, it doesn't make sense to say "we have different providers for magic".
datadrivenangel · · focus · HN ↗
Vendor-neutrality helps reduce lock-in, and OpenAI and Anthropic are big enough that the reduction is valuable.
noisy_boy · · focus · HN ↗
alansaber · · focus · HN ↗
timpera · · focus · HN ↗
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alansaber · · focus · HN ↗
JumpCrisscross · · focus · HN ↗
This is everything OpenAI have to say about privacy in this announcement. No guarantees. No promises. Just a pinky-swear promise.
Anyone trusting them–or a lawyer who relies on them–for legal work deserves what they get.
dathinab · · focus · HN ↗
the kind of work mostly done by juniors not yet through their final exam and other "non" lawyers etc.
so it's a slippery slope of "lets just use it for <this> things where it doesn't matter" and then out of laziness and convenience it creeps into all the other places (at least for drafts).
dd8601fn · · focus · HN ↗
There’s another case making headlines every week.
I get the feeling a lot of them won’t care about this stuff.
byzantinegene · · focus · HN ↗
dzonga · · focus · HN ↗
they need to pick a lane and optimize for it. coz at their size they can't serve the application layer (a.i startups who can fine-tune models will eat their lunch)
if they gonna do a consumer play - then go ham on that.
otherwise they're gonna get caught in the dreaded middle valley.
estetlinus · · focus · HN ↗
scrollop · · focus · HN ↗
noir_lord · · focus · HN ↗
You can afford to play silly buggers when you have dumpster trucks of money backing up to your door every day see also: Meta.
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Tanjreeve · · focus · HN ↗
OpenAI doesn't have any of these things. They have products that they're paying for customers when the market they're in is rapidly converging on fighting for API reasoning as part of enterprise systems and fighting a race to the bottom for fickle consumer solutions that will be eaten by open source.
alansaber · · focus · HN ↗
tuesdaynight · · focus · HN ↗
epolanski · · focus · HN ↗
Provisioning and contracts and data retention was just an extension to review of existing ones.
Nobody serious is going to risk sending sensible data to OpenAI/Anthropic, etc because "the benchmarks have shown +8% performance there and +2% there". Irrelevant.
jackb4040 · · focus · HN ↗
I suspect that half-assed announcements like this are a result of different people internally with conflicting incentives resulting in a split-the-baby solution.
WarmWash · · focus · HN ↗
hahajk · · focus · HN ↗
stockresearcher · · focus · HN ↗
adzm · · focus · HN ↗
stockresearcher · · focus · HN ↗
In the real world, lawyers submit detailed bills and their clients examine them. If you don’t, that’s on you.
epolanski · · focus · HN ↗
program_whiz · · focus · HN ↗
gabhuzk · · focus · HN ↗
[dead]
elpakal · · focus · HN ↗
slowhadoken · · focus · HN ↗
Ecstatify · · focus · HN ↗
alansaber · · focus · HN ↗
Ecstatify · · focus · HN ↗
TomGarden · · focus · HN ↗
keeda · · focus · HN ↗
TomGarden · · focus · HN ↗
krm01 · · focus · HN ↗
It’s cleaner.
john_strinlai · · focus · HN ↗
epolanski · · focus · HN ↗
People confuse slop with "bad", but slop isn't bad per se, it only becomes bad when real effort was required.
trollbridge · · focus · HN ↗
samtp · · focus · HN ↗
trollbridge · · focus · HN ↗
samtp · · focus · HN ↗
epolanski · · focus · HN ↗
williamcotton · · focus · HN ↗
samtp · · focus · HN ↗
<a href="https://www.reuters.com/legal/litigation/lawyer-state-farm-fined-over-ai-hallucination-los-angeles-lawsuit-2026-09-14/" rel="nofollow">https://www.reuters.com/legal/litigation/lawyer-state-farm-f...
williamcotton · · focus · HN ↗
samtp · · focus · HN ↗
williamcotton · · focus · HN ↗
samtp · · focus · HN ↗
williamcotton · · focus · HN ↗
samtp · · focus · HN ↗
williamcotton · · focus · HN ↗
samtp · · focus · HN ↗
<a href="https://www.reuters.com/legal/litigation/appeals-court-warns-about-ai-slop-filings-weighs-punishing-lawyer-2026-09-17/" rel="nofollow">https://www.reuters.com/legal/litigation/appeals-court-warns...
It's everywhere and not hard to find if you make even the most modest effort.
williamcotton · · focus · HN ↗
Honestly, this word has lost all meaning, outside of perhaps “any use of AI”.
Well at least I know where team “lawslop” is coming from. Thanks, I guess?
samtp · · focus · HN ↗
endymi0n · · focus · HN ↗
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cmcclellan · · focus · HN ↗
6thbit · · focus · HN ↗
Is the play here a set of specialized harnesses using their best general model?
aaimnr · · focus · HN ↗
It's analogous to crypto. Started from some noble anti-authoritarian ideas and morphed into machine that removes any friction for capital - whoever has the most money will keep gaining the most.
jatora · · focus · HN ↗
xwkd · · focus · HN ↗
aaimnr · · focus · HN ↗
Hence the crypto analogy - it was also supposed to "democratize", but the opposite happaned - it only further empowered the most powerful. Imagine legal case so purposefully complex that only those with access to best models have chances to participate and win the dispute.
wartywhoa23 · · focus · HN ↗
charcircuit · · focus · HN ↗
wartywhoa23 · · focus · HN ↗
A headline from Russia to consider:
The Supreme Court approves the plan to deploy AI in Russian courts: the document states that by 2030, more than 95% of judges will have to use AI regularly. The risk matrix cites AI hallucinations and opposition from the judicial community.
<a href="https://www.rbc.ru/technology_and_media/15/09/2026/6aa8e03421f80289f2f2a8ab" rel="nofollow">https://www.rbc.ru/technology_and_media/15/09/2026/6aa8e0342...
alansaber · · focus · HN ↗
freejazz · · focus · HN ↗
keeda · · focus · HN ↗
amelius · · focus · HN ↗
john_strinlai · · focus · HN ↗
alansaber · · focus · HN ↗
qingcharles · · focus · HN ↗
shicholas · · focus · HN ↗
droidjj · · focus · HN ↗
I have had some success using frontier models from the last 6ish months, but only when I can break up my work into discrete and verifiable tasks. For example, I had ~15k pages of discovery I needed to dig through for a summary judgment motion. Instead of just asking Claude to find the best evidence, I asked it first to run a clean, high quality OCR pass (it was almost entirely PDFs). Then I had it generate embeddings and write some reusable python scripts to make keyword and semantic searching easy for agents. While I was writing the brief, I would routinely ask my agent (Claude Code) to use both keyword and semantic searching to find the best evidence supporting whatever assertion I was trying to make. I trusted it because there were traces I could follow.
In other cases/situations, I’ve tried just giving a model access to all the docs and saying “write a brief arguing X,” but it’s always terrible at this. It writes briefs with lots of evocative jargon and rhetorical flourish, but a low signal-to-noise ratio.
Again, I’m sure others’ experiences differ based on workflow, legal area, etc.
[deleted] · · focus · HN ↗
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shimman · · focus · HN ↗
Digory · · focus · HN ↗
But lately, I’ve been taking hints from the “company brain” models, where it develops a running model of the case, and assesses each new piece as it comes in and updates the file.
I’ve also been using “Ralph Wiggum”-type models where you pass letter or contract drafts back and forth between agents with different goals (rules compliance, grammar, conciseness, ai slop detector, an opposing counsel critic, etc.). After a few rounds, it’s not perfect — but I start with a very good first draft in my hands.
Otterly99 · · focus · HN ↗
Are they separate searches, or some sort of weighted search?
NoboruWataya · · focus · HN ↗
keeda · · focus · HN ↗
Interesting! In other unrelated domains, models seem more willing to take a position. It may be nuanced, but they do tend to take a stance. I think it's good that it leaves the interpretation to humans, but I wonder if this is also some sort of a guardrail to minimize liability...
mcmcvane · · focus · HN ↗
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mullingitover · · focus · HN ↗
If you automate lawyers out of a job, you can absolutely automate lawmakers out of jobs next. (Not that this would be a bad thing? Maybe pervasive agents for everyone can be the gateway drug to a "this time it's different!" workable direct democracy)
jimmyjazz14 · · focus · HN ↗
halamadrid · · focus · HN ↗
Its just like code I suppose, if you can read and understand and validate, you can use it to scale and otherwise it could end up being a vibe effort.
rayiner · · focus · HN ↗
Even without that, I think it'll be extremely valuable to clients to allow them to answer simple questions without a lawyer, figure out the lay of the land so they can supervise their counsel, etc.
throwaway20222 · · focus · HN ↗
samtp · · focus · HN ↗
That is an incredible statement that could not be further from the truth. Large scale adoption of email, searchable document databases like Westlaw, LexisNexis, PACER, etc.. , OCR Software, electronic signatures, and tons more have had a much more defineably positive impact on the legal profession since the internet came about.
rayiner · · focus · HN ↗
samtp · · focus · HN ↗
alansaber · · focus · HN ↗
qarl · · focus · HN ↗
But programmers have this concept of a "code review" where another person looks at the code to look for problems.
We use this same technique with our LLMs. Most mistakes are caught by having a second LLM look at it. Doesn't even need to be a different model - just make sure it has a different context.
flyinglizard · · focus · HN ↗
Not so in other knowledge work. There's no test harness for a contract and error is non-recoverable. Likewise in finance. There are specific ways of doing things and these ways are many times set in regulations. LLMs can assist all day, sure. But replacing the human, in highly regulated, zero tolerance for error environment?
qarl · · focus · HN ↗
flyinglizard · · focus · HN ↗
>> You should know - for coding they make terrible mistakes as well.
>> But programmers have this concept of a "code review" where another person looks at the code to look for problems.
jll29 · · focus · HN ↗
Logically, this actually doesn't make sense strictly speaking because the sentence creates a paradox: doesn't it make clear whether it includes itself or not, and each reading ends up in trouble. There is a "tradition" in law around the world to accept the only benign reading of such clauses, which I always found funny given that in all other ways lawyers adopt the most adversarial mindset imaginable.
telliosic · · focus · HN ↗
It doesn't matter how smart someone is, they need specialized training to be good at these jobs. Specialized training in the area the company specializes in.
There is a category error in all this that is hard to think about because of the normal discourse and ordinary language. We say people work in "finance" but no one works in just "finance". They work at a company that has a specialization within "finance", inside a hierarchy that has specialization on top of specialization.
What we really need is exactly what we don't have and aren't going to get. A type of LORA that generalizes the task specific intelligence needed from a very small sample size and that in practice makes so many less mistakes in a highly regulated, zero tolerance for error environment that it is irresponsible to not use the model.
I have worked in this type of environment for 3 years and I have made zero mistakes in 3 years. The people that make even a small number of mistakes get fired.
Any real automation in this area is going to be incredibly slow and piecemeal over a long period of time because even an amazing model would need a long time to prove itself against what the human standards for error rates are.
int_19h · · focus · HN ↗
I find that the number of issues discovered is noticeably higher if you do use different models though. I'm doing some very finicky things (formal semantics) and find that there's value in review panels as large as 5 different models from different families. It gets even more profitable if you set it up as a truly agentic panel where after writing their own separate reviews they get to see what others have said, and adjust their positions or defend them etc. Some models are not that good by themselves but can be surprisingly good at finding flaws in others' reasoning (Grok for example).
chrisjj · · focus · HN ↗
More to the point, programmers have this concept of a complier - which delivers 100% success in catching uncompilable errors.
Lawyers don't.
qarl · · focus · HN ↗
Defensive much?
chrisjj · · focus · HN ↗
As much as needed.
qarl · · focus · HN ↗
cannonpalms · · focus · HN ↗
shim__ · · focus · HN ↗
alansaber · · focus · HN ↗
alansaber · · focus · HN ↗
charcircuit · · focus · HN ↗
Razengan · · focus · HN ↗
The outcome of a case shouldn't depend on someone's fallible ability to recall facts or convince other people or point their index finger*
Law should generally be deterministic. One's CHA stat should have no bearing on justice.
There should still be human judges, but the middleman between the judge and petitioner could easily be removed, and have generally been seen as leeches since forever anyway.
Though, like how the USA opts to remain in the Stone Age with regard to tax filing because of lobbying by tax software companies, this faction of society will flail the hardest before they admit they're obsolete.
----
* What's a lawyer's favorite programming language? Objection C.
[deleted] · · focus · HN ↗
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geodel · · focus · HN ↗
cannonpalms · · focus · HN ↗
samtp · · focus · HN ↗
autoexec · · focus · HN ↗
A lot of communication is conveyed through more than the words themselves though and even though it's often misinterpreted people put a lot of value in that information. I suspect that even if we took away the ability to see the people involved judges and jurors would still find bias in the tone/quality of people's voices. Even if everything was reduced to text they'd find bias based on word choices, phrasing, spelling, and grammar.
alansaber · · focus · HN ↗
Razengan · · focus · HN ↗
A Mediocre Lawyer not winning a winnable case = not a good thing.
Say a starving child steals a loaf of bread. The law says all theft is at least 1 year in prison. But the judge can see that the child is actually destitute and it was his first time. The judge could shorten the sentence to 1 week; that's fine, there should be room for interpretation and leniency.
But it should NOT depend on whether that child had a persuasive lawyer or not.
A good "AI Lawyer" would simply behave as how ALL lawyers SHOULD: Simply present the facts, the laws that apply to those, offer suggestions for the verdict, and the possible long-term consequences for each possible verdict, without injecting dramatization, exaggeration, or attempts to pull at heartstrings etc.
janalsncm · · focus · HN ↗
An example is in the banking industry, where making a loan used to require deep analysis of a person’s credit worthiness. Now they use an algorithm (credit scores) which means someone with less experience can do it.
If law follows the same pattern, a job done by someone making $500/hour might be done by someone making $50/hour.
samtp · · focus · HN ↗
notatoad · · focus · HN ↗
but how much of the revenue of the average law firm comes from that, vs the day-to-day "we need this relatively routine contract reviewed" sort of work?
rayiner · · focus · HN ↗
samtp · · focus · HN ↗
So who is going to define your strategy, represent you in court, adapt the strategy to changing circumstances, negotiate with counter-parties on a mutually accepted settlement? A paralegal? An AI model? Please
victorbjorklund · · focus · HN ↗
samtp · · focus · HN ↗
notatoad · · focus · HN ↗
But this is the same story that has played out in other industries. The top tier isn’t at risk. The artist who commands $100k for a commission is still making money. But the artist who makes a living creating background images for corporate presentations doesn’t have a revenue stream anymore. The software developer who makes novel, high-complexity applications is still making money. But the guy churning out Wordpress templates has lost his job. The law firm doing 90% boring corporate boilerplate is next.
citizenkeen · · focus · HN ↗
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CTDOCodebases · · focus · HN ↗
moralestapia · · focus · HN ↗
Not being snarky here but I've encountered some really crappy lawyers and they seem to be doing great ($$$).
It really sucks one cannot publish something like "this guy charged me $5k, wrote my name wrong and forgot important paperwork the day we showed up to court" as that could make you liable for damages. There should be a safe harbor for that.
YawningAngel · · focus · HN ↗
bethekidyouwant · · focus · HN ↗
TZubiri · · focus · HN ↗
That's pretty much what bar associations are for, filing a complaint against an attorney at the bar seems like a pretty standard procedure.
>There should be a safe harbor for that.
A safe harbor would be the opposite, it would be immunity for the lawyer.
CTDOCodebases · · focus · HN ↗
Also for those things you could sue for damages or lodge a complaint for malpractice.
ElProlactin · · focus · HN ↗
Do you know how difficult and costly it is to sue an attorney for malpractice?
CTDOCodebases · · focus · HN ↗
With AI models this option does not exist. I can't sue OpenAI because the contract that I got ChatGPT to draft carelessly exposes me to some type of financial loss. I can't contact the state bar and have Open AI banned from drafting up contracts or doing any other work that lawyers are licenced to perform. Even if I could it would not compare to a lawyer loosing their license to practice for life. If I tell a friend or acquaintance about my negative experience they will still likely use OpenAI for professional work and chalk up my experience to a skill issue or premature use of the technology.
Also note the use of the word "professionals". I was referring to doctors, engineers, accountants in addition to lawyers.
ElProlactin · · focus · HN ↗
> This risk functions as a guarantee.
Except it doesn't, particularly as far as lawyers are concerned. There are almost a million and a half active attorneys in the US. Just 500-600 are disbarred every year, and almost always for money-related violations, not bad advice. Public discipline is also relatively uncommon (about a quarter of 1% of attorneys every year) and usually related to issues like financial impropriety, neglect, undisclosed conflicts of interest and failure to communicate, not disagreement over the quality of advice.
If a lawyer drafts an agreement that causes a loss, a bar complaint will not help you recover your money. You'd need to sue for malpractice. This costs a lot of money and takes a lot of time. Because you're going up against a lawyer, expect the defense to be vigorous, especially, ironically, if you hired an attorney at a good firm. The full weight of the firm will back the attorney and you might find it difficult to find an attorney, as many won't want to be involved in suing a fellow professional in their market.
I don't disagree with your fundamental premise about the value of human responsibility, but these professions have been structured to protect their members and the ABA in particular basically functions like a cartel today.
jcfrei · · focus · HN ↗
cromka · · focus · HN ↗
skeptic_ai · · focus · HN ↗
alansaber · · focus · HN ↗
ww520 · · focus · HN ↗
Law LLM will surely help competent lawyers in their fields with greater sources of knowledge not in their core area of expertise.
samtp · · focus · HN ↗
cannonpalms · · focus · HN ↗
matheusmoreira · · focus · HN ↗
But will their glamorous salaries persist? That is the question that matters.
AI doesn't need to wipe out lawyers. If they just depress salaries enough, virtually nobody is going to want to be a lawyer anymore.
NoboruWataya · · focus · HN ↗
(Not that I think AI will necessarily have that effect. We just don't know yet)
matheusmoreira · · focus · HN ↗
Very few people, if any, are going to bust ass in law school or medical school if they're not going to get rich off it. Better to do literally anything else.
NoboruWataya · · focus · HN ↗
bethekidyouwant · · focus · HN ↗
rayiner · · focus · HN ↗
alansaber · · focus · HN ↗
darth_avocado · · focus · HN ↗
This doesn’t replace lawyers, but paralegals surely will be affected. A good enough model could shrink the number of paralegals needed in a firm.
snoman · · focus · HN ↗
alansaber · · focus · HN ↗
QuiEgo · · focus · HN ↗
moralestapia · · focus · HN ↗
Lawyers can practice, can represent you in court, etc. that's not going away soon.
dd8601fn · · focus · HN ↗
sick_of_slop · · focus · HN ↗
[dead]
psadri · · focus · HN ↗
I had start with asking for a contact with some details I provided. But then I ask the model to be an experienced corporate lawyer and ask me a series of questions to gather the details it needed and then write the contract. The result covered a lot of details that were highly relevant but were absent from the original attempt.
The key insight is that you can lean on the model to cover your unknown unknowns.
dghlsakjg · · focus · HN ↗
psadri · · focus · HN ↗
samtp · · focus · HN ↗
psadri · · focus · HN ↗
jll29 · · focus · HN ↗
This is due to the fact that LLMs are statistical processes that rely on pseudo random numbers in chosing what to say and how to say it to a substantial degree.
inopinatus · · focus · HN ↗
Another one suckered by the plausibility engines.
Buttons840 · · focus · HN ↗
jonplackett · · focus · HN ↗
If the expensive person is still better at getting what _you_ want from a contract then it’s always worth doing that.
There’s a reason lawyers are so expensive to begin with - they do very complicated stuff with very expensive consequences if done badly.
SchemaLoad · · focus · HN ↗
jonplackett · · focus · HN ↗
overfeed · · focus · HN ↗
A lot of contract-lawyering involves getting ahead of when things go south and the two previously agreeing parties find themselves in disagreement.
jjmarr · · focus · HN ↗
mcculley · · focus · HN ↗
1attice · · focus · HN ↗
mcculley · · focus · HN ↗
NoboruWataya · · focus · HN ↗
smelendez · · focus · HN ↗
The interesting question is whether AI can fill a niche these can’t — or, alternatively, help a layperson evaluate a contract they’re asked to sign better than they could themselves.
legostormtroopr · · focus · HN ↗
Contract law has evolved because transfering the ownership of things is fraught with difficulty. Ownership as a concept itself is notoriously hard to define.
Consider housing - when you buy a house you own that land. Except if its an apartment, you just own the internal walls. Or when the government aquires your land through eminent domain. Or mineral rights - which don't belong to you, you just own the top 5 feet of topsoil. Or if you neglect a property and some squats in it. Or if you were given a fraudulent payment, and they take back the property.
Just getting people to agree is notoriously difficult when people have different often conflicting desires.
MiroslavPokorny · · focus · HN ↗
alansaber · · focus · HN ↗
drschwabe · · focus · HN ↗
andriy_koval · · focus · HN ↗
DesaiAshu · · focus · HN ↗
The same has happened with modern finance. Despite more technology that has power to drive more transparent/efficient markets, we have less perfect information sharing and a larger group of middlemen capturing a growing share of profits of the economy
alansaber · · focus · HN ↗
TZubiri · · focus · HN ↗
At the very least because the attorney monopoly assigns a 5ish year of training as PoW and natural personhood as Identity as protection for Sybil Attacks.
If anything, the exclusive right of attorneys to represent clients in court, file motions, and enjoy professional secret, is more valuable, as it's not something AI can ever compete at. (Barring a wild recognition of machines as humans, or an overturn of the impossibility of companies to appear in court.)
cheema33 · · focus · HN ↗
I agree. But, we will need a lot fewer of them. My small company called our lawyer a lot more before the advent of AI. Mostly to clarify a few things or review simpler contracts. Now, for simple things, we do not call them at all.
barbazoo · · focus · HN ↗
jll29 · · focus · HN ↗
(1) Rich people will use human expertise and "the rest of us" will use AI models to get by. This could happen in law, but also in medicine (in particular in societies that - like in the US - do not have universal healthcare).
(2) A positive effect in both domains may be that access to knowledge will be broader and cheaper.
I hope I will be wrong about (1) - I would not like to live in such a two-class society.
alansaber · · focus · HN ↗
TZubiri · · focus · HN ↗
>Its just like code I suppose, if you can read and understand and validate
I share this, when I asked an attorney for a contract, they were much simpler when compared to self redacted or AI redacted contract, it was as if I were rediscovering lots of concepts and I HAD to put them in paper, even if they were defaults and were essentially no-ops.
Comparable to:
> Mkdir $PWD/path
instead of
> mkdir path
or conditions so rare that they don't merit including.
> x = 0
> if x!=0:
> raise Exception("Bit flip by solar rays or otherwise")
yieldcrv · · focus · HN ↗
How to fix the lack of trust which is needed to conduct a transaction
Contracts affix a moment of trust in time, so even when trust is lost between parties the contract has guardrails for behavior and consequences for acting outside those rails
There are many transactions that are completely inaccessible to most people because the need for a contract or lawyer is too high
LLM use allows for those inaccessible transactions to decrease, and get people further along to the point where a lawyer is accessible as well, and economically viable to use
TZubiri · · focus · HN ↗
chadash · · focus · HN ↗
I have worked with many lawyers in my career. The bad ones will look at a contract and tell you fifty things that can be improved. Meanwhile, you take the same contract to a really great lawyer and they tell you that's it's not worth fighting over the changes and to just keep it as is. It's kind of like how a beginner or intermediate software engineer might tell you how you can build out a k8s or auto-scaling fargate cluster for your project and a really senior engineer might look at the same thing and explain that it's not worth worrying about scalability right now.
I find that when I feed contracts to ChatGPT (which I do all the time) it will try to find 50 things wrong with it. For example, as a test, i fed chatgpt an employment offer from a US government agency. It came back with 1152 words and 14 recommended (some of them substantial) changes. Meanwhile, any half-decent employment attorney would probably laugh at me if I asked them to redline an employment offer from the State Department.
k099 · · focus · HN ↗
mbreese · · focus · HN ↗
morgoo · · focus · HN ↗
shim__ · · focus · HN ↗
That might not be due to the contents but rather due to the fact that they won't negotiate I'd presume
chadash · · focus · HN ↗
alansaber · · focus · HN ↗
01100011 · · focus · HN ↗
mekael · · focus · HN ↗
calvinmorrison · · focus · HN ↗
[deleted] · · focus · HN ↗
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airstrike · · focus · HN ↗
I'm currently negotiating with someone who I feel is clearly using AI and this is EXACTLY what has been happening
skeptic_ai · · focus · HN ↗
someothherguyy · · focus · HN ↗
some variant of "oh i am capable of generating text i know nothing about, but it helps to have a human i can rely on to tell me more about the text i know nothing about."
pick up a bachelors degree worth of books to humble yourself
alansaber · · focus · HN ↗
varispeed · · focus · HN ↗
(Fable and Astra are crap at these tasks)
syntaxing · · focus · HN ↗
jayzalowitz · · focus · HN ↗
jonahx · · focus · HN ↗
trollbridge · · focus · HN ↗
jonahx · · focus · HN ↗
underlipton · · focus · HN ↗
kappi · · focus · HN ↗
<a href="https://aeon.co/essays/what-made-law-into-a-white-collar-sweatshop-in-the-1980s" rel="nofollow">https://aeon.co/essays/what-made-law-into-a-white-collar-swe...
smusamashah · · focus · HN ↗
Qwen 3.8 Max and Opus 4.8 score highest.
toephu2 · · focus · HN ↗
nerevarthelame · · focus · HN ↗
> The top is a three-way tie: Muse Spark 1.3 Max, Claude Opus 5, and Claude Fable 5.1 all reach 55.29% all-pass accuracy, a clear ~6-point step ahead of the next model. [Astra for Law reached 54.0%]
> Under partial-credit scoring, Claude Opus 5 reaches 90.58% weighted pass rate but 55.29% under strict all-pass grading, where every rubric check must pass. The gap shows models often get most of an answer right but fail on one or two required elements. [Astra for law reached 90.0%]
<a href="https://www.vals.ai/benchmarks/legal_research" rel="nofollow">https://www.vals.ai/benchmarks/legal_research
[deleted] · · focus · HN ↗
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jackb4040 · · focus · HN ↗
followed a month later by
"Anthropic's Claude inadvertently repeals the 19th amendment"
wartywhoa23 · · focus · HN ↗
"Due to a spontaneous loss of alignment, JustitAI 2.3 pleads the government guilty of war crimes, launches ballistic missiles at several bunkers and tropical islands"
hansonkd · · focus · HN ↗
frustrating that law firms have no liability for these mistakes
I welcome ai law
d0odk · · focus · HN ↗
hansonkd · · focus · HN ↗
Most interactions with big tech firms involve 4-5 people so a basic phone call is $5k-10k. It shouldn't be unreasonable to expect after paying $80k for a financing round that they issue the right docs to the right people.
alexnewman · · focus · HN ↗
nsoseka · · focus · HN ↗
alasano · · focus · HN ↗
When opportunity cost isn't a thing anymore because it reaches every corner of the planet simultaneously faster and builds better than any human can.
There's no reason to let others build on top of AI, except if the AI determines that it needs capitalism to continue because it's paperclip goal is to maximize shareholder value.
jansport123 · · focus · HN ↗
wartywhoa23 · · focus · HN ↗
A hefty asteroid will. The whole situation today is so Tower Of Babel 2.0...
jackb4040 · · focus · HN ↗
margorczynski · · focus · HN ↗
whazor · · focus · HN ↗
Instead, if you resolve your dispute outside of court, you don’t need a lawyer. If both parties use ChatGPT to find the relevant laws or read contracts, they could come to an agreement without expensive legal fees.
reactordev · · focus · HN ↗
elpakal · · focus · HN ↗
I also see a lot of watermark removal services popping up as a result.
alansaber · · focus · HN ↗
throw03172019 · · focus · HN ↗
Our counsel made a few edits where it clearly drafted in favor of the customer instead of us.
victor9000 · · focus · HN ↗
freejazz · · focus · HN ↗
akg_67 · · focus · HN ↗
alansaber · · focus · HN ↗
LandenLove · · focus · HN ↗
"Felt like a significant step toward legal-focused AI."
"Showed strength across key aspects of legal research."
Madmallard · · focus · HN ↗
Vachyas · · focus · HN ↗
If this is true that must mean there are a good deal of cases settled using precedent "gotchas" where both sides knew that without the "load-bearing" precedent the outcome would've definitely been the opposite. (i.e precedents almost always trump even valid arguments)
alansaber · · focus · HN ↗
msy · · focus · HN ↗
alansaber · · focus · HN ↗
ivraatiems · · focus · HN ↗
They recently bought a Claude subscription and began using Claude to do the initial read of the documents and output JSON they can import into their internal systems. The work still must be reviewed by an attorney - Claude is nowhere near making the kinds of judgments a lawyer would make about this content - but it has increased their throughput from 2-3 documents an hour to 8-10 documents an hour by killing the busy work.
LLMs have great advantages for this kind of work - but not for decision-making. I just don't see OpenAI ever admitting that.
(I've left some details intentionally vague because this is a very specific area of law and I don't want my friends to be identified without their consent.)
[deleted] · · focus · HN ↗
[deleted]
lemonlimetea · · focus · HN ↗
[dead]
MiroslavPokorny · · focus · HN ↗
You havent given any proofs or even comments that the work is the same level of quality or accuracy.
ivraatiems · · focus · HN ↗
MiroslavPokorny · · focus · HN ↗
The statements in the post are opinions, there is no actual PROOF they are true, and thats my point.
ivraatiems · · focus · HN ↗
It's an incredible level of hair-splitting to say "well, all these people who know what's good agree it's good, but that's not technically PROOF".
I'm just a guy on the Internet posting comments. It's tautological that I can't "prove" anything if what you want is hard evidence right in front of you. What's the point of pointing it out?
samtp · · focus · HN ↗
nradov · · focus · HN ↗
ivraatiems · · focus · HN ↗
TallGuyShort · · focus · HN ↗
newyankee · · focus · HN ↗
refurb · · focus · HN ↗
You’ve accurately stated that AI isn’t as rigorous as a trained attorney. Doesn’t that mean that every single datapoint must be confirmed by a human?
How is that quicker than just using a human to read the content and make the call? Data entry savings?
juiceland · · focus · HN ↗
cromka · · focus · HN ↗
margalabargala · · focus · HN ↗
"Write a python script that breaks down this PDF by X feature" would not hallucinate anything in the PDF. Certainly you could trivially double check that all text in the extracted JSON was in the text layer of the PDF.
jeffbee · · focus · HN ↗
terminalcommand · · focus · HN ↗
rayiner · · focus · HN ↗
NateEag · · focus · HN ↗
LLMs change not a whit, and there's no one to take responsibility for the failure (and thus no way to fix it).
As the new variation on the old theme has it, "A computer can never be held accountable, and so very many people are trying to get them make management decisions."
IanCal · · focus · HN ↗
enraged_camel · · focus · HN ↗
NateEag · · focus · HN ↗
But they do learn and improve.
The models don't (yet).
hollerith · · focus · HN ↗
It might be that the models learn and improve in this sense faster than a human child does.
juiceland · · focus · HN ↗
LLM output is nondeterministic and humans take responsibility for the failure the same way they take responsibility of a photocopy is too dark.
NateEag · · focus · HN ↗
You mean, they notice it's too dark right after making it, change the settings, do it again, and give you the good copy?
Because yes, that's my experience of humans.
podocarp · · focus · HN ↗
stevesimmons · · focus · HN ↗
eru · · focus · HN ↗
chrisjj · · focus · HN ↗
egorfine · · focus · HN ↗
mcmcvane · · focus · HN ↗
[dead]
chrisjj · · focus · HN ↗
margalabargala · · focus · HN ↗
chrisjj · · focus · HN ↗
ferngodfather · · focus · HN ↗
For instance, if you can say:
"Refer to the database schema in x.sql as your source of truth for the database structure we want to import int. Do not invent data, tables or columns that do not exist. Carefully match all output against this database schema and do not create output that doesn't exist if it does not match the schema, simply skip it."
You will end up with a far better result in my experience.
Gotta treat it like a child.
chrisjj · · focus · HN ↗
ivraatiems · · focus · HN ↗
But now it's comparing already filled columns on a spreadsheet, not copy-pasting every single thing from an (often uncopyable) PDF.
chrisjj · · focus · HN ↗
ivraatiems · · focus · HN ↗
juiceland · · focus · HN ↗
edmundsauto · · focus · HN ↗
lolakutty · · focus · HN ↗
edmundsauto · · focus · HN ↗
Whether that is useful measurement I suppose depends on the circumstances.
eru · · focus · HN ↗
ivraatiems · · focus · HN ↗
It took a human attorney 20-30 minutes on average to manually copy-paste data from these PDFs into a spreadsheet (while also fixing any errors they found in the document and re-checking for quality).
Now, the AI copies everything into the spreadsheet in a small amount of time, and then the human reviews it. It takes maybe ~5-7 minutes to scroll to the appropriate pages in the document, read the lines vs the spreadsheet, and make corrections. So you've gone from 2-3 items an hour to ~8-10 items an hour.
Maybe you could pay someone to develop an OCR/ML application that could do this. But that project would never be profitable, even with the time savings. At the cost of a couple Claude subscriptions, it makes sense.
barrenko · · focus · HN ↗
Sample is around 300 court dates, shy under 1k files.
At best I'm building a claude skills file.
newAccount2025 · · focus · HN ↗
eru · · focus · HN ↗
And Claude should write down the mistake in a sealed envelope, so it doesn't make into the database.
A review that doesn't find the mistake counts as invalid.
k4tsu · · focus · HN ↗
camdenreslink · · focus · HN ↗
eru · · focus · HN ↗
stymaar · · focus · HN ↗
A better use of these Claude subscription would be to develop the app (which it can pretty much do at that point) and you could iterate to make the workflow even more efficient than your current one.
ivraatiems · · focus · HN ↗
eru · · focus · HN ↗
Keep in mind that the task is fixed, so as the frontier of AI advances, you can switch to a cheaper trailing edge system and still get the same or even better performance for this task.
stymaar · · focus · HN ↗
The difference between a tech-savyy person, and a non-tech-savyy person has always been mostly in the later's head, but this is even more true now that we have pocket assistants who can answer pretty much all of our questions in a language tuned to our level of understanding.
ricky54 · · focus · HN ↗
tkgally · · focus · HN ↗
refurb · · focus · HN ↗
Your experience mirrors my own. AI is great for parsing data that can take up a huge amount of time. My only concern is whether or not it’s done accurately. I wouldn’t use it for anything where mistakes cause serious consequences.
2Gkashmiri · · focus · HN ↗
I see problems in LLMs doing research, making drafts, etc.
I see 3 kinds of potential users.
1. Non legal background people trying to avoid going to a lawyer. They should definitely NOT use an LLMs.
2. Fresh out of law school graduates.
They think they can do fast work, draft quick replies, do fast case research, enh. They should go the traditional route of interning, learning the "art", they probably won't need it because they will learn "how the law works"
3. Established attorneys. They usually have templates made for most things, over their career, they have established routines of making things fast, maybe it can help them but to say replacing good chunk of work or offloading to LLMs isn't probably going to go well.
There is a reason why interns are made to do grunt work. The "chain of command" is built so they learn on basic stuff, learn to make decisions, etc. Without these basic decisions under their belt, an intern can't take bigger decisions later on. They just won't know....
jcims · · focus · HN ↗
3 kinds of users that don't scare the shit out of you.
My buddy works with lots of folks that have gone all in on Harvey. There are other kids of users.
nullsanity · · focus · HN ↗
[dead]
newyankee · · focus · HN ↗
If there is no precedence for X happening when Y , Z, P, Q, R are special combinations , the judge decides and sets precedence. But if another judge interprets it differently with similar set of circumstances it is not considered incorrect I presume especially if in different jurisdiction unless overridden by a higher court. This is my layman understanding but I think this design is wrong and essentially where human subjectivity controls the system.
Subjectivity is not totally avoidable in law but the goal of the legal system should be reduce it as much as possible along with ambiguity.
applfanboysbgon · · focus · HN ↗
Law is intentionally not code. The world is not something you can program.
rayiner · · focus · HN ↗
azan_ · · focus · HN ↗
gf000 · · focus · HN ↗
amunozo · · focus · HN ↗
applfanboysbgon · · focus · HN ↗
Since this is a thread about using ChatGPT for law, I should note that this is actually one of the most important reasons you'd rather hire a lawyer than ChatGPT to represent you. A good lawyer or firm will know the local judges and how they tend to lean on ambiguities in their area of expertise, and will be able to use that information to both advise you and tailor their arguments to appeal to the judge's sensibilities. There is an element of unfairness to this, to be sure, but you'd find much more unfairness really quickly with machine-generated judgments because of how messy and non-compressable real world circumstances are.
amunozo · · focus · HN ↗
p0deje · · focus · HN ↗
In my experience, it is incredibly hard, practically impossible, to find a lawyer who will even talk to you. I think this is a valid use case to get at least some understanding what the next steps might be and if it even makes sense to seek legal representation.
fy20 · · focus · HN ↗
There was a post here a few weeks ago about a UK court being inundated with some kind of claims (unfair dismissal?). To submit a claim you do not need a lawyer, but the process is (intentionally?) vague and very complicated, so it takes a lot of effort to figure it out yourself. But AI makes that kind of stuff easy.
AI is not going to replace layers billing big corporate clients millions a month, but it will replace things that are fairly standardized processes, that don't require a lawyer, but today are just too complicated for regular people.
ferngodfather · · focus · HN ↗
I'm not sure there's quite accurate. The form is really not that difficult to complete.
It's basically: Party details, type of claim, particulars, damages
Obviously knowing these details requires some legal knowledge but I actually think ET claims are easy enough to bring if you've got the time to do a little research and build your case. Almost all ET judgments are public so there isn't the usual difficulty with research as you get with law reports being restricted either.
<a href="https://assets.publishing.service.gov.uk/media/65bcbd214a666f000d1747ba/ET1_0224.pdf" rel="nofollow">https://assets.publishing.service.gov.uk/media/65bcbd214a666...
eru · · focus · HN ↗
On the margin, AI will drop these guys' billable hours.
eru · · focus · HN ↗
Really? I find them quite talkative. But I'm not sure what kinds of questions you are pestering them with?
In any case, the whole discussion reminds me of people using LLM to replace medical professionals.
For both: unless you have a doctor or a lawyer always on standby, you have to make a decision on whether to even go and seek out one of these professionals. By definition, you make that decisions without professional help. I think LLMs can help you there with the initial research to decide whether it's even worth it to contact the professionals.
consensus1 · · focus · HN ↗
rayiner · · focus · HN ↗
eru · · focus · HN ↗
That very first image uses a different inflation indices for each of the two lines in the graph.
They also only post pictures without linking to sources.
amunozo · · focus · HN ↗
roncesvalles · · focus · HN ↗
I used LLMs to replace a lawyer this year to great effect. I successfully advised myself as to the right strategy and drafted an immigration petition in the correct language. Granted it wasn't 100% LLMs (I also supplemented it with "traditional" online research and wrote the letter myself using the LLM version as rough guidance), but still, I certainly would've gone to a real lawyer in 2024 for this stuff but didn't.
Professional advisory work can be divided into two types:
1. Once you know the rules of the game, the next move is immediately obvious.
2. Knowing the rules is not enough to know the next move -- that requires judgement and experience.
LLMs in the hands of someone smart and savvy can easily replace the first type of work.
throwaway89864 · · focus · HN ↗
Lawyers nearly universally tend to: convince clients they need a lawyer; promote extreme views; charge legal fees (that ultimately result in financial damages to the client). There are no winners in this game, except for lawyers, who are having a lovely time. Even if you won the case, you've lost, because the pie got smaller due to lawyer fees.
eru · · focus · HN ↗
danielrhodes · · focus · HN ↗
throwaway89864 · · focus · HN ↗
There is a chance of de-risking yourself, but the chance of a bloodbath is even higher.
And yeah, the sharks are trying to convince you that they are "your" sharks, while it is quite clear that their mates are the other sharks.
LtWorf · · focus · HN ↗
zhivota · · focus · HN ↗
These situations usually are not ones that an individual can justify the time or money to contact an actual lawyer, but then if they do decide to contact one they will come in with better questions and more of a sense of what they are expecting.
This is similar to medical. Should you use LLM to diagnose yourself, treat yourself with prescription drugs you buy from shady gray market online sellers? No. But you can use it very well to know when it's time to go to the doctor and what to ask.
eru · · focus · HN ↗
LLMs can help with that. I don't think they are worse at this than me trying to figure this out all by myself.
littlecranky67 · · focus · HN ↗
eru · · focus · HN ↗
That might be true, but that doesn't mean you benefit from training up juniors.
elysianfields · · focus · HN ↗
"You can't trust the output, it doesn't understand bigger systems"
"Its an art, you need to learn the ropes of it to truly write good code"
Its a very dangerous line of thinking. Software engineering will never be the same, as writing code has basically vanished from the daily workflow. Not for every specialized usecase, but for many.
inemesitaffia · · focus · HN ↗
stymaar · · focus · HN ↗
At my company we're also in the process of deploying a system that does exactly that. And what's interesting is that you absolutely do not need a frontier model for that, a small VLM (vision-language model), with optionally a little bit of fine-tuning, gives you the same output quality at a fraction of the latency and cost.
dguest · · focus · HN ↗
It's also not really clear if everyone is going to want a frontier model when the real implications sink in. Maybe we'll get sick of incomprehensible code optimizations and people wile tire of reading AI prose that feels ever-more-human. There might be a few use cases, but who is going to pay for this when providers start charging enough to be profitable.
Cthulhu_ · · focus · HN ↗
But that's phase two, phase one is finding localized problems to solve using LLMs and productize them. I'm reminded of cloud tech, where phase one was changing software to run in the cloud, and phase two was optimizing costs.