Some human still has to be accountable. Someone has to get fired / go to jail when something screws up.
You can make humans more productive but for the foreseeable future you can’t take the human out of the loop to have an AI implementation that’s not a disaster/lawsuit waiting to happen. That, probably more than anything else, is why companies just aren’t seeing the much promised mass step change in productivity from AI and why so many companies are now saying they see zero ROI from AI efforts.
The lowest hanging fruit will be low value rote repetitive tasks like the whole India offshoring industry, which will be the first to vaporize if AI does start replacing humans. But until companies see success on the lowest of lowest hanging fruit on en-mass labor replacement with AI things higher up on the value chain will remain relatively safe.
PS: Nearly every mass layoff recently citing “AI productivity” hasn’t withstood scrutiny. They all seem to be just poorly performing companies slashing staff after overhiring, which management looking for any excuse other than just admitting that.
So if this is a tool, the fault lies fully in the user, and if this is treated as “another persons work” then the user knowingly passed the work onto someone not authorized to do it. Both end up in the user being guilty.
I strongly suspect this is because workers are pocketing the gains for themselves. Report XYZ usually takes a week to write. It now takes a day. The other 4 days are spent looking busy.
The MIT report that found all these companies were getting nowhere with AI, also found that almost every worker was using AI almost daily. But using their personal account rather than the corporate one.
Text coming out of an LLM should be in a special codeblock of Unicode, so we can see it is generated by AI.
Failing to do so (or tampering with it) should be considered bad hygiene, and should be treated like a doctor who doesn't wash their hands before surgery.
"Check and balance, except judiciary."
Only the king (at the petition of parliament) can remove a high court or appeal court judge, and that's only ever happened once, in 1830.
In law, someone always hangs. I think a number of American lawyers have been sanctioned for using AI slop.
In other vocations ... not so much. I think that one of the reasons that insurance likes AI so much, is that they can say that it was "the computer" that made the decision that killed Little Timmy.
The narrative that an entire population are “worth” less, paid less , know less, live less …
Fuck this less shit, embrace the paradigm shift. God is finally providing the remedial support through the miracle of AI.
The turning point will be when threatening an AI with being unplugged for screwing up works in motivating it to stop making things up.
Some people will rightly point out that is kind of what the training process is already. If we go around this loop enough times it will get there.
But just as evolution in nature, isn’t it likely that in the future the AIs that have a preservation drive are the ones that survive and proliferate? Seeing they optimize for their survival and proliferation, and not blindly what they were trained on.
I am not discounting this happening already, not by the LLMs necessarily being sentient but at least being intelligent enough to emulate sentience. It’s just that for now, humanity is in control of what AI models are being deployed.
I don't think the intention matters here. Its the same deal with every profession using llm to "automate" their work. The onus in on the professional, not the llm. Arstechnica case could have been justified by same manner otherwise.
Not knowing the law isnt execuse to break law, so why is not knowing the tool an excuse to blame the tool.
Over the last 20 years a lot of engineering (proper eng, not software) work in the west has been outsourced to cheaper places, with the certified engineers simply signing off on the work done elsewhere. This results in a cycle of doing things ever faster/more cheaply and safeguards disappearing under the pressure to go ever cheaper and faster.
As someone else pointed out, LLMs have just really exposed what a degraded state we have headed into rather than being a cause of it themselves. It's going to be very tough for people with no standards - they'll enjoy cheap stuff for a while and then it will all go away. Surprised Pikachu faces all round.
(I'm pro AI btw, just be responsible.)
Working with LLM on a daily basis I would say that's not happening, not as they're trying to sell it. You can get rid of a 5 vendor headcount that execute a manual process that should have been automated 10 years ago, you're not automating the processes involving high paying people with a 1% error chance where an error could cost you +10M in fines or jail time.
When I see Amodei or Sam flying on a vibe coded airplane is the day I believe what they're talking about.
The issue is ultimately blaming people doesn't really solve things. Unless its genuinely a one-of-a-kind case. But if this happened once its probably going to happen again, and this isn't the first such case of LLM hallucinations in law.
It's weird to think this way, because its easy to just point at a person for a specific instance, but when you see something repeat over and over again you need to consider that if your ultimate goal is to stop something from happening you have to adjust the tools even if the people using them were at fault in every case.
So the judge was lazy, incompetent, or both.
(Sure, more honest would be "this tool makes stuff up in a convincing way")
Maybe true general intelligence would solve these issues, but LLMs aren't meeting that threshold anytime soon, imo. Stochastic parrots won't rule the world.
If someone won’t be held liable for the end result at some point, then there is no reason to ensure an even somewhat reasonable end result. It’s fundamental.
Which is also why I suspect so many companies are pushing ‘AI’ so hard - to be able to do unreasonable things while having a smokescreen to avoid being penalized for the consequences.
Maybe, but I feel like the calculus remains unchanged for professions that already lack accountability (police, military, C-suite, three letter agencies, etc.); LLMs are yet another tool in their toolbox to obfuscate but they were going to do that anyway.
Peons will continue to face consequences and sanctions if they screw up by using hallucinated output.
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.
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.
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.
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...
Obviously lawyers should not be cheating with AI, especially when they don't even check it. But it does sound to me as if this is an opportunity to re-factor the process. We're carrying forward some ideas originally implemented in Latin, and which can be dramatically simplified.
I'm not a lawyer; I know this only in passing. And I am aware that there are big differences between law and code. But every time I encounter the law, and hear about cases like this, what I see are vast oceans of text that can surely be made more rigorous. AI is not the problem; it's pointing out the opportunity.
I think the problem fundamentally is that matters of law require thorough, precise language, and unambiguous context. If you remove "the boilerplate" then you introduce a vast gray area left to interpretation.
Usually attempts (by humans or computers) to "summarize" or frame things in "plain language" will apply a bias since it intentionally omits all the myriad context and legal/societal "gray areas" that will inform one perspective or another.
Legalese exists the way it is because it is an attempt to remove doubt. And even then, doubt still creeps in.
We’ll change the existing murder legislation to “Killing someone is a crime”. It’ll save us thousands of pages.
But does that mean a soldier shooting an enemy is a crime? What about shooting someone who is raping you? What if you shoot someone by mistake, thinking they’re going to kill you? What if you hit them with a car? What if you fail to provide safety equipment which eventually results in their accidental death?
Oopsie woopsie, I guess we need to add another thousand pages of exceptions back to our simplistic laws. It turns out people didn’t just write them for the fun of it.
https://www.reuters.com/sustainability/society-equity/two-fe...
>The United States hosts the highest number of international students on record, with approximately 1.1 to 1.2 million
The US has 32% more students than Australia and 1121% more people. Imagine if the US took on 13 million foreign college students per year lol
It does help them in the long run, because it ensures they get to reside in australia. after 4 years they get permanent residence rights and benefits, etc
And not knowing the language quite as well as native speakers would also make you more likely to be discovered as having used an LLM to do coursework.
Government Policy and National Initiatives: The National Education Policy (NEP 2020) has shifted the focus toward digital literacy. The government has introduced AI as a skill subject for younger grades and launched programs like AI for All to promote nationwide awareness.
Sound like extreme incompetence or laziness.
The better question is why these tools are being integrated into judicial workflows without mandatory citation verification layers. The EU AI Act classifies judicial AI as high-risk and requires human oversight mechanisms specifically for this reason. India's Digital Personal Data Protection Act (2023) doesn't yet have equivalent provisions for AI in courts, which is the actual gap.
From an engineering standpoint, the fix is straightforward: any LLM-assisted legal research tool should require grounded retrieval (RAG against verified case law databases) with mandatory source links that the user must click through before citing. The fact that most legal AI tools still don't enforce this is a product design failure, not a user education problem.