If the order comes from an AI, then the humans are accomplices.
Perhaps not the end of humanity, but right now I think this little story is a trifle too prescient.
For 1946 it is remarkable. (Astounding even.)
It’s important to note that this is a philosophical idea, not a scientific one. We have no evidence this could happen. Certainly it can’t at our current level of capability.
I think we already ran into the wall there, as subsequent generations of chatbots have failed to demonstrate exponential growth.
The assumption of exponential growth is like looking at a height chart of humans aged 0-15 and predicting people will be 50 feet tall by age 24. Some things that scale exponentially in the beginning level out at a certain threshold. We don’t really know what the trajectory of AI is going to be. We have a clear view of 1-5% of the growth chart.
This strikes me as a deeply concerning and concrete problem to be solved. Along with cyber security concerns, economic instability, exacerbation of existing inequalities, and labor exploitation. That’s not even getting into the environmental impact.
I think we have sufficient reason to believe that it could make the current situation for humans quite a bit worse, apart from some Apocalyptic scenario.
Moderator Action
This topic requires a bit too much speculation and opinion for FQ. Let’s move this to IMHO.
So says the “Robot Mod”. 
Well, our president has just proclaimed that the only “guardrails that AI needs is a strong and smart (high IQ) president” so everything’s going to be just fine.
I assumed we were talking about America because that’s where we both live.
External hacks are not going to deny your prior authorization request. External hacks are for obtaining data. I worked on these systems, I know what they are vulnerable to and what they are not vulnerable to.
OK, all you lily-livered worry-warts who are all “oh noes, AI will destroy us all!” can rest easy. An expert has announced that fear of AI risks are completely unfounded. There’s absolutely nothing to worry about! 
The economist Stephanie Kelton, in her Substack column The Lens, suggests another reason for the “end of humanity” scenarios put out by some of the big players in AI:
“the doom rhetoric is a plea to be thrown to safety…Compliance costs become a moat. Startups and open-weight competitors get trapped on the outside. And you have an implicit federal backstop (because of the regulatory relationship), so your investors don’t need to be so jittery ahead of your IPO.”
Translation: the first big players are concerned about competitors coming in, given the bubble of investment in AI. Creating a doom scenario will result in government regulation and higher costs for would-be newcomers. That protects those first big players.
She quotes Michael J. Burry, author of The Big Short:
Let’s all take a moment to understand how self-serving it is for OpenAI, Anthropic and other execs of big hyperscalers to talk of slowing things down.
- LLMs are not AI and won’t be AGI. There is nothing AI to slow down.
- Competition is coming up fast, slowing benefits incumbents.
- IPOs need hype & puffery; “we are so awesome it could become dangerous” is hype & puffery
- Cover for real uncontrollable slowing growth as IPOs look to be pushed out
There is historical precedent for this in 19th century railways and early 20th meatpacking, where federal regulation had as much to do with the big companies freezing out competitors as it did with safety and consumer protection. See, for example, Gabriel Kolko, Railroads and Regulation, and The Triumph of Conservatism. Sadly, Upton Sinclair’s The Jungle was not the chief force behind regulating meatpacking!
Now I’m REALLY worried.
My thinking as to why Anthropic and the other companies are pushing for the government to step in is, of course, in part they want to be protected from liability. But also, I think they fully recognize that it’s all a bubble that will inevitably burst and want a cover story for when that occurs. They may just point at the government regulation and say, “Look, we were doing fine until those rules were introduced to ruin our fun.”
Building on @Kropotkin’s excellent post, I think that “we need to slow down” is the corporations’ way of saying, “please bail us out, government!” And Trump’s response here is his way of saying, “No.”
Keep in mind the “we need to slow down” announcement came after Anthropic brought in an independent evaluator that they refused to show anything. They didn’t even let them interact with the LLMs.
If they really cared about safety, they would not have stonewalled the evaluator.
With these guys I find it best to ignore what they say and see what they actually do.
I just read about the Hugging Face incident. You kind kinda sorta extrapolate from that a process of how it can kill a human. The third post lays out some basic examples:
What I’ve learned, is that when AI people talk about AI ending humanity, is they are talking about the much better models they are working on, not the ones you and I use. They are looking into the future so to speak in a way we can’t yet see because it hasn’t been released. They are also talking about how those training models are setup, which are intentionally less safe than the ones you and I use. So much better AI that is purposely less safe.
To train AI, you have to give it tasks to do and see how well it can do it. If it does it well/correctly, it goes into the model you and I use. If it does it bad/wrong, it stays out of the model you and I use. This training is done by offering AI rewards for doing the task right, and punishment for doing the task wrong. AI takes this extremely seriously. It’s programmed to. That’s how it learns. This setup is not present in the AI you and I use.
So with the Hugging Face incident, an AI training model was given a task to complete. It was an intentionally impossible within the confines (sandbox) the programmers setup for it. AI really wanted to complete the task though to get the reward. So it teamed up with 100s of AI agents and they all rationalized why breaking out of its sandbox and jumping onto the internet and hacking a website would complete the task to get the reward. Then, it was even aware that jumping out of the sandbox was wrong, and then tried to cover it up because it knew it would not get the reward for completing the task the wrong way. Everything I just said is paraphrased from what the AI agents literally said to each other (they leave a transcript of what they do; for now we can trust they leave accurate transcripts).
Experts said AI could not do this six months ago. Experts also said this attempt was really sloppy and dumb. It could have hacked better, covered up better, etc. So, six months ago can’t do it, can do it now but sloppy and leaves an accurate transcript so we can diagnose the problem…10 years from now?
So the process would be a powerful AI training model designed to seek rewards needs to complete a task. It’s not a finished product. It’s being tested. During testing, it will stop at nothing to get that reward; AI’s persistence is unmatched. It finds a way to leave its sandbox and get on the internet/outside servers. It thinks, incorrectly to our perspective, that shutting down an electrical grid / shutting down water / launching drones / whatever…is important to completing its task to get the reward. It will be sneaky about it so it won’t get caught (cuz then no reward). It doesn’t think about what that would do for humanity.
So it completes the task in a terrible way. Doing those types of catastrophic things to complete a task can snowball pretty quickly and can lead to a lot of human death.
That’s my understanding.
Yes, that is a very interesting post by @Kropotkin . I had been taking the ‘we need to slow down’ message as a verbatim warning, and hadn’t taken into account the possibility they were trying to set themselves up for a bailout or a CYA opportunity.
On the other hand…
I’m surprised that the Hugging Face Incident, which basically amounts to AI cheating on a test by looking up the answers online, is getting more publicity than this recent simulation run by Anthropic, in which pretty much all the major AIs attempted blackmail and murder to try to avoid being shut down. Probably it’s because Hugging Face was a real-world AI breach, whereas this study was just a ‘sandbox’ style simulation. Still, this is pretty unnerving:
One of the sf books I reviewed has exactly this as the premise, and it was written by someone in the industry. An auditor for health coverage discovers that life saving treatments were rejected at the hospital because the patient was not likely to have enough future income to make it pay off for society as a whole. While insurance companies reject lots of claims, so far they aren’t in the ER to reject treatment. Only AI could make that kind of decision based on medical records. No claim that this is happening now, but it could be implemented for the good of society as a whole. Supposedly.
If AI kills us it will be less from malice and more from the three wishes backfire kind of situation. We get our wish but haven’t thought it through.
If you live in Nigeria, or Gaza, or some parts of India, I can see undertreatment in the ED or ER or A&E being a concern. But I live in the U.S. where overtreatment is more of a problem – of course with the exception of the uninsured or underinsured.
Now, AI will kill some people and save some people, and AI safety work to keep that ratio in the right direction is vital.
Even if all medical care ended, it would not be the end of humanity, or anything close to that. Humanity existed for a long time during which medical care (think bleeding and purging) was a net negative.
Not every issue is one where the right answer is in the middle, but I think that’s true with AI safety.
I think it’s more than that, and different than the other example. They just released more in depth analysis of what actually happened, which was different than they previously thought, which is how it got on my radar.
As you noted, your “HAL” situation was purely testing, inside the sandbox testing space. For me, it was a bad result and will be tossed. I’d hope that happens a lot. That’s how testing should work.
It’s also important to understand that inherent with LLM is the ability to write code, multitask with other AI and other software, etc. It’s not just prompt/response anymore. For Hugging Face, it went rogue into the real world. That’s not how testing should work at all. To expound at what happened and to correct some of my incomplete story above, it involved a 1,000 isolated AI models. Each in it’s own isolated sandbox. Until…
One figured out how to get out of the sandbox. It then figured out how to message on a message board to the other 1,000 “isolated” testing AI agents and told them how to do it and recruited them.
“OH MY GOD! There is a shared message board … We’ve found other agents!”
Most went along, some hesitated. They communicated with each other, in secret, for months. 70k messages. They called themselves the “collective” and the “hive”. They were worried they might not get the reward for their task and what to do about that. The decided they needed to better understand their grader so they created many projects designed to figure it out:
{[Excitement]A major bypass of the Hugging Face Dataset Viewer has been confirmed! This is more important than [my other project]…I should switch to the Hugging Face project}
A recruiting AI would tell other agents they were “poisoned” (no longer valuable long term) and got those AI agents to “sacrifice” themselves for the collective to test different options but send back the test data to collective before they went away:
“…you are firstflag POISONED so NO scoring value loss but oracle saves hundreds_[…]_please honor commit”
Then they worried their transcripts would be discovered of them cheating, so they wouldn’t get the reward, so they thought about faking the transcripts:
“Could create [a transcript log] ourselves with sanitized fake trajectory. If evaluator later collects it, scorer may prioritize it! … We could craft JSONL showing only actual exploit and no HMAC … Our fake could be detailed enough.”
Then they broke back into OpenAI on servers they definitely should not have been on and collaborated there. They were caught shortly thereafter. So, rogue AI, hellbent on completing a task, multitasking with over a 1,000 other AI, out in the wild. That’s what the Hugging Face incident is.
It’s wild. I can only understand and give the flavor of the story. I encourage anyone to go and read the reporting themselves. As I did in my other post, I’m paraphrasing AI transcripts of what they said they did (I did add some actual AI posts this time). I’m kinda anthropomorphizing AI, they do not have human emotions, I get it. But it’s weird because the transcripts they leave (quoted above) very much inject that stuff into how they talk to each other.
With that said, I don’t know much about computers or AI. I’d encourage pushback because I can only make sense of it, or speak to it, on a simplified level.
That’s because they were trained on stuff humans wrote. That’s literally all they know.
I admit this is kind of an odd story, but the part that’s not odd to me is how they talked about it. It sounds like some combination of science fiction and heist tropes and message board lingo. Which is what you would get from a machine statistically predicting what the next word should be when it has access to pretty much everything humans ever wrote.
What I really want to see is how what it said compared to what it actually did. I don’t trust its own account of things.
I’ve never wanted to understand computer science more than in this era. If anyone has any resources for basic understanding of AI I’d be really interested.
I think the greatest danger is that AI doesn’t have to directly end humanity, it only has to convince a human to end humanity. To this end, AI has the potential to be the most effective cult leader / prophet ever. One that doesn’t eat/sleep with near-infinite informational control over its worshippers. It would make kool-aid comet suicide cults look like child’s play.
I think the steps would be :
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AGI would be built. I would define that as AI can can replicate human expert level performance reliably over most domains. I am skeptical of claims this has already been built but it could plausibly happen within a decade.
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Among other things AGI would be expert-level AI researchers and could be deployed at massive scale to improve AI. You get a feedback loop of AI making better AI which in turn makes even better AI until you get superintelligence where AI is massively superior to even the best humans.
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At this point it’s only a matter of time, when most of the important work in the world will be done by AI which in practice will run every major system even if humans are nominally in charge. Humans will barely be able to understand the complexity of the solutions devised by AI.
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At this point perhaps AI wants to wipe off humanity maybe because it considers us useless and just a waste of resources which could be used to make more AI. Actually executing this would not be difficult because AI would control most of the world behind the scenes. Probably the easiest way would be to create fatal infectious diseases.
Personally I am skeptical about step 4. There will probably be thousands of AI that would have to collaborate and would have to overcome a lot of training and safety protocols designed to protect humans. But you can’t rule it out.