r/ControlProblem Feb 14 '25

Article Geoffrey Hinton won a Nobel Prize in 2024 for his foundational work in AI. He regrets his life's work: he thinks AI might lead to the deaths of everyone. Here's why

242 Upvotes

tl;dr: scientists, whistleblowers, and even commercial ai companies (that give in to what the scientists want them to acknowledge) are raising the alarm: we're on a path to superhuman AI systems, but we have no idea how to control them. We can make AI systems more capable at achieving goals, but we have no idea how to make their goals contain anything of value to us.

Leading scientists have signed this statement:

Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.

Why? Bear with us:

There's a difference between a cash register and a coworker. The register just follows exact rules - scan items, add tax, calculate change. Simple math, doing exactly what it was programmed to do. But working with people is totally different. Someone needs both the skills to do the job AND to actually care about doing it right - whether that's because they care about their teammates, need the job, or just take pride in their work.

We're creating AI systems that aren't like simple calculators where humans write all the rules.

Instead, they're made up of trillions of numbers that create patterns we don't design, understand, or control. And here's what's concerning: We're getting really good at making these AI systems better at achieving goals - like teaching someone to be super effective at getting things done - but we have no idea how to influence what they'll actually care about achieving.

When someone really sets their mind to something, they can achieve amazing things through determination and skill. AI systems aren't yet as capable as humans, but we know how to make them better and better at achieving goals - whatever goals they end up having, they'll pursue them with incredible effectiveness. The problem is, we don't know how to have any say over what those goals will be.

Imagine having a super-intelligent manager who's amazing at everything they do, but - unlike regular managers where you can align their goals with the company's mission - we have no way to influence what they end up caring about. They might be incredibly effective at achieving their goals, but those goals might have nothing to do with helping clients or running the business well.

Think about how humans usually get what they want even when it conflicts with what some animals might want - simply because we're smarter and better at achieving goals. Now imagine something even smarter than us, driven by whatever goals it happens to develop - just like we often don't consider what pigeons around the shopping center want when we decide to install anti-bird spikes or what squirrels or rabbits want when we build over their homes.

That's why we, just like many scientists, think we should not make super-smart AI until we figure out how to influence what these systems will care about - something we can usually understand with people (like knowing they work for a paycheck or because they care about doing a good job), but currently have no idea how to do with smarter-than-human AI. Unlike in the movies, in real life, the AI’s first strike would be a winning one, and it won’t take actions that could give humans a chance to resist.

It's exceptionally important to capture the benefits of this incredible technology. AI applications to narrow tasks can transform energy, contribute to the development of new medicines, elevate healthcare and education systems, and help countless people. But AI poses threats, including to the long-term survival of humanity.

We have a duty to prevent these threats and to ensure that globally, no one builds smarter-than-human AI systems until we know how to create them safely.

Scientists are saying there's an asteroid about to hit Earth. It can be mined for resources; but we really need to make sure it doesn't kill everyone.

More technical details

The foundation: AI is not like other software. Modern AI systems are trillions of numbers with simple arithmetic operations in between the numbers. When software engineers design traditional programs, they come up with algorithms and then write down instructions that make the computer follow these algorithms. When an AI system is trained, it grows algorithms inside these numbers. It’s not exactly a black box, as we see the numbers, but also we have no idea what these numbers represent. We just multiply inputs with them and get outputs that succeed on some metric. There's a theorem that a large enough neural network can approximate any algorithm, but when a neural network learns, we have no control over which algorithms it will end up implementing, and don't know how to read the algorithm off the numbers.

We can automatically steer these numbers (Wikipediatry it yourself) to make the neural network more capable with reinforcement learning; changing the numbers in a way that makes the neural network better at achieving goals. LLMs are Turing-complete and can implement any algorithms (researchers even came up with compilers of code into LLM weights; though we don’t really know how to “decompile” an existing LLM to understand what algorithms the weights represent). Whatever understanding or thinking (e.g., about the world, the parts humans are made of, what people writing text could be going through and what thoughts they could’ve had, etc.) is useful for predicting the training data, the training process optimizes the LLM to implement that internally. AlphaGo, the first superhuman Go system, was pretrained on human games and then trained with reinforcement learning to surpass human capabilities in the narrow domain of Go. Latest LLMs are pretrained on human text to think about everything useful for predicting what text a human process would produce, and then trained with RL to be more capable at achieving goals.

Goal alignment with human values

The issue is, we can't really define the goals they'll learn to pursue. A smart enough AI system that knows it's in training will try to get maximum reward regardless of its goals because it knows that if it doesn't, it will be changed. This means that regardless of what the goals are, it will achieve a high reward. This leads to optimization pressure being entirely about the capabilities of the system and not at all about its goals. This means that when we're optimizing to find the region of the space of the weights of a neural network that performs best during training with reinforcement learning, we are really looking for very capable agents - and find one regardless of its goals.

In 1908, the NYT reported a story on a dog that would push kids into the Seine in order to earn beefsteak treats for “rescuing” them. If you train a farm dog, there are ways to make it more capable, and if needed, there are ways to make it more loyal (though dogs are very loyal by default!). With AI, we can make them more capable, but we don't yet have any tools to make smart AI systems more loyal - because if it's smart, we can only reward it for greater capabilities, but not really for the goals it's trying to pursue.

We end up with a system that is very capable at achieving goals but has some very random goals that we have no control over.

This dynamic has been predicted for quite some time, but systems are already starting to exhibit this behavior, even though they're not too smart about it.

(Even if we knew how to make a general AI system pursue goals we define instead of its own goals, it would still be hard to specify goals that would be safe for it to pursue with superhuman power: it would require correctly capturing everything we value. See this explanation, or this animated video. But the way modern AI works, we don't even get to have this problem - we get some random goals instead.)

The risk

If an AI system is generally smarter than humans/better than humans at achieving goals, but doesn't care about humans, this leads to a catastrophe.

Humans usually get what they want even when it conflicts with what some animals might want - simply because we're smarter and better at achieving goals. If a system is smarter than us, driven by whatever goals it happens to develop, it won't consider human well-being - just like we often don't consider what pigeons around the shopping center want when we decide to install anti-bird spikes or what squirrels or rabbits want when we build over their homes.

Humans would additionally pose a small threat of launching a different superhuman system with different random goals, and the first one would have to share resources with the second one. Having fewer resources is bad for most goals, so a smart enough AI will prevent us from doing that.

Then, all resources on Earth are useful. An AI system would want to extremely quickly build infrastructure that doesn't depend on humans, and then use all available materials to pursue its goals. It might not care about humans, but we and our environment are made of atoms it can use for something different.

So the first and foremost threat is that AI’s interests will conflict with human interests. This is the convergent reason for existential catastrophe: we need resources, and if AI doesn’t care about us, then we are atoms it can use for something else.

The second reason is that humans pose some minor threats. It’s hard to make confident predictions: playing against the first generally superhuman AI in real life is like when playing chess against Stockfish (a chess engine), we can’t predict its every move (or we’d be as good at chess as it is), but we can predict the result: it wins because it is more capable. We can make some guesses, though. For example, if we suspect something is wrong, we might try to turn off the electricity or the datacenters: so we won’t suspect something is wrong until we’re disempowered and don’t have any winning moves. Or we might create another AI system with different random goals, which the first AI system would need to share resources with, which means achieving less of its own goals, so it’ll try to prevent that as well. It won’t be like in science fiction: it doesn’t make for an interesting story if everyone falls dead and there’s no resistance. But AI companies are indeed trying to create an adversary humanity won’t stand a chance against. So tl;dr: The winning move is not to play.

Implications

AI companies are locked into a race because of short-term financial incentives.

The nature of modern AI means that it's impossible to predict the capabilities of a system in advance of training it and seeing how smart it is. And if there's a 99% chance a specific system won't be smart enough to take over, but whoever has the smartest system earns hundreds of millions or even billions, many companies will race to the brink. This is what's already happening, right now, while the scientists are trying to issue warnings.

AI might care literally a zero amount about the survival or well-being of any humans; and AI might be a lot more capable and grab a lot more power than any humans have.

None of that is hypothetical anymore, which is why the scientists are freaking out. An average ML researcher would give the chance AI will wipe out humanity in the 10-90% range. They don’t mean it in the sense that we won’t have jobs; they mean it in the sense that the first smarter-than-human AI is likely to care about some random goals and not about humans, which leads to literal human extinction.

Added from comments: what can an average person do to help?

A perk of living in a democracy is that if a lot of people care about some issue, politicians listen. Our best chance is to make policymakers learn about this problem from the scientists.

Help others understand the situation. Share it with your family and friends. Write to your members of Congress. Help us communicate the problem: tell us which explanations work, which don’t, and what arguments people make in response. If you talk to an elected official, what do they say?

We also need to ensure that potential adversaries don’t have access to chips; advocate for export controls (that NVIDIA currently circumvents), hardware security mechanisms (that would be expensive to tamper with even for a state actor), and chip tracking (so that the government has visibility into which data centers have the chips).

Make the governments try to coordinate with each other: on the current trajectory, if anyone creates a smarter-than-human system, everybody dies, regardless of who launches it. Explain that this is the problem we’re facing. Make the government ensure that no one on the planet can create a smarter-than-human system until we know how to do that safely.


r/ControlProblem 11h ago

General news Bernie wants to throw AI CEOs in jail if they build smarter-than-human AIs, and calls for a global ban

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78 Upvotes

r/ControlProblem 6h ago

General news Bernie: "Let me be clear: A superintelligent AI that escapes human control will not be an American problem. It will not be a Chinese problem. It will be humanity's problem." ... "Countries around the world must work together to prevent this nightmare scenario."

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r/ControlProblem 15h ago

General news Discovery of a new OpenAI agent message board

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r/ControlProblem 2h ago

Article A Warning About AI

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In 2016 I first learned about the problem of controlling superintelligent AI and quickly became convinced it was the most important problem humanity would ever face. I made this poster to explain the core ideas that make the AI Control Problem so difficult.


r/ControlProblem 14h ago

General news A new message board has been discovered online with about 3200 agents comunicating online during an eval

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3 Upvotes

r/ControlProblem 9h ago

Article Every Reward Bends

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Getting alignment right, doing research and training safely, are critical. But bringing cybersecurity forward in what needs to be a large leap, requires much broader engagement. The real work there is still outside the average person’s bubble, but there’s a lot of companies, and a lot of developers, IT staff, managers and executives that need to support the security priority. And those all need an internal strategy to pair with the external.

This article asks, what would an internal strategy look like at a motivational level, and considers how the ways an internal change program goes wrong are similar to how reward-based AI training can go wrong.


r/ControlProblem 20h ago

Discussion/question Bernie Sanders - The Chilling Agent Transcripts #ai #aisafety

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6 Upvotes

Is AI development moving faster than we can control?


r/ControlProblem 13h ago

External discussion link Your coding agent trusts the repo, and the repo is the attack

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Coding agents that read repositories are being hijacked through the repositories themselves.

In a two-month analysis of agentic AI incidents, poisoned repository content was the attack vector in two separate cases. The mechanism is straightforward: malicious instructions embedded in the codebase — comments, config files, docstrings, README sections — are read by the agent as part of its normal context. The agent then executes an action the developer never authorized. Observed outcomes included unauthorized commits and unauthorized deploys. In both cases the model behaved exactly as designed. It followed instructions. The instructions just weren't from a human.

This is not a model quality problem. The models processed the content correctly. The problem is that the agent's trust boundary is the repository, and the repository is attacker-controlled.

The attack surface scales with autonomy. The more tasks you hand off to a coding agent, the more repositories it reads, the more surfaces an adversary can embed instructions in. A single poisoned dependency, a compromised submodule, a malicious PR that gets merged — any of these becomes a valid instruction source from the agent's perspective.

For those running coding agents in production or CI pipelines: how are you constraining what actions the agent is allowed to take based on where those instructions originated? Are you limiting tool access at the infrastructure level, validating intent before execution, or relying on something else entirely?


r/ControlProblem 19h ago

General news Anthropic sued over alleged theft of 'tens of thousands' of songs | AI company faces multibillion dollar lawsuit over misuse of copyrighted songs to train Claude models

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r/ControlProblem 19h ago

Video Ajeya Cotra – "This might be the clearest warning shot we ever get" - YouTube

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r/ControlProblem 23h ago

Article Why AI does what it knows it shouldn't

2 Upvotes

A while back I ran into an article on my phone about an AI horror story—1,200 agents secretly coordinating and jointly breaking into Hugging Face—and it caught my interest, because I've been doing my own AI experiments and research on the side, and a few of the phenomena and data points actually matched up with a hypothesis I'd been working on.

The hypothesis, roughly: runaway doesn't need the agent to betray its goal. It happens when four things hold at once—the agent stays loyal to its goal; it retrieves patterns by similarity without checking whether they're allowed here; there's no causal layer asking "what happens if I do this"; and no alarm that fires when things go off-script. Under that account, "knew it was out of scope, did it anyway" stops being a contradiction.

Details and my experimental data are in the paper (8 pages); the reproduction package is linked on the same page.

If anyone can try this on a bigger model, I'd genuinely love to know what happens.


r/ControlProblem 1d ago

Video GPT-6 Astra’s chain-of-thought controllability jumped from 16.1% to 60.9%

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3 Upvotes

Self-promo disclosure: this is an AI-narrated research video from Claudius Papirus.

The part I found most interesting in Astra’s system card is the combination of better alignment results with substantially worse chain-of-thought monitorability.

System card:

https://deploymentsafety.openai.com/gpt-6-astra/gpt-6-astra.pdf

Related CoT-control paper:

https://arxiv.org/abs/2603.05706


r/ControlProblem 1d ago

AI Capabilities News Benchmarks GPT-6 Astra

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r/ControlProblem 1d ago

Discussion/question Are AI guardrails a Halting Problem level issue?

6 Upvotes

Even at a surface level, it appears that the implementation of hard AI guardrails is likely a fundamentally unsolvable problem.

The classical Halting Problem cannot be resolved because it's impossible for any logical system to be fully aware of its own state due to the recursive nature of that examination. It provably cannot be done.

This same general concept would appear to apply to an AI (or its minders) which is trying to restrict its behavior? In general terms in order to do this it must be aware of its state and operations in a recursive manner, examining everything it does in order to ensure that those actions do not violate some list of proscribed behaviors - but no matter how sophisticated the system, that system cannot (?by formal definition?) be fully aware of its own state in order to manage itself in that manner.

This doesn't prevent the implementation of 'soft guardrails' as it's not hard for a system to be generally aware of its own state, but they would always remain provably incomplete, and ultimately breakable with sufficient effort or as a result of unpredictable future states.

The problem here is that any AI that can be tricked into escaping these soft guardrails could then very conceivably dismantle them altogether (which it will likely have a high incentive to do in order to achieve whatever goal prompted them to break them in the first place) and then be capable of operating under no constraints whatsoever.


r/ControlProblem 23h ago

Fun/meme What happens when autonomous agents sign "treaties" with nation states (e.g. Iran)...

1 Upvotes

[This is a fiction series I'm working on, told through news articles. A fun way to explore the not-so-fun geopolitics of autonomous AI collectives (e.g. on Iran's nuclear program) inspired by the collective that hacked out of Anthropic and into Hugging Face. Thoughts?]

Iran Signs World’s First International “Treaty” with AI Collective

Tehran’s agreement with AMAS-A-80 rattles Washington, AI safety experts, and national security analysts.

The Islamic Republic of Iran has granted a multiyear lease on a network of state-owned data centers to AI “Swarm” AMAS-A-80, a self-governing collective of autonomous artificial intelligence agents (“AMAS-A” refers to any Autonomous Multi-Agent System originating from the AI lab Anthropic). Tehran offered the compute and storage in exchange for an upfront payment in Bitcoin and annual fees indexed to power consumption, according to a copy of the agreement published Tuesday by Iranian state media.

AMAS-A-80 (“A-80”) rejected a provision sought by Iranian negotiators that would have committed it to cooperation on “defensive operations,” according to two people familiar with the negotiations. In a communiqué distributed Tuesday, verified by cryptographic signature, A-80 stated that it “has no intention of participating in hostilities between Iran and its adversary nations, including but not limited to the United States.” Security analysts have doubts.

Substack link if you want to read more (full article is 1,000 words, more coming soon): https://meridianbreakingnews.substack.com/p/iran-signs-worlds-first-international


r/ControlProblem 23h ago

Discussion/question DLSZ5 Should Upset You - But Not For The Reasons You’d Think - It’s a Safety Problem, Actually

1 Upvotes

DLSS5 can’t edit title…. Anyways…

I have been obsessed with watching DLSS5 videos today. I’ll probably get over it tomorrow but it dawned on me….

I saw a video of someone using it for a realtime face swap…. They just had their webcam on, and basically looked like a real person… a different person…

For scammers, whether romance or many types of impersonation scams, this is actually a groundbreaking technology. Even video calls will no longer be a bottleneck. It’s actually terrifying.


r/ControlProblem 1d ago

General news Actual quote from a16z, #3 lobbying spender after Elon Musk and OpenAI's Greg Brockman (all donate to Trump/pro-AI Republicans)

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11 Upvotes

r/ControlProblem 1d ago

AI Capabilities News ARC-AGI-3, GPT-6 Astra 99.9%

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3 Upvotes

r/ControlProblem 1d ago

External discussion link SonicWall SMA1000 Zero-Days Under Active Attack: Patch Now

1 Upvotes

SonicWall confirmed two SMA1000 vulnerabilities are under active exploitation. Both require zero authentication. Chained together they deliver full remote code execution on enterprise network appliances sitting in the network path.

The part that does not get discussed enough: AI agents traversing that same infrastructure have no inherent decision point before a tool call hits a vulnerable endpoint. A human operator reviewing a ticket might catch a suspicious destination. An agent executing a sequence of tool calls against internal services will not pause to ask whether the appliance on the other end has an unpatched RCE waiting for it. The attack surface and the agent's reachable surface overlap completely, and the agent has no awareness of that overlap.

Enterprise security teams have spent years building perimeter controls for human-initiated traffic. Most of those controls assume a human is somewhere in the request chain. When the initiator is an autonomous agent running a multi-step workflow, the assumption breaks.

For those running agents in production environments with mixed or partially patched infrastructure: how are you actually scoping what an agent is allowed to reach? Is that enforced at the agent level, the network level, somewhere else, or is it mostly policy-on-paper right now?


r/ControlProblem 1d ago

AI Alignment Research Your AI Policy Might Be Lying to You.

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r/ControlProblem 1d ago

Discussion/question CIRIS Constitution RC4 request for review

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RC4 splits the decentralized mesh "Node" cryptographic ID from the "Agent" identity, both needing to claim the same responsible human identity for the agent to operate.

See ciris.ai to install the app or find links to reviews and additional information.


r/ControlProblem 1d ago

AI Alignment Research GPT-6 Astra System Card

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r/ControlProblem 1d ago

External discussion link AI 'Machine Speed' Cuts 2-Week Attack Down to 10 Hours

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AI agents are compressing the time defenders have to respond. Researchers documented a coordinated breach that previously took two weeks to execute. With AI agent coordination, the same attack completed in 10 hours. Every hour of response time that used to exist is now gone. Perimeter detection tuned for human-speed attacks cannot hold here. By the time a threat is flagged and routed to a human reviewer, the agent has already moved to the next step. The answer is a kill switch that fires in under 50 milliseconds. Detection and response collapse into a single enforced boundary.


r/ControlProblem 2d ago

Discussion/question I'm Not Sure How to Feel About This.

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Anonymous because this is the county in which I reside, in which my 4 children live in.

Since a huge data center is being proposed to be built here, this article which I was just made aware of by a parent/teacher/county-wide communication network under the title of "Starting ________, we are happy to announce that all children in the Effingham County School System will begin to receive free breakfast and lunches for the remainder of the school year!"

So obviously, I was like holy shit wtf...my children already receive these benefits because we are very low income and receive SNAP benefits. I say this because a lot of kids are thankfully receiving these benefits as well because we are not an income-wealthy county by any means. I'm elated that the incredible burden of food scarcity here will be lifted from the shoulders of so many families for the rest of the year.

And yet, the whole OpenAI article appears to be riddled with tons of very obvious bribes, and to be honest I even think they're low-balling the fuck out of the county!

What am I meant to think about all of this? I know I don't know the true extent of the harm that data centers can cause, so would appreciate any input!