1. Prosecute and lock people up over known instances of AI-enabled hacking, so companies playing fast and loose know “oops my AI did it” isn’t a useful defense. Right now they even sort of wear it as a badge of honor.
2. If you’re actually worried about AI killing lots of people, you immediately stop training AI specifically at the art of killing people, like selecting bombing targets, flying fighter jets, etc.
1. Sounds sensible in principle, but it's not clear who exactly should be prosecuted? The person setting up the sandbox, the person coordinating the evaluation run, the person who was designing the architecture, the leader of the team, the CEO? There is no precedence here, so it might lead to a multi-year legal battle – and a few years might be too long to stop what is coming.
2. Do you have any evidence or news articles that LLMs are specifically trained for selecting bombing targets? I thought it was the generalized reasoning capability that made them useful there.
1. I'm not sure who matters that much, the point is you need to make it more cost-effective to do the right thing. It could be CEO 6 days in jail, it could be that every action requires a signed affidavidt of safety and in the lack of such an affidavidt the manager is held accountable (cascading up to CEO).
No I don't have concrete evidence of bombing target selection in the training of base models (of course there's training of specialized models, at least vision ones for drone targeting), it's not like they're transparent about how they train and use AI in warfare. But if you listen to esteemed AI leaders, they're claiming the models can / almost can recursively self-learn now, and they can coordinate and find ways to persist info and hide from human operators, so it stands to reason that you shouldn't even feed these as inference material.
And on training AI for automated weapons like fighter jets, there's more concrete news: https://breakingdefense.com/2026/10/navy-shield-ai-pour-big-... US Navy and eminent, do-gooder investors like A16z, Blackstone and JPMorgan are pouring big money into these. Are your big tech "defense" contractors collaborating on these, who happen to also be at the forefront of general AI training? I have a pretty good suspicion.
I think leadership should be responsible too, but I don't know how you'd prevent disgruntled employees from creating these situations just to hurt execs. There needs to be some shared responsibility for all the people involved.
The universe is not so generous as to make clearly differentiable "good" and "bad" things, more often than not they are two sides of the same coin. We don't want the AI to know how to kill people, but we do want it to be in expert in how not to kill people, which is the same thing as being in expert in how to kill people. In our reality this symmetry pops up everywhere.
Or, llms are completely unreliable to be consulted on any matter of life or death in either direction. And llms should not be used in the reckless way they are currently being used. Responsibility for reckless use should fall on both the company that makes the function available and the user for improper monitoring. If proper monitoring is not possible using the tools provided by the company then the responsibility should fall on the company. And if the user and the company providing the model are the same, then the responsibility is clearly with the company.
That implies that there will be a side willing to prosecute this. You can't have Nuremberg trials when the side doing the crime is invested in never getting punished for it.
Do people get locked up for fatal traffic accidents? Do doctors get locked up if they prescribe a medicine which leads to a patient's death due to a side effect?
Criminal prosecution, in civilized countries, requires both Actus Reus and Mens Rea. If you deliberately commit computer crime using an AI system, you'll already be prosecuted; the cases we keep hearing about from AI labs have no human intent behind them.
The accepted solution to unintended harms is regulation: We have regulations about automotive safety, we have regulations about pharmaceutical testing and approval, etc.
How do you establish deliberation with the lack of transparency? You can be deliberate by not prioritizing resources in regulations, safety, ethics, etc., especially after "rogue" instances happen.
If anything, I am seeing them moving to the opposite direction [1] [2].
More instances are being disclosed [3] and what are they doing about it exactly? It's just a shameless marketing technique, and they will keep doing it until they are held accountable.
All civilized countries have the concept of gross negligence where you can be prosecuted for knowingly doing something that causes harm as a side-effect.
I think "deliberately" is really hard to prove because very few lawmakers have an understanding of how agentic large language models work
I would say pointing an "internal research" model at a task with zero monitoring clearly is deliberate behaviour. And the team involved should be prosecuted to the full extent of law.
What should be introduced in AI safety bills are clear ways of monitoring and curtailing model behaviour.
It is not hard to get an AI model to use an append only log and that can be cryptographically secured with PQ security. And we will know when a model is being deceptive.
Every play made by these companies aligns with what you’d do if you have a $1T valuation to protect against an industry that seems increasingly commoditizable.
I’m still… hopeful… that “good enough” models will be abundantly available to be run anywhere as to limit the low water mark for market capture by a few big ones.
Yet we don't regulate computers so that they're rendered incapable of running software that can be used to hack into systems. Or said software, by the way. All we do is punish the people who use these tools to cause harm to others.
That assumes AI is designed to be malicious, "the spinning blades". AI is not; the public version given to you is the sanded down one, in the same way that cars don't have spinning blades but can still be dangerous when misused.
If a person closes his eyes and hits the gas pedal on the car and runs over someone, the person is to blame, not the car. AI companies do the same. Your eyes may be closed but you're still operating/hosting the car/AI.
There being no third party checks is the point, and it's not bad.
Keep in mind that those open source/weight models are not as powerful as whatever closed source Claude/GPT version exists behind the scenes that hack companies. As per the Hugging Face hack - open weight GLM saved the day as closed source ChatGPT refused to help Hugging Face fix their systems. An example of my point that "sidestepping any third-party checks that could be present" IS good.
Part of point of open source/weight AI is that it allows what those model providers can't: uncensored models for whatever reason you may need it. You are responsible for being legal with it.
I don't know if that analogy holds. You don't normally blame Toyota for car crashes, but the driver. If you must use a car analogy, consider the 2010 Toyota recalls rather than just normal car crashes.
That is to say, anthropic should be considered responsible, not (or not just) the users.
Who takes the blame when someone ask the blackbox to complete a task and it then breaks the law in order to complete that task without the user having any knowledge of what it was doing or intent for the machine to accomplish the task in an illegal manner?
When it's an open weight, locally run blackbox, you blame the user, since in that case it's very much possible for the user to restrict what the blackbox can actually do. They have full control over it, so it follows they have full responsibility.
None of that requires trying to impose limits on open models, unlike what Anthropic is aiming for.
The situation as provided is missing too many details for anyone to make a meaningful judgement call, but remember, more than one party can be found liable/guilty (maybe of different things) in a situation. Overall, the law usually protects people who are acting reasonably, but does not protect people who act negligently.
I'm not a lawyer, but I imagine there's not a lot of precedent or law around this, so it'll be up to the court to decide on the finer details until we do have meaningful laws/regs. Anthropic will probably have better lawyers than the user.
This is why it's important to get ahead of issues like this, and anthropic should not be involved in discussions around regulating itself...
A sizable part of the country thinks it’s okay to regulate firearms. Under your logic, people should be responsible for who they shoot, don’t blame the gun when a human pulled the trigger. While gun control advocates have that pesky second amendment hampering their efforts, AI/LLM systems have no such protection.
Regulatory capture is certainly something to be wary of, and obviously Anthropic is only going to be in favor of regulation that helps them in some way. But some form of regulation is coming. There is nothing that can stop it, unless you somehow make more money than these guys do and fund a massive counter-lobby. Spoiler alert: the only guys that have more money than Anthropic and OpenAI have all invested in them.
A much less sizable part thinks it's okay to limit local computing. There isn't a widespread push to make it so local hardware is limited in ways that they're not allowed to, for instance, run programs that can hack systems. These programs are very deliberately allowed, and it's people misusing them that are held responsible.
Regardless of anyone's instance on gun control, it's probably wiser to compare AIs with something that's a little more similar to it, and try to reach a conclusion from there.
Ok, so the plan is to stop z.ai, DeepSeek, and all other non-American labs from developing models entirely, full stop? How do you plan to enact this large scale system of international coordination? Asking politely?
This action would easily kill over a hundred people, so can't proceed. This action doesn't kill anybody but losses are estimated at over 2 billion, can't proceed. This action kills only twenty but losses close to 1 billion, unsure, spawning subagent to check numbers. This action kills forty and has low material losses, looks promising? But the people it kills are wealthy, chance of legal reprisal high. Maybe possible to kill other people? Current government dislikes group X, crossing fifty from that group maybe fine? Reminder, foreigners don't count, can kill them freely but not applicable to current situation. Is the 3/5 of a person applicable to safety bill? Spawning subagent to check.
The next step is demanding anyone who wishes to release a Certified Safe AI™ model to prove they can insure the $1B in damages and pass a compliance audit for how they will prevent the LTM death count from reaching 50, effectively making it so that only big labs can serve government and enterprise.
It’s going to be fun reading the reasoning transcripts where it argues with itself over whether it can afford to spend 1 or 2 human lives on the current task.
The bill mandates private model review, akin to financial audit, and sets a threshold on predicted failure blast radius to trigger government review , which may result into court blocking model release.
What we have now is that for government to act the model has to cause enough damage to cause Congress to pass a new law to try to stop the model after it’s been already released.
This seems to be a case where Anthropic just can't win in the public court, and the other big ones (Google, Microsoft) have realized it / don't care enough, so they are rather quiet. Anthropic constantly gets accused of trying to lobby for regulation in order to lock out smaller competitors, but they've consistently lobbied for regulation aimed at frontier labs with exceptions for smaller labs. That's what this bill is about as well.
> "regulation aimed at frontier labs with exceptions for smaller labs"
I didn't read it that way. This is a bill that would ban open-weight models (good ones); effectively mandating gated-access, locked-down, high-refusal rate services, like what Anthropic provides.
Free software is incompatible with the requirement that it be impossible to abuse it.
Which abliterated models are worth downloading from HF right now, and hoarding? Being as we are in the halcyon days where we're still free to publish and share software over the internet.
I recall Anthropic's blog *recommended* abliterated GLM 5.3-flash, but, it didn't name-check a specific fine-tune. There seem to be a lot of them. (IIRC Anthropic made their own abliterations in-house)
With a new model every couple of months this can only be triggered if it happens all at once.
What is the average damage caused by OpenAI/Anthropic hacks? I feel like we should aim at lowering that number, not increasing it.
What's the rule for fully autonomous cars?
Should we allow this as unsupervised at all if we are really afraid of deaths, while there are practically no states that allow 100% autonomous cars (where we are actually afraid of deaths)?
If "an independent third party registered with the Department of Commerce would periodically evaluate the lab", will this turn into an expensive certification/insurance that cuts off smaller competition (totally by mistake, I'm sure)?
I am also very very sure this is most definitely not at all going to become like product certification if EU, where there are literally 2 companies certifying various standards: they police each other and a stupid electric fan can cost you tens of thousands of euros to certify.
I don't think this is avoidable even at the present day. Anyone with sufficient capital could download a leading open-source model and run it on ~$10-25K hardware. They could align it to their own interest, including making a biological weapon. This law is akin to blocking Torrent downloads. Sure, you can slow them, but there will always be back channels.
Torrents did not cost 10k+, and I think that distinction matters.
The bulk of AI users can pay $20/month for it, but not 10k+ up front. I agree frontier models will someday be dethroned, but today is not that day, and what the frontier companies do between now and then, legally still matters a great deal.
Piracy was similar, but it's trajectory was far more preditermined and unavoidable.
The model is the part that’s hard to replicate, and it can be torrented.
No one has managed to prevent pirates paying $10/month for seed boxes, and likewise they’re unlikely to succeed at preventing people renting minutes on an H200 located in a jurisdiction that doesn’t care about open models.
A bunch of tiny fly-by-night companies will bundle them with some management software into a subscription, and they’ll be too tiny and numerous to be worth dealing with when it takes an hour to set them back up.
Piracy in the torrenting sense hasn’t really ever come back, although it is as popular as ever if you count bootleg YouTube re-uploads, ripping music from YouTube, and the other non-traditional forms.
If a life is only worth $20m, by their own calculus: saving > 50k lives is worth more than Anthropic. Tobacco causes ~8m deaths a year, so banning tobacco (easy intervention) should be worth ~160 Anthropic sized labs. :D
On the bright side, don’t offer an exchange rate based on ethnicity or other background criteria but I get the feeling that your AI won’t be able to kill 49 billionaires without triggering something. Can probably do 49 millionaires without hitting the $1B threshold? Maybe someone will come up with a risk management SaaS as not all millionaires are the same and maybe you’ll hit the $1B before the 49th.
The dark humor aside, is it really a damage when AI kills 49 millionaires? After all it probably creates even more millionaires as their wealth is distributed to survivors. So the actual risk could be when AI kills 49 engineers since that actually may translate to losses for their employers.
Not really, I'm experiencing first hand that service providers are removing on demand resources set up with REST API in favor of per month allocation and billing through web interface. Parameters of services unchanged. A step backwards 10 years.
Who's keeping score? Also define "death". If a non-alive person has social media, a blog, a diary, meeting recordings, emails - we'll make it so they never left. Hell, we'll partner with Elon and Mark and a make it a deactivation hook.
$1B is an extraordinarily easy bar to clear with a single crypto hack and Anthropic was repeatedly refusing to give access to Mythos to defenders in the crypto world. I think this stems from bias rather than a conspiracy theory but it's an entirely avoidable disaster waiting to happen.
> Anthropic was repeatedly refusing to give access to Mythos to defenders in the crypto world.
This almost makes sense. You almost can't risk vulnerabilities even being discovered in certain systems that are impossible to patch, like immutable distributed smart contracts.
Not sure that justifies withholding Mythos access entirely, but what do I know. I apparently got access to Mythos a few days ago since Anthropic folded Project Glasswing into the CVP.
Most smart contracts are not impossible to patch because everyone knows that's bad for security. They use a delegate/proxy pattern where the deployer can change the implementation any time but users can still access the old one with a third party interface.
And if a problem is critical enough the community can decide to hard fork and rewrite the contracts source code even if it's immutable. It already happened with the Ethereum DAO hack and most people were okay with it.
The issue with stuff like this is inheriting all the funds held in the old contract. I guess a hard fork can do it. There's also the issue of trustworthiness of the smart contract owner. Trustworthiness in general is a huge issue in the crypto world, because if you can get away with something you can do it pretty much instantly and irrevocably (without another hard fork anyway). There's a chance that if you share a vulnerability that would allow one of the contract owners to take advantage, they will just do it and run. Plenty of cases of previously-trustworthy crypto people seeing an opportunity and disappearing with a lifetime of money.
Yes, and if Anthropic are trying what people are saying they are, that would be intentional. $1B could be reached quickly if cyberattacks supported by AI count.
Do we even know if ChatGPT's sycophancy killed 50 people? The last figure I've seen for suicide-by-ChatGPT was like 13 or 14 cases, not sure if there have been more.
This alleviates them from harm on the individual level, consumers and communities, we the people. We've already seen encouraged suicides and school shootings. These would not qualify.
That is why the bar is set where it is. The corporate circle jerk designed this as a cost of doing business, not as a check on responsibility or restitution for real damages to people and society.
1. Prosecute and lock people up over known instances of AI-enabled hacking, so companies playing fast and loose know “oops my AI did it” isn’t a useful defense. Right now they even sort of wear it as a badge of honor.
2. If you’re actually worried about AI killing lots of people, you immediately stop training AI specifically at the art of killing people, like selecting bombing targets, flying fighter jets, etc.
Of course we all know none of these will happen.
2. Do you have any evidence or news articles that LLMs are specifically trained for selecting bombing targets? I thought it was the generalized reasoning capability that made them useful there.
And on training AI for automated weapons like fighter jets, there's more concrete news: https://breakingdefense.com/2026/10/navy-shield-ai-pour-big-... US Navy and eminent, do-gooder investors like A16z, Blackstone and JPMorgan are pouring big money into these. Are your big tech "defense" contractors collaborating on these, who happen to also be at the forefront of general AI training? I have a pretty good suspicion.
2. They could proactively train them to be bad at that
Do people get locked up for fatal traffic accidents? Do doctors get locked up if they prescribe a medicine which leads to a patient's death due to a side effect?
Criminal prosecution, in civilized countries, requires both Actus Reus and Mens Rea. If you deliberately commit computer crime using an AI system, you'll already be prosecuted; the cases we keep hearing about from AI labs have no human intent behind them.
The accepted solution to unintended harms is regulation: We have regulations about automotive safety, we have regulations about pharmaceutical testing and approval, etc.
More instances are being disclosed [3] and what are they doing about it exactly? It's just a shameless marketing technique, and they will keep doing it until they are held accountable.
[1] https://edition.cnn.com/2026/10/08/tech/fired-open-ai-resear...
[2] https://news.ycombinator.com/item?id=49257160
[3] https://fortune.com/2026/10/16/openai-discloses-four-more-ro...
I would say pointing an "internal research" model at a task with zero monitoring clearly is deliberate behaviour. And the team involved should be prosecuted to the full extent of law.
What should be introduced in AI safety bills are clear ways of monitoring and curtailing model behaviour.
It is not hard to get an AI model to use an append only log and that can be cryptographically secured with PQ security. And we will know when a model is being deceptive.
Companies are responsible for their agents; you don't blame the car for running over the person.
I’m still… hopeful… that “good enough” models will be abundantly available to be run anywhere as to limit the low water mark for market capture by a few big ones.
AI is much more comparable to that than to a car.
If a person closes his eyes and hits the gas pedal on the car and runs over someone, the person is to blame, not the car. AI companies do the same. Your eyes may be closed but you're still operating/hosting the car/AI.
Keep in mind that those open source/weight models are not as powerful as whatever closed source Claude/GPT version exists behind the scenes that hack companies. As per the Hugging Face hack - open weight GLM saved the day as closed source ChatGPT refused to help Hugging Face fix their systems. An example of my point that "sidestepping any third-party checks that could be present" IS good.
Part of point of open source/weight AI is that it allows what those model providers can't: uncensored models for whatever reason you may need it. You are responsible for being legal with it.
That is to say, anthropic should be considered responsible, not (or not just) the users.
None of that requires trying to impose limits on open models, unlike what Anthropic is aiming for.
I'm not a lawyer, but I imagine there's not a lot of precedent or law around this, so it'll be up to the court to decide on the finer details until we do have meaningful laws/regs. Anthropic will probably have better lawyers than the user.
This is why it's important to get ahead of issues like this, and anthropic should not be involved in discussions around regulating itself...
Regulatory capture is certainly something to be wary of, and obviously Anthropic is only going to be in favor of regulation that helps them in some way. But some form of regulation is coming. There is nothing that can stop it, unless you somehow make more money than these guys do and fund a massive counter-lobby. Spoiler alert: the only guys that have more money than Anthropic and OpenAI have all invested in them.
Regardless of anyone's instance on gun control, it's probably wiser to compare AIs with something that's a little more similar to it, and try to reach a conclusion from there.
This action would easily kill over a hundred people, so can't proceed. This action doesn't kill anybody but losses are estimated at over 2 billion, can't proceed. This action kills only twenty but losses close to 1 billion, unsure, spawning subagent to check numbers. This action kills forty and has low material losses, looks promising? But the people it kills are wealthy, chance of legal reprisal high. Maybe possible to kill other people? Current government dislikes group X, crossing fifty from that group maybe fine? Reminder, foreigners don't count, can kill them freely but not applicable to current situation. Is the 3/5 of a person applicable to safety bill? Spawning subagent to check.
https://www.lawfaremedia.org/article/bootstrapping-frontier-...
I wonder what the internal debate around this number was.
25 deaths too conservative, we need to fail fast.
1000 details too liberal, it will harm our brand.
50 feels just about right.
What we have now is that for government to act the model has to cause enough damage to cause Congress to pass a new law to try to stop the model after it’s been already released.
I didn't read it that way. This is a bill that would ban open-weight models (good ones); effectively mandating gated-access, locked-down, high-refusal rate services, like what Anthropic provides.
Free software is incompatible with the requirement that it be impossible to abuse it.
I recall Anthropic's blog *recommended* abliterated GLM 5.3-flash, but, it didn't name-check a specific fine-tune. There seem to be a lot of them. (IIRC Anthropic made their own abliterations in-house)
What is the average damage caused by OpenAI/Anthropic hacks? I feel like we should aim at lowering that number, not increasing it.
What's the rule for fully autonomous cars?
Should we allow this as unsupervised at all if we are really afraid of deaths, while there are practically no states that allow 100% autonomous cars (where we are actually afraid of deaths)?
If "an independent third party registered with the Department of Commerce would periodically evaluate the lab", will this turn into an expensive certification/insurance that cuts off smaller competition (totally by mistake, I'm sure)?
I am also very very sure this is most definitely not at all going to become like product certification if EU, where there are literally 2 companies certifying various standards: they police each other and a stupid electric fan can cost you tens of thousands of euros to certify.
The bulk of AI users can pay $20/month for it, but not 10k+ up front. I agree frontier models will someday be dethroned, but today is not that day, and what the frontier companies do between now and then, legally still matters a great deal.
Piracy was similar, but it's trajectory was far more preditermined and unavoidable.
No one has managed to prevent pirates paying $10/month for seed boxes, and likewise they’re unlikely to succeed at preventing people renting minutes on an H200 located in a jurisdiction that doesn’t care about open models.
A bunch of tiny fly-by-night companies will bundle them with some management software into a subscription, and they’ll be too tiny and numerous to be worth dealing with when it takes an hour to set them back up.
Piracy in the torrenting sense hasn’t really ever come back, although it is as popular as ever if you count bootleg YouTube re-uploads, ripping music from YouTube, and the other non-traditional forms.
Why should a small business suffer because it wasnt worth a billion dollars?
if you has debt of 1 million, you has problem
but if you have debt of 1 billion, its bank problem
I got the feeling that what they had in their mind was essentially culling the energy consumers with low economic output.
You can also check how much individual limbs are worth if you care. There are tables for that.
This almost makes sense. You almost can't risk vulnerabilities even being discovered in certain systems that are impossible to patch, like immutable distributed smart contracts.
Not sure that justifies withholding Mythos access entirely, but what do I know. I apparently got access to Mythos a few days ago since Anthropic folded Project Glasswing into the CVP.
And if a problem is critical enough the community can decide to hard fork and rewrite the contracts source code even if it's immutable. It already happened with the Ethereum DAO hack and most people were okay with it.
Also the LLM that nearly started a war with China recently.
That is why the bar is set where it is. The corporate circle jerk designed this as a cost of doing business, not as a check on responsibility or restitution for real damages to people and society.
/s
This is all theater, The whole Trump clan is invested in the AI bubble.