How many of these cases do we have to have before lawyers realise that they need to check that the things an LLM tells them are actually true?
It's just like the cars driving themselves but you need to be able to jump in if there is a mistake, humans are not going to react as fast as if they were driving, because they aren't going to be engaged, and no one can stay as engaged as they were when they were doing it themselves.
We need to stop pretending we can tell people they "just" need to check things from LLMs for accuracy, it's a process that inevitably leads to people not checking and things slipping through. Pretending it's the people's fault when essentially everyone using it would eventually end up doing that is stupid and won't solve the core problem.
what's the core problem tho? Because if the core problem is "using ai", then it's an inevitable outcome - ai will be used, and there are always incentive to cut costs maximally.
So realistically, the solution is to punish mistakes. We do this for bridges that collapse, for driver mistakes on roads, etc. The "easy" fix is to make punishment harsher for mistakes - whether it's LLM or not, the pedigree of the mistake is irrelevant.
Punishment isn't a problem because it doesn't work. If you create a system that lulls people into a sense of security, no punishment will stop them because they aren't doing it thinking "it's worth the risk", it's that they don't see the risk. There are so many examples of this, it's weird people still think this actually works.
Furthermore, it becomes a liability-washing tool: companies will tell employees they have to take the time to check things, but then not give them the time required to actually check everything, and then blame employees when they do the only thing they can: let stuff slip.
If you want to use LLMs for this kind of thing, you need to create systems around them that make it hard to make the mistakes. As an example (obviously not a complete solution, just one part): if they cite a source, there should be a mandated automatic check that goes to that source, validates it exists, and that the cited text is actually there, not using LLMs. Exact solutions will vary based on the specific use case.
An example from outside LLMs: we told users they should check the URL bar as a solution to phishing. In theory a user could always make sure they were on the right page and stop attacks. In practice people were always going to slip up. The correct solution was automated tooling that validates the URL (e.g: password managers, passkeys).
that's because this particular problem has a solution.
The issue here is that there's no such a tool to automatically validate the output of the LLM - at least, not yet, and i don't see the theoretical way to do it either.
And you're making the punishment as being getting fired from the job - which is true, but the company making the mistake also gets punished (or should be, if regulatory capture hasn't happened...). This results in direct losses for the company and shareholders (in the form of a fine, recalls and/or replacements etc).
Yeah, it's never going to be possible to validate everything automatically, but you may be able to make the tool valuable enough to justify using it if you can make errors easier to spot. In all cases you need to ask if there is actually any gain from using the LLM and checking it, or if doing so well enough actually takes enough time that it loses it's value. My point is that just blaming the user isn't a good solution.
> And you're making the punishment as being getting fired from the job - which is true, but the company making the mistake also gets punished (or should be, if regulatory capture hasn't happened...). This results in direct losses for the company and shareholders (in the form of a fine, recalls and/or replacements etc).
Yes, regulation needs to be strong because companies can accept these things as a cost of doing business and will do so, but people losing their jobs can be life destroying. If companies are going to not give people the time and tools to check this stuff, then the buck should stop with them not the employees that they are forcing to take risks.
And if you can't play by those rules, then maybe you aren't a professional, even if you happened to sneak your way into a job where professionalism is expected.
People will have to choose between being fired for being "too slow", or taking the risk they end up liable. Most people can't afford to just lose their job, and will end up being pressured into taking the risk, then the companies will liability-wash by giving them the responsibility.
You need regulation that ensures companies can't just push the risk onto employees who can be rotated out to take the blame for mistakes.
companies cannot rotate people out to take the blame - the company would have to suffer a fine for there to be a punishment.
1) https://en.wikipedia.org/wiki/Clever_Hans
2) https://archive.org/details/nextgen-issue-26 as an example of how in the 90s we has rapid cycles of a new tech (3d graphics) astounding us with how realistic each new generation was compared to the previous one, and forgetting with each new (game engine) how we'd said the same and felt the same about (graphics) we now regarded as pathetic.
So yes, they do sound "authoritative and confident text it just overrides any skepticism subconsciously", but you shouldn't be amazed, we've always been like this.
LLMs just revealed what a decadent society we have setup for ourselves worldwide.
It’s likely happening to everyone.
It's not just lawyers.
If someone is a lawyer, accountant, doctor, teacher, surgeon, engineer etc, and is regurgitating answers that were pumped out with with GPT-5-extra-low or whatever mediocre throttled model they are using, they should just be fired and de-credentialed. Right now this is easy.
The real problem is ahead: 99.999% of future content that exists will be made using generative AI. For many people using Facebook, Instagram, TikTok, or some other non-sequential, engagement weighted feed, 50%+ of the content they consume today is fake. As that stuff spreads in to modern culture it's going to be an endless battle to keep it out of stuff that should not be publishing fake content (e.g. the New York Times or Wall Street Journal; excluding scientific journals who seem to abandoned validation and basic statistics a long time ago.)
Much of the future value and profit margins might just be in valid data?
Easy? In the US you need house impeachment to fire a judge. In some countries judges are completely immune unless they are sentenced for crimes.
Can they though with 100% accuracy and no hallucinations? Wouldn't you still need to validate that they validated correctly?
https://arstechnica.com/tech-policy/2026/02/randomly-quoting...
> In October, two federal judges in the US were called out for the use of AI tools which led to errors in their rulings. In June 2025, the High Court of England and Wales warned lawyers not to use AI-generated case material after a series of cases cited fictitious or partially made up rulings.