The problem with measuring AI productivity is that the people doing the actual job (paralegals, developers, etc.) are doing it for someone else (judges, managers, etc.). More work, or even a speedup does not actually benefit them. So when you give professionals a tool that speeds them up, they increase their slack and/or focus on other, less productive activities rather than work more.
The article captures this too, mentioning a couple of examples of startups where presumably this feedback loop is tighter.
Nilay Patel argues that law is undeterministic (and its application ambiguous) to begin with:
> 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.
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.
You can apply this same argument to everything. Code is deterministic but what is being made is often not because people don't know what they want to make. Society can choose just to make everything boring and deterministic so that computers can do everything.
This isn't really true though. This is how the law used to work, until people did the research and discovered it let to absolutely loads of mad variation in outcomes, with people with similar offences getting totally different sentences based on random luck. Hence most countries not have pretty strict sentencing guidelines, with a bit of space for judgement on top (despite a lot of protesting from judges).
Non-grey-area cases are common, and never reach court.
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).
“most countries now have pretty strict sentencing guidelines”
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.
Counter argument - even stone age Chat GPT 3 was great at making reasonably convincing sounding arguments and newer models are great at aligning those arguments to souces (laws or cases). Chat is IMO better at ambiguous nonsense than objective analysis.
You may want to take a look at the "AI hallucination Cases" database which tracks cases when someone used AI and ended up presenting made-up sources in a legal case.
Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients. They would need far more clients to bill the same hours.
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).
> Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients.
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.
And for a thought experiment - if a lawyer controls the pace of their work, why work at any reasonable speed? They could take the client's money and go picnic or something then put in 20 minutes at the end of the day.
Something is forcing them to put in long hours. It's the market.
> Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients.
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.
These are probably contracts where a lawyer would struggle to add value anyway, or you wouldn’t have hired them in the first place. Seems more likely a Jevon’s paradox example to me than anything.
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.
I think the most likely situation with AI lawyers is simply Jevon's paradox. We'll simply ask for lawyer support in 1000's of more situations where we didn't before.
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].
> Only three entities in the United States have anything approaching complete coverage
> 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.
Precedent in law is like discovery in science. It advances the boundary of human understanding so a probabilistic regurgitator will have trouble applying it without treatise roadmaps.
There may also be a Bitter Lesson element here. Ultimately, if law is like other domains, we may be able to solve legal applications with more compute on the limited freely-available data.
That's a load-bearing "if", though, given the incohesiveness of legal systems compared to typical Bitter Lesson examples.
Courts are already overflowing with years of backlogs. I would argue if everyone had a legal bot to represent their interests against others according to the law, and they could come to an automatic traceable agreement, that would be an overall benefit.
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.
There's just a whole bunch of the wrong people involved. AI will replace a majority of lawyers. It is inevitable. It won't be an LLM alone that does it though.
> As AI becomes capable of producing entire work products, the profession that has spent decades treating “I reviewed it myself” as the standard of care has no framework for what happens when that review becomes economically irrational. The ethical rules assume a human at the center. The technology is moving humans to the periphery.
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".
I suppose one way is that the Lawyers and Legal Assistants use Legal AI as a replacement for standard search. Instead of parsing content and creating new notes, let AI search and create but humans spend the same amount time instead for verifying what was created.
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?
This does not mention either interpretation or hermeneutics. For a computer to function as a lawyer it would have to be able to perform interpretation.
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.
> This does not mention either interpretation or hermeneutics. For a computer to function as a lawyer it would have to be able to perform interpretation.
The good thing is new law usually references old law and explains why it has evolved so I wonder if arranging the law in chronological order will help the LLM follow the thread.
It would seem these structural barriers are increasingly become either more porus or more malleable as AI has brought more OSS legal initiatives to empower both attorneys and regular users. The Law and lawyers are being dragged kicking and screaming into e/acc.
Lawyers, especially appealing to juries, require appealing to humanity. I'm sure the state will force software defense on us but it will fuck our neighbors over.
I do not understand why we do not abandon english common law and find common sense.
The LLMs are not even that good at law. I have a license agreement that I wanted to turn into General Terms and Conditions and they kept failing or rewriting the whole thing from scratch when a competent lawyer would just do a few pinpoint changes
The problem with measuring AI productivity is that the people doing the actual job (paralegals, developers, etc.) are doing it for someone else (judges, managers, etc.). More work, or even a speedup does not actually benefit them. So when you give professionals a tool that speeds them up, they increase their slack and/or focus on other, less productive activities rather than work more.
The article captures this too, mentioning a couple of examples of startups where presumably this feedback loop is tighter.
Nilay Patel argues that law is undeterministic (and its application ambiguous) to begin with:
> 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.
You can apply this same argument to everything. Code is deterministic but what is being made is often not because people don't know what they want to make. Society can choose just to make everything boring and deterministic so that computers can do everything.
I agree that you can apply this same argument to everything. And it's still a correct argument.
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.
This isn't really true though. This is how the law used to work, until people did the research and discovered it let to absolutely loads of mad variation in outcomes, with people with similar offences getting totally different sentences based on random luck. Hence most countries not have pretty strict sentencing guidelines, with a bit of space for judgement on top (despite a lot of protesting from judges).
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.
Non-grey-area cases are common, and never reach court.
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).
“most countries now have pretty strict sentencing guidelines”
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.
Fair, most countries that follow the common law judicial system I should have said.
Counter argument - even stone age Chat GPT 3 was great at making reasonably convincing sounding arguments and newer models are great at aligning those arguments to souces (laws or cases). Chat is IMO better at ambiguous nonsense than objective analysis.
You may want to take a look at the "AI hallucination Cases" database which tracks cases when someone used AI and ended up presenting made-up sources in a legal case.
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.
Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients. They would need far more clients to bill the same hours.
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.
> Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients.
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.
And for a thought experiment - if a lawyer controls the pace of their work, why work at any reasonable speed? They could take the client's money and go picnic or something then put in 20 minutes at the end of the day.
Something is forcing them to put in long hours. It's the market.
> Lawyers bill by the hour. It is not in their interest to speed up what they do, because they only have so many clients.
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.
These are probably contracts where a lawyer would struggle to add value anyway, or you wouldn’t have hired them in the first place. Seems more likely a Jevon’s paradox example to me than anything.
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.
I think the most likely situation with AI lawyers is simply Jevon's paradox. We'll simply ask for lawyer support in 1000's of more situations where we didn't before.
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...
> Only three entities in the United States have anything approaching complete coverage
> 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.
Precedent in law is like discovery in science. It advances the boundary of human understanding so a probabilistic regurgitator will have trouble applying it without treatise roadmaps.
There may also be a Bitter Lesson element here. Ultimately, if law is like other domains, we may be able to solve legal applications with more compute on the limited freely-available data.
That's a load-bearing "if", though, given the incohesiveness of legal systems compared to typical Bitter Lesson examples.
A massive firm in the UK has reported itself to the regulator for using AI not once, but twice in a submission to a court.
https://www.ft.com/content/5ba4690b-8b98-43b3-ba0b-f2ec5591a...
But these figures measure exposure, not integration.
Ach, it's probably a mostly human-generated piece, but any time I see the 'Not [x] but [y]' formulation, I tune out.
Courts are already overflowing with years of backlogs. I would argue if everyone had a legal bot to represent their interests against others according to the law, and they could come to an automatic traceable agreement, that would be an overall benefit.
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.
I know someone who is with a leading firm. He is involved in a new multibillion USD matter every month.
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.
There's just a whole bunch of the wrong people involved. AI will replace a majority of lawyers. It is inevitable. It won't be an LLM alone that does it though.
> As AI becomes capable of producing entire work products, the profession that has spent decades treating “I reviewed it myself” as the standard of care has no framework for what happens when that review becomes economically irrational. The ethical rules assume a human at the center. The technology is moving humans to the periphery.
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".
I suppose one way is that the Lawyers and Legal Assistants use Legal AI as a replacement for standard search. Instead of parsing content and creating new notes, let AI search and create but humans spend the same amount time instead for verifying what was created.
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’m thinking the structural barrier is always going to be AI confabulations and misalignment.
This does not mention either interpretation or hermeneutics. For a computer to function as a lawyer it would have to be able to perform interpretation.
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.
> This does not mention either interpretation or hermeneutics. For a computer to function as a lawyer it would have to be able to perform interpretation.
Don't overwhelm engineers with hermeneutics
AI can't do novel research either right?
I assume also that LLMs are not very good at chronology.
Since law evolves, I wouldn’t be suprised that LLMs would spit out arguments that are out of date.
The good thing is new law usually references old law and explains why it has evolved so I wonder if arranging the law in chronological order will help the LLM follow the thread.
It would seem these structural barriers are increasingly become either more porus or more malleable as AI has brought more OSS legal initiatives to empower both attorneys and regular users. The Law and lawyers are being dragged kicking and screaming into e/acc.
Lawyers, especially appealing to juries, require appealing to humanity. I'm sure the state will force software defense on us but it will fuck our neighbors over.
I do not understand why we do not abandon english common law and find common sense.
> I do not understand why we do not abandon english common law and find common sense.
What's common sense?
AI Lawyers paid by crypto coins with robots as executioners.
The moment to off oneself...
The LLMs are not even that good at law. I have a license agreement that I wanted to turn into General Terms and Conditions and they kept failing or rewriting the whole thing from scratch when a competent lawyer would just do a few pinpoint changes
I found the opposite to be true. Did you use a legal specific plugin?