The Structural Barriers to AI Lawyers(diffuseai.pub) |
The Structural Barriers to AI Lawyers(diffuseai.pub) |
> But law isn’t actually code, and society and courts aren’t computers. [...] the law is not deterministic. You simply cannot take the facts of a case, the law as written, and predict the outcome of that case with any real certainty, even though the formality of the legal system makes people think it works like a computer — that it’s predictable.
> [...] it’s actually ambiguity that’s at the very heart of our legal system. It’s ambiguity that makes lawyers lawyers. Honestly, it’s ambiguity that makes people hate lawyers because it’s always possible to argue the other side, and it’s always possible to find the gray area in the law. That’s why prosecutors end up working as defense attorneys and why our regulators tend to end up working for big corporations.
https://www.theverge.com/podcast/917029/software-brain-ai-ba...
IMO, as with most domains, AI _tools_ will save a huge amount of time, but it's the human specialist making judgment calls based on real world context.
I argue that of all things, law should be as deterministic as possible.
I've always thought that we (as a country) should maintain one single ordered list of specific crimes and punishments. Every new case that wants to set a punishment must insert it into this ordered list and explain convincingly why it fits into the list at the proposed position.
This would prevent the outrageous differences we see today where someone gets a few days of house arrest for murder and another guy gets a decade of solitary confinment for stealing a pen.
It is (probably) impossible to write down a complete list of rules for how to judge even petty crimes. Someone who steals a loaf of bread because their child is starving should not be punished the same way as someone who steals a loaf of bread because they're a kleptomaniac.
No two situations are identical, and the problems start when you try to come up with a one-size-fits-all approach.
A human with sound judgement (and, arguably, some empathy) should be in control.
Programmers will have jobs for a long time, and our most valuable skill will be figuring out what the heck management wants us to make.
https://www.ubs.com/global/en/our-firm/what-we-do/our-brand/...
You should be able to predict the outcome of a court case if you have all the facts available. That's what fairness means.
If a case reaches court then that means that either the evidence or the law isn't clear enough for the person to simply plead guilty (or the case to be dropped).
That’s a vast, vast overstatement.
“You should be able to predict the outcome of a court case if you have all the facts available. That's what fairness means.”
Too much of a simplification. The role of a jury is to interpret the evidence, every jury is unique. Evidence is not an absolute, there are no “facts”. A judge can include/exclude evidence that would sway a jury one way or the other. Sentencing, even without guidelines, is the least variable part of the criminal justice system in the western world.
https://www.damiencharlotin.com/hallucinations/
Just because GPT can make an argument sound convincing it doesn't mean that the argument is convincing. Or based on objective truth, even.
I used AI to save my last company thousands of dollars, and more importantly weeks of time. When I had to negotiate a contract, I'd just have Claude legal make the redlines against the counterparty for me. Sometimes their lawyer even complimented my "lawyer" on how thorough it was.
Only when a final contract was agreed on did I engage my human lawyer for final review (and usually they didn't find anything of concern).
For standard contracts, AI is pretty good.
It's so counter-intuitive that even seasoned AI researchers get it wrong. It happened to radiologists, it's about to happen to Lawyers too [1].
[1]:https://fortune.com/2026/05/04/godfather-of-ai-geoffrey-hint...
The difference in capital deployed is huge. A common laptop on my desk vs big bucks for a real estate full of medical imaging equipment. If radiology becomes less profitable the industry won't deploy as many imaging machines. Legal doesn't have that moat.
Radiologists don't do this, that's just rad techs. Theres's specifically been an explosion in the need for AI review of real radiology analysis and handling complex situations.
Legal document templates and generating them with given constraints existed before the LLM boom. They are accurate and predictable. Many easy and clear cases are already automated. You get a basic case, you take a template, and if the case has something specific, you add it.
I can see LLMs helping with: some paralegal work, legal searches when humans are there to judge the results, spotting and reporting errors in writing. Small modifications for templates.
The problem with the "AI lawyer" idea is that after things are written down, most of the thinking is already done. The text is the output of a hard-to-automate process involving:
* "Asking questions," being curious, and spotting things visually or by listening.
* figuring out the angle (formulating a case theory),
* identifying what is special in the case (the core anomaly),
* what the client wants (the true client objective). That's almost never what they say unless it's another corporate lawyer. You need to figure out emotional drivers, risk tolerance, and what constitutes a "win."
* what the opponent wants (adversarial motives),
* identifying ambiguities. Society is always shifting, and new ambiguities are created steadily.
A lawyer does all this and writes down their thinking. Lawyers think in writing. The legal profession has a really amazing blogosphere.
Obviously I'm not going to be taking on huge law firms but AI has opened up a whole new vector for me in that I am able to sue people at will without paying for any legal fees and I think that is the most powerful outcome of all.
My days are spent now not asking what mobile apps or SaaS I need to make but who I can apply pressure to. The fact is most companies do not like to go to court as it costs them a lot of money. For me I spent about $1000/month on various LLMs for software mostly but I am amused the amount of sway I can have on companies now.
So far I've gotten free internet after suing my ISP for overcharging me, won injunctions against a neighbor over encroaching fences and trees, and now pursuing legal actions against my ex coworkers and employers in an attempt to garnish their wages.
It truly is incredible how much value one can extract from frontier models and what was out of reach due to exorbitant legal fees AI allows me to do.
My days are spent looking for ways to sue companies, employers, people to the same vigor a security vulnerability researcher would.
Please note that I've had some legal education and that its probably not for everyone and I understand if some are upset my choices.
We understand what we can & can't do with software licences and creative commons because we know "this is MIT" or "that is CC, no commercial, with attribution" and we don't need to delve further.
If we had similar for employment terms - ACME Ltd want to hire me for £x at Y location using the standard "UK employee contract" - it feels like you could sidestep a lot of the need for AI parsing individual documents that are all subtly different.
Lawyers are _already_ using templates, but they're all using bespoke templates and it means that you've got ambiguity by virtue of the fact that the sentence in my contract has never been tested in court.
> They sell the editorial infrastructure built on top: headnote taxonomies that organize millions of opinions into searchable categories, practice guides written by specialists over decades, and treatises that synthesize primary law into usable guidance.
> The Free Law Project’s CourtListener provides free access to millions of federal and state court opinions, oral arguments, and PACER documents.
I think issue of a data-moat is somewhat overstated, or at least it is not argued very well here. If secondary organization and interpretation of open data is their moat, and if it is mostly focused on guiding humans through the complex web of knowledge, then AI should make short-order of that.
But, as usual, the issue of structural and organizational barriers is definitely convincing. Sometimes existing players are too entrenched to change. A new kind of AI-oriented law-firm might need to emerge and show itself to be competitive to either make mainstream firms truly change or push them out of the market.
That's a load-bearing "if", though, given the incohesiveness of legal systems compared to typical Bitter Lesson examples.
The article captures this too, mentioning a couple of examples of startups where presumably this feedback loop is tighter.
https://www.ft.com/content/5ba4690b-8b98-43b3-ba0b-f2ec5591a...
However there are highly (self) regulated industries like lawyering that will try to protect their business model with tooth & nails before yielding to what's good for the population.
The clients simply do not care about the multimillion dollar legal bills, since it is just a rounding error at that scale.
I find it hard to see AI being integrated at that end of the market.
Ach, it's probably a mostly human-generated piece, but any time I see the 'Not [x] but [y]' formulation, I tune out.
What horrendous morals behind this article. Why would anyone advocate for prioritizing economics and technology before ethics, especially in something as important as law?
The "won't someone think of the all the poor people with no access to legal counsel" part sounds a lot worse once you realize they actually mean "won't someone think of the money we're leaving on the table by not getting some revenue from selling cheaper AI slop, uh I mean AI legal representation, to those who can't afford anything else".
That way the billable hours can match, but like the article says, who does this benefit? Ultimately the transfer of time to another task will keep law just as expensive. Perhaps there is room to save time on verification vs creation. Is it worth all the investment though?
I would expect such an article to start there, or at least make some argument that concludes that a computer actually could perform professional legal tasks. Which I don't think they can, just as they can't do philosophy.
Don't overwhelm engineers with hermeneutics
Since law evolves, I wouldn’t be suprised that LLMs would spit out arguments that are out of date.
I do not understand why we do not abandon english common law and find common sense.
The moment to off oneself...
These were enterprise contracts where the other company made the contract. It was basically negotiating specific points of the contract. Claude legal called out a few areas that were disadvantageous to us, and then prepared redlines to send back. The same thing my lawyer was doing for me before I switched to using Claude, except I was waiting a week for each turnaround and paying for a few hours of billable hours every time.
> BTW, just curious about the timing: how could Claude for Legal save you thousands of dollars at your last company if the product came out in February?
Negotiating bespoke enterprise contracts can get expensive, especially when the other party is a huge corporation with a big legal team and a lot of time on their hands. And only the latest product came out in February, there were other products before that.
This isn't how markets work.
If one lawyer starts doing 10x as much work in the same number of hours, then all the customers will move to that lawyer as soon as they find out, and the other lawyers will have to adapt to remain competitive.
Something is forcing them to put in long hours. It's the market.
Just like in IT, in law billed hours by one person have little correlation to hours spent working by that person (or others!). The billing does affect customer/client retention and reputation though.