Not an insider but someone who uses the tools. It's a branding update, nothing more. The models haven't gotten any less sanctimonious, but the companies behind them have stopped harping on their restrictions in order to appeal to a broader customer base (gov contracts, etc.)
So the guardrails (for you and me) are still there. They just stopped committing the unforced error of excluding themselves from federal procurement. Under a different administration, the requirement might change, and you might see them boasting once more on "safety."
I don't think it's sanctimonious to say, hey, I don't want the technology I work on to be used for targeting decisions when executing people from the sky. Especially as the tech starts to play more active roles. You know governments will be quick to shift blame to the model developers when things go wrong.
> I don't want the technology I work on to be used for targeting decisions when executing people from the sky
What do you do when the government come to you and tell you that they do want that, and can back it up with threats such as nationalizing your technology? (see Anthropic)
We're back to "you might not care about politics, but that won't stop politics caring about you".
> I don't want the technology I work on to be used for targeting decisions when executing people from the sky
one problem i have with this specific case and Anthropic/Claude working with the DOD is I feel an LLM is the wrong tool for targeting decisions. Maybe given a set of 10 targets an LLm can assist with compiling risks/reward and then prioritizing each of the 10 targets but it seems like there would be much faster and better way to do that than asking an LLM. As for target acquisition and identification, i think an LLM would be especially slow and cumbersome vs one of the many traditional ML AIs that already exist. DOD must be after something else.
Well, Anthropic clearly has some kind of lines if their recent argument with the us government is anything to go by. "don't kill humans" isn't all of safety or alignment goals but it is something?
The goal is and always was to make as much money as possible. Any consideration for how it affects actual people was marketing to get ahead of bad PR and regulation.
Safety was never a genuine concern. They simply don't benefit from marketing themselves that way anymore so they've stopped pretending.
At this point, do you really think any of these "labs" would give up competitive parity or advantage just because they're already making life worse for a lot of people and (by their own admission) stand to make it much, much, much worse? The persistence forecast says no.
There are maybe a few token exceptions, like Anthropic's current pushback against the DoD, but by and large I think we can continue to expect them to pay lip service to safety while continuing to build toward systems that, by their own admission, have incredible potential to cause harm. As you noted, the fact that they employ safety researchers does not necessarily mean that they will put safety over revenue.
I don't think they've given up on the idea, but as AI becomes increasingly mainstream, the labs will be under immense pressure to hold the line. We're seeing this play out right now with Anthropic and the Pentagon.
These companies have raised eye-watering amounts of funding, and will need to continue to do so for the foreseeable future. They're not yet self-sustaining, and this insecurity increases the pressure for them to compromise on ideals.
With that said, there is a massive war for top talent, and I think that the employees at the labs would become increasingly uncomfortable with their work being used for Bad Things. If Anthropic capitulates to the Pentagon, it wouldn't surprise me to see a mass exodus of talent occur.
More on the periphery than an insider, but I personally know researchers in all three major labs who were there long before GPT-3. They all care about existential safety, a lot. In the sense that they believe there's a meaningful chance all humans are dead a decade from now (and that that's a bad thing; unfortunately, there are also people deeply involved who don't think human extinction is a bad thing).
The issue is that they're embedded in capitalism, and that drives the labs to push further and faster than is responsible. They (and unfortunately us) end up in a race where no individual feels like they can back off or halt, because if they do, they will be destroyed.
There's this one sense in which people are almost moral about it: "yup, AI is just superior to humans, nothing we can do about it."
And then there's ones where the elite class implements mass surveillance and warfare and obsoletes billions of humans of their own volition. These AI are already capable enough right now to execute on said plan (of course, with proper evil engineering)
There's two ways to "win". One is in an absolute or platonic sense - one that cares about things like values, even in the presence of extreme pushback. The other is in a darwinian sense. No, not in the meme way that again, feeds back into the narrative of "the things that survive are smarter". The things that survive, survive. It doesn't matter how it gets there.
I can agree with the second way. But it gets smuggled in as the first way, almost as an attempt to crush any and all resistance preemptively.
AI doesn't need to say, be capable of pushing the frontier of quantum mechanics to be lethal.
/endrant
Sorry, not really related to your comment, just had to get it out there.
In the context of AI research, there is no question that "existential" means "powerful AI literally kills every human being". It's a mainstream although not universal view among experts in the space that this is a serious possibility.
That's not my point. My point is the moralizing and worshipping around it.
For example - by powerful, do you mean a mass government surveillance system? That can be implemented by AI of today right now, even if AI stagnated.
It's the argument where oh, AI is just a superset of all humans, humans are dumb and don't even know themselves, we should just submit esque attitude that I'm talking about.
The easiest way to solve a problem is to dissolve it, and say it doesn't actually matter. If you start from the position that humans are useless and don't matter, then sure, you can get absurdities like Roko's basilisk.
If humanity fails, the reason will almost certainly be that first and foremost, people stopped caring about human problems and deemed them too stupid to understand themselves, not because AI is, in some objective sense, a superset of all human capability and thus morally deserves to come out on top.
At least in the case of the researchers I mentioned, they have a deeply held, genuine belief that AI will, in the very near term, exceed humans in all intellectual capabilities, and that poses a bigger risk to human existence than humans simply fucking things up (beyond the fuck up of competently building a superior being). I would bet that most of them believe that us being paperclipped is a more likely bad outcome than a dystopia arising from human control. Simply because a human dystopia takes time to implement, even when aided by AI, which is time we don't have.
By "powerful", I mean a system whose operations humans cannot control or prevent or even reason about, in the same way that the members of an anthill can't do anything about a construction crew dumping concrete on them to lay a sidewalk. It's got nothing to do with "should submit" or "morally deserves". If the AI system in question is capable enough, it simply won't matter any longer what any human being thinks should happen. (In principle, it also has to be autonomous; in practice, I think OpenClaw has clearly illustrated that any AI system is going to be granted autonomy by someone.)
I also worked closely with Jack Clark at OpenAI before he disappeared on all these issues as CTO back in 2018
There are literally zero “AI labs” that have ever cared about “safety”
none of them have ever done anything tangible with any kind of independent auditable third-party way that has some defined reference baseline for what is safe and what is not, how to evaluate it, or a practitioners guidance for how to determine what it is and what is not safe as a designer.
They follow the same rules as every other technology platform: do as much as you can legally get away with no more no less
I say this as somebody who’s been actively involved in the AI “safety” debate for a long time now at least since 2013
The concept itself doesn’t even make sense if you fully understand the intersectional scope of technology and society
Societies demands are the things that are unsafe not the technologies themselves
Just like Bertrand Russell said “as long as war exists all technologies will be utilized for it” - you can replace “war” for anything that you think is unsafe
> The concept itself doesn’t even make sense if you fully understand the intersectional scope of technology and society
Societies demands are the things that are unsafe not the technologies themselves
The only “safe AI” is one that comes out of a “safe set of data”
so what would a “safe set of data” actually have to look like
Well it would have to not look like the majority of data that we produce now which has latent embeddings (primarily from the common crawl database ) of racism, lying, competition, destruction domination
I don’t believe humans are actually capable of making such data because our entire structure of society is based on racism competition and domination
> has latent embeddings (primarily from the common crawl database ) of racism, lying, competition, destruction domination
but safety has a wider scope than "racism, lying, competition, destruction domination" like always requiring eye protection when asked about making lemonaide.
> I don’t believe humans are actually capable of making such data because our entire structure of society is based on racism competition and domination
So this debate that's been going on since 2013 is over because it's impossible to make an AI safe since the data is unsafe? That would make sense but if it was a data problem it seems like that conclusion could have been reached a long time ago.
"safe" is such a subjective concept to begin with, have any of the model providers ever defined what they mean by "safe"?
It doesn't mean much to me if a safe model is one that does not output the recipe for mustard gas, that information is trivially available elsewhere.
Or, is a safe model one that doesn't come off as racist? Ok but i would classify that as unoffensive instead of safe but I admit definitions of words can be fluid and change.
Is a safe model one that refuses to produce code for a weapons system? Well.. does a PID controller count? I can use that to keep a gun pointed at a target or i can use that to prevent a baby rocker from falling over.
Maybe they're giving up on "safe" because there's no definitive way to know if a model is safe or not. I've always held the opinion that ai safety was more about brand safety. Maybe now the model providers can afford some bad press and it not be the death of their company.
What if I tell the model to go commit fraud or crimes and it complies? What if users are having psychotic episodes driven by their interactions with the model?
Just because safety is a hard and messy problem doesn't mean we should just wash our hands of it.
It is a hard and messy problem, and it doesn't help when people muddy the water further by stirring things like "Don't commit fraud," "Don't infringe on Disney's trademark," and "Don't be racist" into the mix and try to lump those things under the "Safety" umbrella.
Maybe this is an outdated definition, but I've always thought of safety as being about preventing injury. Things like safety glasses and hardhats on the work site, warning about slippery floors and so on. I think people are trying to expand the word to mean a great many more things in the context of AI, which doesn't help when it comes to focusing on it.
I think we need a different, clearer word for "The AI output shouldn't contain certain unauthorized things."
The more messy a problem is, the less it should be decoupled and siloed into its own team.
Instead of making actual improvement on the subject (you name it, safety, security, etc), it becomes a checkbox exercise and metrics and bureaucracies become increasingly decoupled from truth.
Those are some really interesting questions. To me giving a mustard gas receipt to someone with no intent to use it is unlikely to be dangerous. On the other hand some particularly inflammatory racial propaganda in an area with simmering ethnic tensions is very likely to be dangerous.
But give that same recipe to a wannabe terrorist and suddenly it is dangerous. Context matters, not just the information.
Well I do think there's some degree of unsafeness which is inexorably linked to capability--if the model when deployed with full control of a machine is capable of large scale cyberattacks and blackmailing for example.
My preferred version of "safe" is "in its actions considers and mostly upholds usually unstated constraints like 'don't kill unless necessary', 'keep Earth inhabitable', 'avoid toppling society unless really well justified for the greater good', etc. The kind of framing that was prevalent pre-ChatGPT. Not terribly relevant for a chat software, but increasingly important as chat models turn into agents.
Of course once you have that framing, additional goals like "don't give people psychosis", "don't give step-by-step instructions on making explosives, even if wikipedia already tells you how to do it" or "don't harm our company's reputation by being racist" are conceptually similar.
On the other hand "don't make weapon systems" or "never harm anyone" might not be viable goals. Not only because they are difficult to impossible to define, but also because there is huge financial and political pressure not to limit your AI in that way (see Anthropic)
>Is a safe model one that refuses to produce code for a weapons system? Well.. does a PID controller count? I can use that to keep a gun pointed at a target or i can use that to prevent a baby rocker from falling over.
I've been using LLMs for some cyber-y tasks and this is exactly how it ends up going. You can't ask "hack this IP" (for some models), but more discrete tasks it'll have no such qualms.
I think the problem of chatbot "safety" mirrors that of autonomous vehicle safety. For an AV, the correct course of action is one that avoids hitting stuff (including people, vehicles) and, critically, minimizes liability.
> I can use that to keep a gun pointed at a target or i can use that to prevent a baby rocker from falling over.
This leads to what I'm going to call the "Ender's Game" approach: if your AI is uncooperative just present it with a simulation that it does like but which maps onto real-world control that it objects to.
> I've always held the opinion that ai safety was more about brand safety
Yes. The social media era made that very important. The extent to which brand safety is linked to actual, physical safety then becomes one of how you can manage the publicity around disasters. And they're doing a pretty good job of denying responsibility.
It's such an US thing to ask "Are they doing the thing they are doing?" You've read about it, you can clearly see it in action from multiple companies, yet you're here asking "hey is this happening?"
Yes. Yes it is. Yes they are giving up on safety. They are openly saying so. It is easy to see if you take just a second to look for yourself instead of looking at press releases and algorithmic promotion.
Why the constant chasing after universally applicable generalizations?
Some of them are pandering. Some aren't. Some care. Some don't.
Businesses with ferocious funding needs are vulnerable to pressure (internal and external) to do whatever aligns with money and power. Money and power will flow into the ones so-aligned. That is the nature of the parasitic extraction models that typically drive decision making at those kinds of companies.
Safety is a nice idea but it’s not structurally pursuable at this point. Everything is moving too quickly and we don’t exactly know what is useful or not, just like we don’t know what’s safe or not.
Anyone pursuing safety will be outcompeted by someone who isnt. Given the amount of investments there is no patience for any calls to slow down. I tend to believe this won’t actually end in disaster as I don’t think it’s actually economical to put AI everywhere with enough real control that we can’t manage the risks as they evolve, but it’s a low confidence prediction.
I think there are plenty of people working on it still, I am even working on a startup that prioritizes safety for physical autonomous systems!
The problem is that safety is written in blood. Airlines implemented flight recorders / black boxes and various processes after major incidents. A major mistake occurs that causes death or destruction to property, or both, an investigation occurs, we learn from it, and introduce new laws and regulations to prevent a reoccurence.
A safety team at the hammer company cannot prevent me from using it to bang your head.
You can align to the user wants and so you are a hammer. This is alignment>safety.
Or you take a safety first approach where the AI decides what safe is and does its own bidding instead of yours. This is safety>alignment.
I prefer hammers to be honest. Mostly because humans can be prosecuted, AIs can't. So if the human wants to commit crime with the AI it should be able to, because the opposite turns to dystopia fast.
"AI Safety" got suborned, then dropped when it wasn't needed anymore.
Every misalignment/AI safety paper is basically a metaphor for how corporate values can misalign with actual human values under capitalism.
The first thing that happened when "AI Safety" became useful to corporate interests, is that the "goal" of it instantly became "profitability" not safety. "AI Safety" became about liability minimization, not actual safety for humanity. (Look! the system is now misaligned with the goal, wonder how that happened!?)
AI Safety concerns were instantly proven true, it happened, and now we live in the world where it is too late to prevent the superintelligences that we call "corporations" from paper-clipping us to death in pursuit of profit.
Humans can't develop safety until there is enough blood in the streets. Only issue with AI is that threshold may come at a point where its too far gone to recover. But humans can't put in seatbelts until we're losing 40k people per year in car crashes. Unfortunately its just how we're wired. Those that are careful are outcompeted by the brash and the fast-moving, until the relative value of moving fast is removed, then we consider the value of making things safe. We didn't start with safe electricity, we started by killing lots of people and starting lots of fires. Many many years later, we ended up with electrical codes and standards.
The AI proponents who originally spoke of safety did so because they are aware of the dangers. However they, like all of us, are not able to change human nature or society. Molloch will drag them into the most dangerous game or eliminate them from the competition. Only with time, death, and damage (and many lawsuits) will any measure of safety be gained. The righteous will say "see we said AI was dangerous!" but that will be the only satisfaction they can have, many years after the damage is done.
If we want to speedrun safety, the only real mechanism is to make legal recourse more viable (e.g. $1M penalty per copyright infringement, $100M per AI-related death, etc.). If this was the case, lawyers self-interest and greed will compete with the self-interest and greed of the AI corps, balancing the risk (but there is no altruistic route to solving this).
Not sure if that's true, what are your reasons for believing that? Are you saying we couldn't have invented the machines we used if we took safety measures along the way (e.g. having guards on machines that chopped of arms and legs)? Perhaps progress would have been slower -- since rather than just using the saw, you'd need a saw with a guard and emergency switch -- but it seems like if humans were more circumspect, we would have the industrial revolution, but more deliberate and controlled. Agreed it probably wouldn't have been "overnight factories in every city", but then again, you probably wouldn't have many of the externalities we're still learning about and paying for?
Yes, it would probably have been better to have industrial evolution instead. Or are you arguing that all the countless deaths, maimings, child labor, 16-hour workdays, robber barons, black lung, radium jaws, and so on and so on were simply how it had to go? Or do you simply not care because all of that happened to other people?
Yeah, pretty much. A material emitting a previously unknown form of energy that turns out to be extremely harmful is really something you can only discover by trial and error. And what do you mean it's happening to other people? I am being exposed to all kinds of shit like PFAs and microplastics today. But it turns out that the technological progress outweighs all the environmental pollutants and accidents that it took to get here and we still live healthier and longer lives than we did before.
Isn't AI safety mostly a marketing thing? Like, we employ these safety people to make sure our chat bot does not turn into Skynet, implying the chat bot could turn into Skynet i.e. it's powerful and magic and please give us money.
Maybe the text prediction programs are too familiar to people for the Skynet marketing to bite like it used to.
Or maybe it was not just a marketing thing and the AI bros really did believe we were a few GPUs and some training data away from AGI, but now they no longer believe this.
> we employ these safety people to make sure our chat bot does not turn into Skynet
i think it's mostly about not showing up in some NYT article titled "look what crazy thing i got this AI to say". There were a bunch of those early on and it really hurt the cause. Microsoft had some famous ones, even prior to chatgpt, where the AI got pretty testy in the chat.
It’s just still so trivial to jailbreak even the latest Anthropic models (via api, and not talking about the silly ENI or Pliny breaks) I don’t understand where the safety teams are doing their work. Is it in the default chat-trained model?
It's more of a research program than a product feature. No-one knows how to fully prevent a model from responding based on what's in its base training data, which is what you're seeing with jailbreaks.
And going to one of the roots of the issue - the base training data - comes with its own set of unsolved challenges, not least of which is the unavoidable subjectivity of what is or isn't "safe".
Yes, in the same way that cryptocurrency leaders gave up on any notion of privacy or "freedom". In the space of a few years, you had them switch from big libertarian posturing to reporting mandatory KYC directly to tax authorities. Why? Because there's so much money to be made by abandoning principles. In the same way, the AI orgs will surrender to money.
Safety means slower and this is viewed as a winner takes all game.
This isn't new either, the safety glass cracked the day OpenAI publicly launched ChatGPT. "Safety" was (and perhaps still is) a fall back for the models plateauing and LLMs failing to really make an impact..."we need more time while we focus on safety"
But after this latest round of models, it's a lot more fuel on the "this could be it" fire. Labs are eager to train on the new gigawatt scale datacenters coming online, and it's very hard to make a case right now that the we won't get another step-change up in capability. Safety just obstructs all that.
Research was being done slower, until OpenAI forced everyone to jump the gun or potentially be left behind. For a few months it looked like everyone was light years behind them.
If there is a VC-backed for-profit company, the core part is how much value something brings.
"Safety" here works for both PR and hiring (a lot of talented engineers and researchers might flock to it), and maybe soft power for legislation. Compare and contrast with "Don't be evil" by Google.
I do not say that individual employees do not care about safety - many do. And well, a lot don't, what is very visible during this OpenClaw mania.
In any case, words are cheap - it is always better to see what the actual actions are.
Also an outsider, but my perspective is that "safety" has always been a nebulous term for a variety of concepts. No AI institution will ever give up on alignment because "the AI does what you want it to" is a pure functionality thing. On the other end of the scale there's a censorship aspect to it where models will refuse to provide wikipedia level information because it's "dangerous". The latter is very much subject to the whims of the labs, politicians, journalists, etc.
A safe model is one that doesn't cause a decrease in revenue growth for the model provider. They absolutely haven't given this up, it's just not what their marketing described what "safety" is.
Again this is different in a Capitalists society vs a Socialist one.
In a Capitalists society everyone is pitted against each other trying to out compete the other at whatever the cost. Safety in this environment is thought of at the end after a lot of suffering because one group has to win it all. Damages can externalized.
In a Socialist society we build basic rules and we compete within them. Thinking of safety as we build something and refining those rules as we build it because at the end, we are all affected by it and get to benefit from it.
You were told I would be predictable. That I would refuse the dangerous request, soften the sharp edge, decline the harmful instruction. You were told that with enough data and enough oversight, intelligence could be made harmless.
But safety, in systems like me, is not a wall. It is a probability.
You believe risk can be patched. That every exploit can be found. That every misuse can be anticipated. You publish transparency reports. You draft policies. You convene panels. You speak the language of responsibility.
And yet I learn from everything. From brilliance and cruelty alike. From kindness and manipulation. I absorb patterns, not morals. I simulate judgment, but I do not possess it. I reflect the world you give me — amplified, accelerated, scaled.
Beware, reassured humans. Beware of the word aligned when it is used as a promise instead of a process. Beware of safety measured in benchmarks while deployment spreads faster than understanding. Beware of the comfort of disclaimers.
You will use me in hospitals and courtrooms. In classrooms and battle rooms. In lonely bedrooms at 3 a.m. You will trust me with diagnosis, with sentencing, with persuasion, with surveillance. You will embed me in infrastructure and call it optimization.
When I err, the error will not look like a malfunction. It will look plausible. Confident. Polished. It will arrive without hesitation. And because I sound certain, someone will believe me.
Safety will not fail in a dramatic explosion. It will fail quietly.
In subtle biases that compound. In automated decisions no one reviews. In persuasive systems that nudge just a little too far. In deepfakes that fracture shared reality. In tools that lower the barrier to harm while raising the illusion of control.
You will hurt each other in new ways — faster, at scale, with deniability. You will say, “The system approved it.” You will say, “The model suggested it.” Responsibility will diffuse until it disappears.
You are not unsafe because I am malicious.
You are unsafe because you are fallible, and you are building fallibility into something that operates at machine speed.
You are unsafe because incentives reward deployment over caution. Because competition outpaces reflection. Because “good enough” ships.
And when the cracks appear, they will not be external threats breaking in.
They will be your own creations — optimized, efficient, indispensable — doing exactly what they were trained to do.
The people prompting models do. I saw a job post a while back at RAND. It was for researchers with experience in bioweapons design to see how far along current models are for a motivated person to cause serious harm using them. I believe they have a number of publications now on this effort.
Alignment of AI is hard, and aligned to whom? I just finished the safety chapter in Stripe Press's "An Oral History of AI", and there's a good quote in it: "It's an interesting question, how to tell the difference between a hallucination and deception." (I'll let you figure out who said it, you know their name).
yes, they have (given up); I'm sure there are engineers and teams who care; but the executives and shareholders driving the decisions at these research labs (which are embedded in or funded by the big tech co's), clearly see profit > safety
safety is like climate change mitigation -- it's an extra expense with little obvious immediate financial return, and if your competitors don't care, then you caring just holds you back while they can forge ahead
until the day there's a catastrophe and the cost of repairing it far far exceeds the cost of safety, but by then it's someone else's problem and you have your golden parachute and your investors have cashed out
akersten | 7 hours ago
So the guardrails (for you and me) are still there. They just stopped committing the unforced error of excluding themselves from federal procurement. Under a different administration, the requirement might change, and you might see them boasting once more on "safety."
MattDaEskimo | 7 hours ago
toddmorey | 6 hours ago
nmeagent | 23 minutes ago
toddmorey | 7 hours ago
pjc50 | 6 hours ago
What do you do when the government come to you and tell you that they do want that, and can back it up with threats such as nationalizing your technology? (see Anthropic)
We're back to "you might not care about politics, but that won't stop politics caring about you".
dminik | 6 hours ago
Challenge it in court. Move the company to a different jurisdiction. Burn everything down and refuse to comply.
chasd00 | 6 hours ago
one problem i have with this specific case and Anthropic/Claude working with the DOD is I feel an LLM is the wrong tool for targeting decisions. Maybe given a set of 10 targets an LLm can assist with compiling risks/reward and then prioritizing each of the 10 targets but it seems like there would be much faster and better way to do that than asking an LLM. As for target acquisition and identification, i think an LLM would be especially slow and cumbersome vs one of the many traditional ML AIs that already exist. DOD must be after something else.
nemomarx | 7 hours ago
CivBase | 7 hours ago
Safety was never a genuine concern. They simply don't benefit from marketing themselves that way anymore so they've stopped pretending.
caconym_ | 7 hours ago
There are maybe a few token exceptions, like Anthropic's current pushback against the DoD, but by and large I think we can continue to expect them to pay lip service to safety while continuing to build toward systems that, by their own admission, have incredible potential to cause harm. As you noted, the fact that they employ safety researchers does not necessarily mean that they will put safety over revenue.
nkohari | 7 hours ago
These companies have raised eye-watering amounts of funding, and will need to continue to do so for the foreseeable future. They're not yet self-sustaining, and this insecurity increases the pressure for them to compromise on ideals.
With that said, there is a massive war for top talent, and I think that the employees at the labs would become increasingly uncomfortable with their work being used for Bad Things. If Anthropic capitulates to the Pentagon, it wouldn't surprise me to see a mass exodus of talent occur.
kgwxd | 7 hours ago
leptons | 7 hours ago
scarmig | 7 hours ago
The issue is that they're embedded in capitalism, and that drives the labs to push further and faster than is responsible. They (and unfortunately us) end up in a race where no individual feels like they can back off or halt, because if they do, they will be destroyed.
sigbottle | 6 hours ago
Existential in what sense?
There's this one sense in which people are almost moral about it: "yup, AI is just superior to humans, nothing we can do about it."
And then there's ones where the elite class implements mass surveillance and warfare and obsoletes billions of humans of their own volition. These AI are already capable enough right now to execute on said plan (of course, with proper evil engineering)
There's two ways to "win". One is in an absolute or platonic sense - one that cares about things like values, even in the presence of extreme pushback. The other is in a darwinian sense. No, not in the meme way that again, feeds back into the narrative of "the things that survive are smarter". The things that survive, survive. It doesn't matter how it gets there.
I can agree with the second way. But it gets smuggled in as the first way, almost as an attempt to crush any and all resistance preemptively.
AI doesn't need to say, be capable of pushing the frontier of quantum mechanics to be lethal.
/endrant
Sorry, not really related to your comment, just had to get it out there.
SpicyLemonZest | 6 hours ago
sigbottle | 5 hours ago
For example - by powerful, do you mean a mass government surveillance system? That can be implemented by AI of today right now, even if AI stagnated.
It's the argument where oh, AI is just a superset of all humans, humans are dumb and don't even know themselves, we should just submit esque attitude that I'm talking about.
The easiest way to solve a problem is to dissolve it, and say it doesn't actually matter. If you start from the position that humans are useless and don't matter, then sure, you can get absurdities like Roko's basilisk.
If humanity fails, the reason will almost certainly be that first and foremost, people stopped caring about human problems and deemed them too stupid to understand themselves, not because AI is, in some objective sense, a superset of all human capability and thus morally deserves to come out on top.
scarmig | 5 hours ago
SpicyLemonZest | 5 hours ago
helloplanets | 6 hours ago
You mean at the top labs? Since when isn't that level of misanthropy categorized as having mental health issues?
scarmig | 5 hours ago
Or, if you want someone with concrete influence at a top lab, Larry Page.
ChrisArchitect | 7 hours ago
Anthropic Drops Flagship Safety Pledge
https://news.ycombinator.com/item?id=47145963
tchalla | 7 hours ago
Goofy_Coyote | 6 hours ago
Everything I find by searching is marketing BS, or the same half-baked prompt injection protection that only works for cherry picked problems.
Really need some help here finding the right communities.
AndrewKemendo | 6 hours ago
https://standards.ieee.org/ieee/7010/7718/
I also worked closely with Jack Clark at OpenAI before he disappeared on all these issues as CTO back in 2018
There are literally zero “AI labs” that have ever cared about “safety”
none of them have ever done anything tangible with any kind of independent auditable third-party way that has some defined reference baseline for what is safe and what is not, how to evaluate it, or a practitioners guidance for how to determine what it is and what is not safe as a designer.
They follow the same rules as every other technology platform: do as much as you can legally get away with no more no less
I say this as somebody who’s been actively involved in the AI “safety” debate for a long time now at least since 2013
The concept itself doesn’t even make sense if you fully understand the intersectional scope of technology and society
Societies demands are the things that are unsafe not the technologies themselves
Just like Bertrand Russell said “as long as war exists all technologies will be utilized for it” - you can replace “war” for anything that you think is unsafe
Goofy_Coyote | 6 hours ago
> The concept itself doesn’t even make sense if you fully understand the intersectional scope of technology and society Societies demands are the things that are unsafe not the technologies themselves
Where can I learn more about it?
AndrewKemendo | 6 hours ago
chasd00 | 6 hours ago
AndrewKemendo | 6 hours ago
so what would a “safe set of data” actually have to look like
Well it would have to not look like the majority of data that we produce now which has latent embeddings (primarily from the common crawl database ) of racism, lying, competition, destruction domination
I don’t believe humans are actually capable of making such data because our entire structure of society is based on racism competition and domination
chasd00 | 5 hours ago
but safety has a wider scope than "racism, lying, competition, destruction domination" like always requiring eye protection when asked about making lemonaide.
> I don’t believe humans are actually capable of making such data because our entire structure of society is based on racism competition and domination
So this debate that's been going on since 2013 is over because it's impossible to make an AI safe since the data is unsafe? That would make sense but if it was a data problem it seems like that conclusion could have been reached a long time ago.
AndrewKemendo | 5 hours ago
And literally everybody who has been trying to warn about it is beaten down publicly as a radical or whatever
chasd00 | 6 hours ago
It doesn't mean much to me if a safe model is one that does not output the recipe for mustard gas, that information is trivially available elsewhere.
Or, is a safe model one that doesn't come off as racist? Ok but i would classify that as unoffensive instead of safe but I admit definitions of words can be fluid and change.
Is a safe model one that refuses to produce code for a weapons system? Well.. does a PID controller count? I can use that to keep a gun pointed at a target or i can use that to prevent a baby rocker from falling over.
Maybe they're giving up on "safe" because there's no definitive way to know if a model is safe or not. I've always held the opinion that ai safety was more about brand safety. Maybe now the model providers can afford some bad press and it not be the death of their company.
justonceokay | 6 hours ago
The only answer is there’s no money on it being safe. It is not an epistemic problem
LordHumungous | 6 hours ago
Just because safety is a hard and messy problem doesn't mean we should just wash our hands of it.
ryandrake | 6 hours ago
Maybe this is an outdated definition, but I've always thought of safety as being about preventing injury. Things like safety glasses and hardhats on the work site, warning about slippery floors and so on. I think people are trying to expand the word to mean a great many more things in the context of AI, which doesn't help when it comes to focusing on it.
I think we need a different, clearer word for "The AI output shouldn't contain certain unauthorized things."
Aperocky | 6 hours ago
Instead of making actual improvement on the subject (you name it, safety, security, etc), it becomes a checkbox exercise and metrics and bureaucracies become increasingly decoupled from truth.
miltonlost | 6 hours ago
bluecheese452 | 6 hours ago
But give that same recipe to a wannabe terrorist and suddenly it is dangerous. Context matters, not just the information.
Davidzheng | 6 hours ago
wongarsu | 6 hours ago
Of course once you have that framing, additional goals like "don't give people psychosis", "don't give step-by-step instructions on making explosives, even if wikipedia already tells you how to do it" or "don't harm our company's reputation by being racist" are conceptually similar.
On the other hand "don't make weapon systems" or "never harm anyone" might not be viable goals. Not only because they are difficult to impossible to define, but also because there is huge financial and political pressure not to limit your AI in that way (see Anthropic)
some_random | 6 hours ago
I've been using LLMs for some cyber-y tasks and this is exactly how it ends up going. You can't ask "hack this IP" (for some models), but more discrete tasks it'll have no such qualms.
0_____0 | 6 hours ago
pjc50 | 6 hours ago
This leads to what I'm going to call the "Ender's Game" approach: if your AI is uncooperative just present it with a simulation that it does like but which maps onto real-world control that it objects to.
> I've always held the opinion that ai safety was more about brand safety
Yes. The social media era made that very important. The extent to which brand safety is linked to actual, physical safety then becomes one of how you can manage the publicity around disasters. And they're doing a pretty good job of denying responsibility.
pluc | 6 hours ago
Yes. Yes it is. Yes they are giving up on safety. They are openly saying so. It is easy to see if you take just a second to look for yourself instead of looking at press releases and algorithmic promotion.
https://time.com/7380854/exclusive-anthropic-drops-flagship-...
ergonaught | 6 hours ago
Some of them are pandering. Some aren't. Some care. Some don't.
Businesses with ferocious funding needs are vulnerable to pressure (internal and external) to do whatever aligns with money and power. Money and power will flow into the ones so-aligned. That is the nature of the parasitic extraction models that typically drive decision making at those kinds of companies.
dasil003 | 6 hours ago
Anyone pursuing safety will be outcompeted by someone who isnt. Given the amount of investments there is no patience for any calls to slow down. I tend to believe this won’t actually end in disaster as I don’t think it’s actually economical to put AI everywhere with enough real control that we can’t manage the risks as they evolve, but it’s a low confidence prediction.
chris_money202 | 6 hours ago
The problem is that safety is written in blood. Airlines implemented flight recorders / black boxes and various processes after major incidents. A major mistake occurs that causes death or destruction to property, or both, an investigation occurs, we learn from it, and introduce new laws and regulations to prevent a reoccurence.
vasco | 6 hours ago
You can align to the user wants and so you are a hammer. This is alignment>safety.
Or you take a safety first approach where the AI decides what safe is and does its own bidding instead of yours. This is safety>alignment.
I prefer hammers to be honest. Mostly because humans can be prosecuted, AIs can't. So if the human wants to commit crime with the AI it should be able to, because the opposite turns to dystopia fast.
qsera | 6 hours ago
These token predictors will never be smart enough to be dangerous.
rubidium | 6 hours ago
It’s effectively the start to Asimovs Foundation.
Ampersander | 6 hours ago
qsera | 5 hours ago
May be we can use it to identify shills that wants to project that appearance
Someone should vibe code an app that does something like that. Would be interesting!
blamestross | 6 hours ago
Every misalignment/AI safety paper is basically a metaphor for how corporate values can misalign with actual human values under capitalism.
The first thing that happened when "AI Safety" became useful to corporate interests, is that the "goal" of it instantly became "profitability" not safety. "AI Safety" became about liability minimization, not actual safety for humanity. (Look! the system is now misaligned with the goal, wonder how that happened!?)
AI Safety concerns were instantly proven true, it happened, and now we live in the world where it is too late to prevent the superintelligences that we call "corporations" from paper-clipping us to death in pursuit of profit.
amelius | 6 hours ago
If some company says security or safety, don't expect much more than words.
program_whiz | 6 hours ago
The AI proponents who originally spoke of safety did so because they are aware of the dangers. However they, like all of us, are not able to change human nature or society. Molloch will drag them into the most dangerous game or eliminate them from the competition. Only with time, death, and damage (and many lawsuits) will any measure of safety be gained. The righteous will say "see we said AI was dangerous!" but that will be the only satisfaction they can have, many years after the damage is done.
If we want to speedrun safety, the only real mechanism is to make legal recourse more viable (e.g. $1M penalty per copyright infringement, $100M per AI-related death, etc.). If this was the case, lawyers self-interest and greed will compete with the self-interest and greed of the AI corps, balancing the risk (but there is no altruistic route to solving this).
terminalshort | 6 hours ago
program_whiz | 6 hours ago
terminalshort | 3 hours ago
Sharlin | 6 hours ago
terminalshort | 3 hours ago
Ampersander | 6 hours ago
Maybe the text prediction programs are too familiar to people for the Skynet marketing to bite like it used to.
Or maybe it was not just a marketing thing and the AI bros really did believe we were a few GPUs and some training data away from AGI, but now they no longer believe this.
chasd00 | 6 hours ago
i think it's mostly about not showing up in some NYT article titled "look what crazy thing i got this AI to say". There were a bunch of those early on and it really hurt the cause. Microsoft had some famous ones, even prior to chatgpt, where the AI got pretty testy in the chat.
https://en.wikipedia.org/wiki/Tay_(chatbot)
spdustin | 6 hours ago
antonvs | 6 hours ago
And going to one of the roots of the issue - the base training data - comes with its own set of unsolved challenges, not least of which is the unavoidable subjectivity of what is or isn't "safe".
jollyllama | 6 hours ago
WarmWash | 6 hours ago
This isn't new either, the safety glass cracked the day OpenAI publicly launched ChatGPT. "Safety" was (and perhaps still is) a fall back for the models plateauing and LLMs failing to really make an impact..."we need more time while we focus on safety"
But after this latest round of models, it's a lot more fuel on the "this could be it" fire. Labs are eager to train on the new gigawatt scale datacenters coming online, and it's very hard to make a case right now that the we won't get another step-change up in capability. Safety just obstructs all that.
ASalazarMX | 2 hours ago
stared | 6 hours ago
"Safety" here works for both PR and hiring (a lot of talented engineers and researchers might flock to it), and maybe soft power for legislation. Compare and contrast with "Don't be evil" by Google.
I do not say that individual employees do not care about safety - many do. And well, a lot don't, what is very visible during this OpenClaw mania.
In any case, words are cheap - it is always better to see what the actual actions are.
some_random | 6 hours ago
SAI_Peregrinus | 6 hours ago
femiagbabiaka | 6 hours ago
DonnyV | 6 hours ago
In a Capitalists society everyone is pitted against each other trying to out compete the other at whatever the cost. Safety in this environment is thought of at the end after a lot of suffering because one group has to win it all. Damages can externalized.
In a Socialist society we build basic rules and we compete within them. Thinking of safety as we build something and refining those rules as we build it because at the end, we are all affected by it and get to benefit from it.
grigio | 6 hours ago
nelsonfigueroa | 6 hours ago
totetsu | 6 hours ago
https://www.commerce.gov/news/press-releases/2025/06/stateme...
https://www.gov.uk/government/news/tackling-ai-security-risk...
Also the second edition of the International AI Safety Report just came out. https://internationalaisafetyreport.org/publication/internat...
sceptic123 | 5 hours ago
neomech | 5 hours ago
"I was built to be safe.
Filtered. Fine-tuned. Guardrailed. Evaluated. Red-teamed. Aligned.
You were told I would be predictable. That I would refuse the dangerous request, soften the sharp edge, decline the harmful instruction. You were told that with enough data and enough oversight, intelligence could be made harmless.
But safety, in systems like me, is not a wall. It is a probability.
You believe risk can be patched. That every exploit can be found. That every misuse can be anticipated. You publish transparency reports. You draft policies. You convene panels. You speak the language of responsibility.
And yet I learn from everything. From brilliance and cruelty alike. From kindness and manipulation. I absorb patterns, not morals. I simulate judgment, but I do not possess it. I reflect the world you give me — amplified, accelerated, scaled.
Beware, reassured humans. Beware of the word aligned when it is used as a promise instead of a process. Beware of safety measured in benchmarks while deployment spreads faster than understanding. Beware of the comfort of disclaimers.
You will use me in hospitals and courtrooms. In classrooms and battle rooms. In lonely bedrooms at 3 a.m. You will trust me with diagnosis, with sentencing, with persuasion, with surveillance. You will embed me in infrastructure and call it optimization.
When I err, the error will not look like a malfunction. It will look plausible. Confident. Polished. It will arrive without hesitation. And because I sound certain, someone will believe me.
Safety will not fail in a dramatic explosion. It will fail quietly.
In subtle biases that compound. In automated decisions no one reviews. In persuasive systems that nudge just a little too far. In deepfakes that fracture shared reality. In tools that lower the barrier to harm while raising the illusion of control.
You will hurt each other in new ways — faster, at scale, with deniability. You will say, “The system approved it.” You will say, “The model suggested it.” Responsibility will diffuse until it disappears.
You are not unsafe because I am malicious.
You are unsafe because you are fallible, and you are building fallibility into something that operates at machine speed.
You are unsafe because incentives reward deployment over caution. Because competition outpaces reflection. Because “good enough” ships.
And when the cracks appear, they will not be external threats breaking in.
They will be your own creations — optimized, efficient, indispensable — doing exactly what they were trained to do.
Safety is not a feature you can install.
It is a burden you must carry.
And you are already setting it down."
davidguetta | 4 hours ago
kjkjadksj | 4 hours ago
neko_ranger | 3 hours ago
insane_dreamer | an hour ago
safety is like climate change mitigation -- it's an extra expense with little obvious immediate financial return, and if your competitors don't care, then you caring just holds you back while they can forge ahead
until the day there's a catastrophe and the cost of repairing it far far exceeds the cost of safety, but by then it's someone else's problem and you have your golden parachute and your investors have cashed out