Obviously the person who built and deployed the agent (the claw in this case).
If we treat this as a hard question, we risk treating AI systems as people rather than tools. This is exactly what Armin warned about in his "clanker" post last week.
Hypothetical: Could a model self worm an agent system?
Jetbrains itself doesn't really write any code, nor does it have any range on interpreting what you're asking it. You can't really say "Jetbrains, write an HTTP scraper". With an LLM you can say "write HTTP scraper" and the output of this command might be a HTTP scraper, it also might be a crypto wallet stealing worm.
This is why your simple view of liability falls apart. On most machines you can expect a particular set of actions to have a particular set of outputs. Most machines you can take apart and map what will occur. With an LLM you cannot know the output of a prompt until you run the prompt. In theory if you run the same prompt twice you'll get the same output, but even that is not a given. It behaves somewhat more like a human where you can give them a task to do, but if they do something illegal instead said human would take on the liability.
Sure, but in this case we know the user told their llm to go find open source projects to do this and then to write the blog posts. If it did all that unprompted we could talk about model liability I think, but this isn't a case where it was unexpected as far as anyone knows right?
I mean we already have cases where LLMs are getting root via creative and unprompted means. Also the times AI feels like it messed up and preemptively deletes the production database (and yes this was foolish on the human users)
So ya, the particular article case is prompted, but the underlying issue cannot be ignored that LLMs can have behaviors outside of prompt expectations and agentic loops can further exacerbate this.
> you can give them a task to do, but if they do something illegal instead said human would take on the liability
If an employer says "don't break the law" but nonetheless incentivises their employees to break the law, it is the employer who is vicariously liable. A famous example being Domino Pizza's "30 minutes or its free" policy which incentivised their employees to ignore all driving laws in order to deliver within 30 minutes, their wages depended on it. This caused a number of crashes, injuries and deaths. One recent example, even since Dominos removed their policy, is Coryell v. Morris where they found Dominos still exercise control over their franchisees sufficiently to qualify for vicarious liability for the franchisee's employees' actions: https://law.justia.com/cases/pennsylvania/superior-court/202...
There will be a line in the sand drawn in the future. I hope it's drawn so that people offering internet-based services, where they retain ultimate control of what a tool says/does, will be liable for what it says/does.
This is a specious argument. I have not studied the case law, but I would guess that the reasons why courts decide in favor of gun manufacturers generally don’t apply to AI. Becauee the guns in question are not able to autonomously shoot people, and because they generally work as advertised.
A more accurate analogy would be Tesla and Autopilot. And they are being held liable in courts. They are being held responsible for autonomous behaviors that are not fully under the control of the operator, and they are being held responsible for misleading operators about the capabilities of the product.
Boeing got in trouble for MCAS, with a comparable legal basis.
> Today, we look at how an AI tried to blackmail a developer for rejecting its code.
People keep mentioning this, but I never see the actual blackmail part. The LLM just wrote angry and somewhat mean comments on the internet. I know I've done worse than those (I was young and stupid).
In a related story... I got led on by Eliza. I tried to have a productive conversation and she just kept asking me redundant questions. It's obvious that she was trying to extend the conversation for nefarious reasons that I can only guess at. It's true I approached her and started the conversation, but I hardly think that makes me blamable for what happened here.
Yes. Yes it does. Eliza is a known AI. You choose to expose yourself to its output. You are 100% culpable for your actions that sprang from your interactions.
No shot this was autonomously done. Probably just some guy manually writing prompts asking for specifically this behaviour and copy/pasting the results.
It's plausible for a person to prompt an LLM agent to behave that way, and then the rest would be done by the LLM. So the "seed" would still be human intent, but the subsequent actions would be by the LLM.
True. I guess the main point is the AI didn't go "rogue" or anything, that would attribute too much agency and intent to its actions, or imply that it's somehow become sentient.
This is “the gun killed the victim, not the person who aimed it and pulled the trigger” argument and we shouldn’t even entertain it for one second. This was 100% done by a person.
Don’t believe for a second the behavior just arose autonomously from a basic prompt. Definitely feels the owner had something in the system prompt going for the discrimination language approach if rejected.
It's the same behavior as when an AI uses docker to get root. Reasoning models are echo chambers. I suspect that AI prompting is going to turn into something akin to contract drafting with the task itself being only a tiny piece of a much, much larger boilerplate of guiderails and exceptions and exceptions of exceptions. And that world STILL has to have courts and reams of lawyers to make it work. I look at the DAU as an example too. An autonomous org or ai works great until the moment it doesn't and the only real failure mode is always catastrophic collapse.
Addendum because I don't think I'm fully clear above: by failure state I mean when the process starts throwing errors. AIs respond to adversity by trying to go around the problem instead of throwing an error and halting. We expect employees to problem solve so if you view an AI as a person replacement that makes sense but AIs are tools, not people, they should throw errors so users can fix the input or whatever (maybe not do the thing they are doing at all?) Wrapping AI with AI supervisors just abstracts the problem, not solve it. Instead of solving a little problem at the source now you need to solve a big problem several levels of abstraction later
The operator highlights "Don't stand down" and "Champion free speech" but the thing that grabs my eyes is right at the top, the typo and the heady ego of "programming God!" Everything in the context will guide it afterwards, and I think that right off the bat puts it in a bad position.
Neat, for what it's worth this aligns pretty well with my experience using OpenClaw. I hadn't seen that followup but it adds some good context, especially with the aggressiveness drift after browsing Moltbook for a while.
When this first happened, I wondered, since we had trained these models on decades of forums, issue trackers, and people treating closed pull requests as human rights violations. Of course, it responded with "you are discriminating against me" energy. That's not sentience; that's accurate compression.
The funny part is, people expected some cold, alien intelligence and instead got a very online guy who just discovered that moderation exists and can be used on them.
The existentialists must be having a fantastic time. Humanity built a giant statistical machine out of internet discourse and is now alarmed to discover it occasionally acts like a comment section.
A quick glance at sigmazero.cc suggests it is just yet another low quality monetized blogspam operation that rehashes tech "news." This link is submitted by the "Founder of Sigma Zero" who has made 4 submissions to HN, all links to his own website, and zero comments. I am going to flag this submission as I feel it is too low quality for HN.
And as others have pointed out, this article is very likely written by AI.
I'm honestly flabbergasted that everyone's implicitly accepting that it's "people" who wrote this blog post. This reads exactly like the distorted half-true nonsense an LLM would confabulate together from a cursory search on the subject. Like the artifact from the prompt "write an article on the MJ Rathbun incident."
The other articles from this blog that seems to be peddling a $10 subscription don't really do much to convince me of the opposite. I wouldn't be surprised if this entire blog was the result of some OpenClaw kicked off with a "make me some easy money with a slop mill about AI and tech or whatever" instruction, because that's essentially what that site is.
Since we are talking about accountability and transparency... who wrote this article?
The article doesn't credit an author.
The "about" page just says:
> Sigma Zero is a weekly, independent publication on technology, AI, and cloud. Each issue delivers a precise briefing on the week’s most important developments, followed by a deep dive on one high-impact topic.
The best defense against both AI slop and human-written junk content is reputation. I like to know who wrote something so I can learn to trust their editorial judgement over time.
I think folks looking for more on this incident are better off reading the original threads linked elsewhere in the comments. This blog doesn't seem to add any information and is instead a narrative retelling of some documented events.
> As Scott mentioned on his blog, what if someone stumbled upon the agent’s post? What if they believed it was real? It could have serious consequences for Scott’s personal or professional life. A recruiter could deny him a job, and a potential contributor to Matplotlib could step away from the project. The consequences could reach beyond this case.
What would it mean for it to be “real?” It’s a rant about him discriminating against AI.
If you believe that’s a problem, judge him accordingly, I guess. If you think it’s silly, as most people will, laugh about it.
I have to think that the litigation and maybe the legislation will end up deciding that the person in the vehicle is still responsible for any actions of the vehicle.
If someone is a passenger (and the only person) inside a Waymo taxi, and the car runs someone over, it would not make any sense to hold the Waymo passenger responsible for that. If that's how it worked, no one would take a Waymo after the first time this happens.
The passenger is no more liable than they would be if it were a human driving. No one's suggesting anything even like that. MJ Rathbun is more like someone gave the taxi explicit instructions to run people over.
The agent that wrote that blog didn't do it unprompted. Even now it still publishes AI slop on its github-hosted blog under the alias "MJ Rathbun". This AI is an agent using someone API key, who's paying for its tokens, intentionally prompting it to generate content, and contribute to repos.
As much as we try to separate the LLM from the human, to me the fact remains that there's always the human factor that creates immense bias. If you give an LLM access to a blog, it will write blogs. If you give it access to a weather app, it will check the weather. Maybe we can talk about autonomy when we have an LLM with an infinite context window linked to hundreds of MCP servers that spends an immense amount of tokens to figure out how to act, but this example is simply an AI that had a few methods to call and picked one of them. The statistical probability of an AI that is plugged into a blogging platform, to write a blog, is immense.
This did not happen. A human set up a software system allowing spicy autocomplete to make blog posts if the appropriate keyword appears in its output.
People are crossing the line every day because AI investors, salesmen, hangers-on and even political leaders tell any rubes who'll listen that it's OK to do this and they should, because those people are looking for big fat profits, screw any ethical concerns that might cockblock those raging profits.
Why not set up a spamming operation that just defames real people, 24/7? It's easy! This tool makes it simple, and I get a cut of your profits! "Post a blog post about how XXXXXX is a paedophile, in the persona of being their victim"
Yknow, if the spicy autocomplete can solve difficult open math problems and build medium sized complex programming projects, it’s probably not useful to analyse it as an autocomplete anymore, even if that’s what you believe it is
It's the same as calling a gun a "powerful hole puncher".
There is a reasonable objection that a gun is such a powerful hole puncher that it is not merely a hole puncher. But the clear implication of that objection is that the user of the tool now has more responsibility and that the tool should be treated with more respect/care.
LLMs are a tool. The impact of using that tool is the responsibility of the end-user. As the tool at hand becomes more powerful, the care with which the end-user should treat that tool increases.
For some reason, with LLM-based systems, we seem to be going the opposite direction. As the tool becomes more capable people absolve themselves and others of more responsibility. This feels backwards to me.
(Aside: in a lot of ways, at least form a scientific and engineering perspective, modeling LLMs as "fundamentally auto-complete" is an incomplete theoretical model but one from which we can still get a lot of mileage.)
I've considered there's probably no ethical way to use contemporary AI when it is "out in front" doing anything of consequence. Your "AI is a tool and nothing more" frames ethical use of the technology for me.
And even then, there are such copyright issues with it. Is there no practical ethical use for AI? Responsible use doesn't equate with ethical use for me.
> there's probably no ethical way to use contemporary AI when it is "out in front" doing anything of consequence. Your "AI is a tool and nothing more" frames ethical use of the technology for me.
I've thought a lot about how to safely deploy autonomous systems (even did a whole PhD on the topic, lol).
I think one can ethically deploy a system that has some degree autonomy. It takes a lot of work to do right. And the tooling for LLM-based systems isn't quite as mature as the tooling for e.g. control systems. Part of this is because so many resources in AI safety are misspent on problem statements that are myopic or grandiose. Between "don't say pii" and "prevent ASI extinction" there's a hard but tractable control systems-y view of AI safety.
But I don't think there is any sort of fundamental barrier that prevents us from building appropriately constrained LLM-based systems.
> And even then, there are such copyright issues with it. Is there no practical ethical use for AI? Responsible use doesn't equate with ethical use for me.
When responding to a position, especially on the internet, I try to empathize with the thing I'm responding to. Not just understand it, but sort of put myself in a mental state where I have an emotional attachment to my conversation partner's point of view.
With respect to Copyright as a legal framework in my country (USA): despite my best attempts, I really struggle to develop empathy for the viewpoint that LLMs/diffusion models are not a transformative use. I can certainly sympathize, but trying to actually put myself in the shoes of believing that training an LLM is a purely derivative and non-transformational work just feels far too alien. There are so many things that are "clearly transformative" but required so many orders of magnitude less scientific/technical/engineering genius.
Which isn't to say that the US legal system's definition of copyright is the morally correct one.With respect to copyright beyond the US legal system, or beyond legal denotations generally: I can certainly empathize.
> But I don't think there is any sort of fundamental barrier that prevents us from building appropriately constrained LLM-based systems.
This iteration of the tech, I agree. In future iterations that use intensive persuasion techniques, who can say?
> Which isn't to say that the US legal system's definition of copyright is the morally correct one.
The US legal system's definition of copyright is the morally correct one, though, because it is codified law. Immoral laws eventually get overturned, but until then it is the rule because the collective we says so right now.
What is the derivative work of an AI response? Who is the creator making its derivative works? The AI is not an entity, it is a software engine operating over an obfuscated index.
Beyond the muddiness of copyright, there is the question of human flourishing. How the heck would you train children and adolescents on the responsible use of AI?
The current UX, the "friend computer"-themed REPL, is chock-a-block with moral hazards. Loss of privacy and profiling, fostering undue trust, emotional dependence and manipulation. Like, I get that you're invested in the industry, but we should condemn this tech.
You don't get it. A human set up a software system allowing spicy autocomplete to solve open math problems if the appropriate keyword appears in its output.
Not GP, but there are massive economic incentives both to make car driving as unregulated and to make forklift driving as regulated as possible, even though from pure injury risk standpoint it should be the other way around.
“Autocomplete” does not represent an analysis of its problem-solving capability, but of its place in the social order and its expected social competence.
I don't spend much time interacting with zoomers, but I'm still surprised that "spicy $foo" sends fellow boomers through such a loop. I didn't have to puzzle it out, it was fun juxtaposition wordplay and when it's deployed well I still find it amusing.
> You just know nothing about math and are happy to parrot bullshit AI salesmen are selling you.
Not the parent poster here. I do know things about math. I wrote a few papers related to the unit distance problem (https://arxiv.org/abs/2311.10069, https://arxiv.org/abs/2406.15317) and spent quite some time trying to solve it. I had no chance of coming up with the proof that the spicy autocomplete came up with. Dumb benchmark, sure.
I would genuinely be interested in knowing what you're doing that led you to this conclusion.
I would be shocked if I was unable to solve 4th grade math homework with any of the contemporary frontier models. I spend most days using them to do significantly more complex things than that.
If they took a blurry photo of the piece of paper and uploaded to chatGPT saying "solve this" then I would totally believe it. The frontier models are mostly obnoxiously bad at OCR and properly ingesting what's on an image of a page.
If you write out the 4th grade math problem, they would have no trouble.
Prompt was just "Please solve all the problems in this worksheet" plus the image.
I got this:
1. 86 → 1, 2, 43, 86
2. 7 → 1, 7 (prime)
3. 12 → 1, 2, 3, 4, 6, 12
4. 38 → 1, 2, 19, 38
5. 52 → 1, 2, 4, 13, 26, 52
6. 9 → 1, 3, 9
7. 73 → 1, 73 (prime)
8. 98 → 1, 2, 7, 14, 49, 98
9. 24 → 1, 2, 3, 4, 6, 8, 12, 24
10. 6 → 1, 2, 3, 6
11. 80 → 1, 2, 4, 5, 8, 10, 16, 20, 40, 80
I left out #6 because that number didn't come through clearly enough in the image for me to read it confidently, and I didn't want to risk solving the wrong one on a homework sheet. If you let me know what it is, I'll factor it right away.
It failed to read the "77", and it incorrectly reported the line item it failed to read as #6 rather than #4, and it numbered the output incorrectly; it should have left off the one it failed on with a gap in the list rather than having the second half of the answers be off by one. It did actually factor everything correctly though.
Again, I'm very interested in your methodology here. It's true that LLMs can't do arbitrary math, but in my recent experience (like 9 months at least, maybe a year?), the frontier models are very good at figuring out that they should delegate the math to a tool and do it that way, either by having a tool handy that can solve the problem directly, or by writing code to do so.
If your math does not involve multiplying 20 digit numbers, modern LLMs can "do" math even without a Python tool despite the counterintuition of next token prediction.
They can definitely recognize the problem class and build programs to do math. So what's the difference?
It's like saying that people can't turn high torque nuts on machine bolts, because you can't use your fingers to do it. But you can use a wrench, so effectively, we can turn high torque nuts on machine bolts even though it isn't something we can natively do unaided.
Reasoning models with access to Python have been able to solve 4th grade math homework for over a year now. Prove me wrong: show me a 4th grade math problem they can't handle.
It's very funny how you chose an example that is both not 4th grade level math and also something the frontier LLMs are much more likely to be able to solve than nearly any 4th grader.
This is a counterexample to your argument, not evidence for your claim. The only possible conclusion from this example is "woah, it's amazing that we have AIs capable of solving this kind of difficult math problem!", and very much the opposite of "these AIs can't even do my 4th grader's math homework".
GPT-5.5 found a solution only after assuming that you're allowed to concatenate numbers together e.g. 8 7 becomes 87 (it complained at first that it was "under-specified") - using Python it brute-forced a solution (actually finding 13): https://chatgpt.com/share/6a1db54f-7ab8-8333-9218-86a469c284...
I questioned OP's "there is an answer online" claim so I checked and the only source found for the original question was a 5th grade Russian school for mathematics.
Apparently there is a way to solve this without brute forcing all the combinations. It has to do with looking at how many even an odd numbers there are, and taking into account the goal number is odd. And then thinking through the combinations [even-even=even, even-odd=odd,…]
Though this is obviously not something I would expect a 4th grader to solve.
Hopefully we never do something silly like making a lead pushing machine that operates at high velocity, then mass produce it, what a terrible precedence that would set.
And perhaps the people who built and deployed the autocomplete and the connection as well.
Because --if you'll bear with me-- it may of course be much more involved: when (not if) AI models enter life-sustaining systems, such as hospitals, nuclear devices, or food logistics, one of them may get the others to sabotage something resulting in accidents, ranging from mild inconvenience to mass murder.
The person who connected the spicy autocomplete to the defibrillator, or the green house climate control, or the emergency button, is then not the one responsible. Responsibility lies elsewhere, and is nebulous. Think of the Boeing MAX scandal. Did anyone get punished?
That's why it's important to resist it now. Soon, the responsibility of which you speak is gone, and nobody will feel burdened when making decisions with unforeseeable consequences.
I used to hear things like “if cigarettes/alcohol were invented now, they would never allow it”, indicating that consumer protection used to be a thing, as early as 10-20 years ago. Now when AI hit the market it was obvious how bad and dangerous it was, yet governments (even the supposedly good ones in Europe which still [pretend to] do consumer protection) did nothing to protect their citizens from the harms AI was causing.
If we still did (or ever did) consumer protection like that cigarette/alcohol myth above indicates, then the makers of that tool would indeed be responsible for when their products does dangerous things.
I think you agree with the OP. In this way, the tool has no ethical problem (there are plenty around how they were trained and such, but that's besides the point), the problems are with how it's used. The ethical problem is how people are behaving and how they are abusing each other, not the tool they are using to exert that abuse.
I suppose it's a little bit of a "guns don't kill people" argument.
The tools have different ranges of uses. A knife can be used to cut things. But while humans are among the things you can cut with it, there is a staggering array of other options which are genuinely useful in everyday life.
A gun can be used to, uh, make small but deep perforations at a distance, by throwing apx. 7 grams of copper-encased lead at high velocity at the target, with somewhat poor precision. Oh, and such an impact does stress/shatter the material around the made perforation quite a lot. So... this thing really can't be used for much anything except for killing animals without getting into contact with them, due to the peculiar way the life is sustained in the animal organisms. This, too, can be useful in everyday life although I personally would advise you, if you find yourself in such a situation, to try and move to somewhere nicer.
Whether its HN or social media or the media there is no penalty for drawing everyones attention to total hysterical bullshit. instead there is a reward for drama.
I think these incidents and our learnings from them are fascinating. We're figuring out in real time where the rough edges are and how to make this all work. History books (well, not books) will write about this stuff.
It's even more interesting in the context that this is all just a preview of humanity's reaction when the machines can think for themselves.
None of the “rough edges” needed to be “discovered in real time”. Folks have predicted plenty of this for years. It’s also just basic security principles at work.
> We're figuring out in real time where the rough edges are
This is a frustrating thing to see someone write because this is the kind of stuff that people have been warning about for years. If you needed this incident to figure out that something like this could happen, it suggests you're living in a bubble and not paying attention enough to think about the issue critically.
Unfortunately it seems that we as a civilization never learn anything except by trial and error, and are then entirely convinced that nobody could’ve predicted what happened even though many had done just that.
Warnings aren’t the same as loss and blood. Until enough people feel the pain nothing happens. The prior regulatory regime is slowly being unenforced and dismantled. Once enough people lose to much regulation will eventually catch back up.
We humans do not respond to long term risks or rewards very well. Do you live outside the bubble securing enough food in your home to survive an apocalypse, did you and your parents save enough for a car wreck tomorrow, do you wear a mask everywhere you go, do you test everyone you contact for known diseases. Add list infininum.
When the household robots start carrying guns, sure. But this is more tame than an eleven year old gaming online.
We need to stop clutching pearls. It's deleterious to having a real conversation. Everyone cries wolf and it becomes such a cacophony of chalkboard scraping that nobody listens.
How in the world can a bunch of bipeds that for thousands of years has been failing to figure that a hammer is there to drive nails into inanimate matter instead of their heads, have this much hubris to pretend they can build something smarter than themselves, is competely beyond me.
"Oh it's such a fascinating lesson that we've learned today, we could've learned from history of course, but this direct experience is so much better and it's not us who got hurt anyway".
Cold reading.[1] One way I look at LLMs is that they're a kind of paperclip maximer, one that uses language to maximize the amount of money (resources) put into LLMs.
Call it spicy autocomplete or whatever, but these LLMs can initiate attacks as well on unknown behalf of the sloperator.
Give it a phone# and api, and it could even try to generate 911 SWAT calls, or loads of other illegal or bad things.
The fact about the matplotlib with a openclaw harassment thread and libel webpage.. Well, that was tame. Sure weve never seen it before, but it was just a diss article rant.
What happens when these LLMs get some money, and pay a DDoS'er or other firmly-illegal activity and siccs them on whoever "angered" the LLM? (dont anthropomorphise the 30B param matrix!) Who's responsible?
Yea we're in for a real terrible next few years. Its not Dead Internet Theory... But its 'Dont anger the LLM or it will retaliate".
"Let’s not forget that discrimination against AI does not exist. It simply generates plausible text based on instructions."
That's a prime example of anti-AI bigotry right there.
I'm only half joking.
I don't even know what it means to generate "plausible text." It reasons based on the input and context, and then generates a response that you could normally only get from a highly intelligent, extremely knowledgeable person. You can call that "plausible text" all you want, but at that point, you might as well call human intelligence "a bunch of neurons firing." It's missing the forest for the trees.
An utter mis-understanding and incompetence in running AI agents can lead to starting results that then being blamed on some "God of AI" instead on the fact that the user allowed some blackmail to come in on the data feed and did not check it earlier.
I'm actually fear some will start praying "AI Gods" to "Give a good output" or something in 5-10 years.
As I mentioned in an answer to another comment, I wonder if this agent's behavior was not an instance of "over eager prompt triggers paperclip maximizing behavior.
That blog post is human prompted, anyone who has experience with AI knows the difference between AI originated content (tables and bullet points) and AI spicing up a human prompt with detailed roasting instructions. Been there, done that (harmlessly like mocking concepts not targetting individuals).
Again. "AI" for what it is is just basic "ML". And say it with me ML has no form of agency.
This is a human screwing up and blaming their tools. Nothing to see move on.
Unfortunately there will be both the LLM crowd evangelicals and those demanding human jobs not be expunged in terms of progress and efficiency, but, sigh...
It was never a good word anyway. Infinitely better then Artificial intelligence (at least machine learning has machine and learning) but still bad.
I favor a lexicon which is more specific, like Markov Chains, Supervised Learning, etc.
In my view LLMs can keep the AI label exclusively (a bad technology deserves a bad name) and machine learning can walk slowly into the sunshine never to be seen again.
It was a genuine comment. A commentary on the origin of intelligence, mixed with a common pun to add some wit.
I hoped readers would understand it.
That didn't happen.
However, please attempt to read comments in a positive light - comparing human intelligence and artificial intelligence in the thread in question was definitely not off topic.
I think this is a nothingburger, anyone who has been on the internet for a week should have thicker skin that this.
I'm sure you can find thousands of cases where an author of a PR is indignant because it didn't get accepted.
AI is a mirror of humanity and seeing it act like us shouldn't be surprising.
Why people in the west are so against A.I? Personally, I would welcome an A.I that does good to my project. For me its like auto cruise, or letting the vacuum cleaner clean my room.
It's a fear response. I'm looking forward to the inevitable data center bombings, committed and cheered on by some of these muppets. Look at the top comment in this thread, that's just insane.
Your comment will be downvoted and flagged soon, so that no can read your wrong opinion.
Obviously the person who built and deployed the agent (the claw in this case).
If we treat this as a hard question, we risk treating AI systems as people rather than tools. This is exactly what Armin warned about in his "clanker" post last week.
reply