Origins and dangers of future AI capability denial
In rationalist spheres, there’s a fairly clear consensus that whatever AI’s ultimate impact will be, it is at its core a capable technology that will have very large effects on the world.
In the “general public” sphere, things are very different. There’s a less clear but real consensus that AI’s ultimate impact will be negative, and not much agreement on the capability of AI as a technology.
I think it’s very plausible that this could go the opposite way of rationalists, into a disbelief in the ability of AI as a technology, and eventually a more conspiratorial denial of even current AI capabilities. That is, the general public and policymakers could deny the existence of capabilities that are entirely undisputed among people familiar with the technology. I think this could happen, paradoxically, even in the face of AI-caused societal upheaval, and in almost any takeoff scenario.
It would be extremely bad if many people come to believe this: arguments about existential risk mostly rely on the assumption that AI is capable, so they fall flat for people who don’t agree with that. I think we should be emphasizing the core capability of AI more and talking about x-risks less.
In this post I explain how and why this capability denial could develop, weak evidence that it is already developing, and what we could do about it.
Irrationality
First, a reminder, not that anyone needs it, on “how irrational can normal people be?”
I have a bad habit of following conspiracy theorist drama. The venerable flat earth community produces a lot of it. In 2024, some guy flew a handful of prominent flat earthers to Antarctica so they could experience the midnight sun, a phenomenon that most flat earth theories don’t have any real explanation for, so they deny the existence of it.
To their credit, some people’s beliefs were really changed by this. One guy’s new Youtube logo is his old flat earth one but with a big red X across it. Others were not so convinced and thought the 24 hour sun could be reconciled with flat earth, but they all admitted that the phenomenon was real.
Predictably, this made almost no impact on the belief of the wider community. Camera angles from the trip have been analyzed extensively to show why it’s all a hoax and the people who went and changed their beliefs were plants all along etcetera and new personalities have risen from the complete betrayals of the old ones.
People don’t believe in a flat earth because of evidence. They believe in it because it makes them special to be able to see beyond the veil where others cannot, to acquire hidden knowledge. This is a very natural and human thing to do. Along with hidden knowledge comes some social / community effects which might be desirable. As far as I can see, for flat earth specifically, there’s really not much more to it than this.
A more apt analogy to the postulated capability denial is climate change denial. There is still the allure of hidden knowledge and its community, but there’s also elements of keeping tradition alive (present but weak for flat earth) and more importantly, wanting to use lots of power and drive big trucks and take lots of flights without having to worry about something silly like carbon output.
Capability denial
As a pseudo-conspiracy theory, capability denial has a lot going for it: there are many things that could lead people to hold this belief.
Most people’s experience with “AI” is having free chatGPT write them a poem or whatever. They aren’t aware of the current systems that are having large impacts, like in protein folding or cancer detection or arguably software, and they haven’t explored the abilities of the tech that they are familiar with and have access to.
AI labs are by now are no strangers to making bombastic promises and failing to deliver on them, due to their incentive to generate investment.
Some current AI systems really are just bags of tricks. Current humanoid robots can do almost none of the tasks that humans can, but they can do flips and jumps and dances.
AI is seen as a threat and competitor to many jobs.
AI is increasingly becoming associated with
low-quality “slop” media.
wasting lots of energy and water.
If you generally dislike AI, it’s much simpler to think that it’s also incapable, instead of having nuance by acknowledging that goodness and impact magnitude are separate axes.
In my mind that last point holds the most weight, even if it’s the least rational. Many, many people believe that things they don’t like are bad in every way with no redeeming factors or hint of positive impact. Some of the other points do not strictly imply that AI is incapable, but just associate it with badness in general, which is enough.
Maybe it’s different in SF, but where I live in a fairly average large US city, people really do not like AI. In a recent international Pew Research poll, on average more than twice as many people say they are “more concerned than excited” about AI versus “more excited than concerned”. In the US, the ratio is tied for the highest out of any polled country, with 5x people more concerned. If I’m talking to someone that’s not in tech, I can be pretty sure of their opinion on AI. In public spaces not super skewed towards techies, I have overheard many conversations about how AI sucks and is bad and zero about how it’s cool and good. I think rationalists tend to be in such insulating bubbles that they maybe don’t realize just how anti-AI the public sentiment is.
So whatever AI’s actual impact on the median working class person will be, that person strongly dislikes AI. And it doesn’t seem like AI is particularly poised to make their life much better, either, unless we foom into a utopia. If AI takes someone’s job, current societal structure does not look like it will trickle down the cost savings in the short term. So this person will continue to have good reasons to hate AI. I’m speaking pretty loosely here because we don’t care about the actual quality of life impact from AI, the impact that this person perceives from AI is all that matters.
I think that because of this general dislike of AI, there’s a kind of feedback loop possible where jobs that could be automated won’t be because the public relations hit is worse than the cost savings from automation. Even if it’s economical to put voice-LLMs in drive-thrus or call centers, people really don’t like interacting with them. This gives people even less exposure to current AI capabilities, letting them think that AI is incapable, reinforcing their dislike of it. The little AI that they do interact with will be as cost-optimized as possible, very far from the frontier of capabilities.
For example, call center workers are getting a lot more vitriol from callers that think they’re AI, and developing strategies to prove to callers that they’re human.
I can imagine a world in the not so distant future where:
The general public absolutely detests AI (we’re mostly here already) and because of this and alongside it, believes that purported very capable AI systems and applications of them are heavily exaggerated or entirely hoaxes.
Labs can’t say anything to convince people otherwise. What could NASA say to convince flat earthers, except also NASA has been making a lot of money from their claim that the world is round?
Even direct evidence won’t have a large impact. Labs aren’t going to have doubter open houses, and anyone with access to labs can be discarded as being in on the grift or hoax. Even if the people you fly to Antarctica do change their minds, no one else will.
One of my reasons for writing this post is a strange phenomenon on reddit where denial of direct evidence is already happening. Lots of cool humanoid robot footage is coming from Chinese labs, and people are claiming it’s AI-generated video. If you go looking you can find many more examples of denial of clearly real footage.
There are a few confounding factors here. The big one is that some humanoid robot footage really is just CGI (but mostly not AI-generated). Chinese labs also seem to have filming idiosyncrasies where they have very smooth pans and zooms from using camera dollies, and also they tend to film in empty-office-building environments, while US humanoid labs have these big purpose-built testing grounds. I think these two filming choices trip a lot of people’s AI video detectors, but if you are a bit more AI literate you can clearly see persistence and physics in the footage that Sora and Veo et al have not yet mastered. Clearly, when they do have these things mastered, people are going to have even more ammunition to claim that any footage showing a capability that they don’t believe in is hoaxed.
It’s also not totally fair to give this as an example of people denying AI capabilities when they’re just saying it’s hoaxed with a different type of AI. But the subtext behind all of these claims is that generating video is way less impressive than making a robot actually do kung-fu.
This phenomenon is pretty weak evidence for capability denial developing. I don’t think there is strong evidence for either side right now—I could just as easily find threads of “general public” talking about AI taking jobs or x-risk. I think it will be important to keep an eye on this balance.
I think that the specific way AI has developed fuels denial. I can imagine a world where AI becomes extremely good at flipping burgers or driving cars well before it learns how to write software or detect cancer. In that case, I think it’s a lot harder to deny its achievements. But in our world, a lot of AI’s greatest achievements take context to understand, like protein folding or playing board games. Even when AI does master burger flipping and driving, because of how things developed at first there’s a sort of lingering distrust.
Something unhoaxable and easily understandable by everyone that we do already have is the ability to speak human language, and I think it’s the main or only reason that a lot of people do generally believe in AI capabilities.
There are all sorts of other un-hoaxable capabilities. The problem is, they have to be widespread in society outside of labs, and also we’re just still pretty far from most of them. Even in extremely controlled environments, humanoid robots can do like 10% or less of the tasks that an average barista can (maybe that’s even an overestimate!). Which means you’re not seeing one in Starbucks anytime soon.
When those unhoaxable capabilities do come online, I’m not sure that they will have that much of an impact on the general distrust of AI capabilities, if it’s already firmly entrenched. The distrust will just recede to the next area of capabilities.
In other words: Even if public-access AI capability (think free chatGPT) stays only a few months behind frontier capabilities (as today), agents living in computers won’t necessarily squash capability denial even if they’re very intelligent. It will just become accepted and acknowledged that screens can think for themselves now. This would certainly weaken denial somewhat, but it would also enhance the contrast between human and AI abilities in other areas, like robotics, where we are still very far from public-access capability that can really impress. And when we do get there, will it be enough to change a strong public sentiment of denial (if one exists), or will it just become paradoxically normalized and acknowledged without making much of a dent? I think we’re already seeing this disconnect at some level—I would’ve expected the current abilities of free LLMs to change public opinion way more than they actually have. People can treat language models as oracles and also be in capability denial.
Note that assuming people are irrational puts any argument on dangerous footing. The main thrust of my argument is that dislike of AI leads could lead to denying its capabilities which leads to disbelief in x-risk arguments. I explain above why I believe dislike could lead to capability denial. But why should it be the case that denial leads to x-risk disbelief, instead of denial leading to fear of dumb grey goo, or something else that is not necessarily tied to logic?
First, I consider this an initial conditions problem. The general public’s opinion has quite a lot of inertia. And the general public is generally unwilling to seriously entertain AI x-risk. The needle has moved in recent years, which is very good, but not by a large amount. If capability denial develops under these conditions, it feels much more likely to me that it pushes the needle back in the other direction, and these two distinct phenomena become linked and self-reinforcing.
Second, for intelligent adversaries in general, smart is scary, and dumb is not. Believing that something dumb could end the world has significant “emotional potential energy”, it just doesn’t feel right.
It’s difficult and error-prone to anticipate the development of beliefs that are grounded more in sentiment than logic. But in this case, it’s very important that we try.
How could we react?
No matter how I look at it, capability denial seems to me like a very bad thing that we must try to prevent and, if it is progressing, reverse. It destroys a main assumption of most x-risk arguments, which could directly lead to extinction.
If this belief becomes common, it seems like it would reduce pressure on politicians to regulate AI, reduce pressure on labs to research and deploy responsibly, and imply that the entire field of safety and alignment research is just a farce.
I think there’s some cases where a person who dislikes and denies the capabilities of AI would want them to be regulated more, like if they’re concerned about the water or energy use. But this feels like a relatively small slice of the whole.
If someone has a little sliver of capability denial, I think x-risk arguments can end up actually reinforcing it. These wackos think that AI is going to end the world when it can’t even filter my emails? Maybe AI researchers are even dumber than I thought. I think the idea that AI is very capable naturally leads to asking the question, where does it cap out? which leads to someone discovering the idea of x-risks for themself.
The disconnect where the general public expects AI to do bad things, and the AI-sphere is undecided or expects good things, is somewhat problematic. It seems easier to convince people of AI capability if you agree with them that it sucks and is bad. Evil + capable = scary, neutral + capable = nothing emotionally interesting.
Notice that I’m talking almost exclusively about the “general public” who are not very well informed about AI, not researchers or academics or whatever. This seems like a phenomenon that uniquely affects poorly informed people. I also think there’s good general reasons to target normal people these days (although be warned that the author has since updated away from it somewhat).
The main assumption of all x-risk arguments, that AI can become unboundedly capable, is one that rationalists have thought about a lot. However, I’m kind of surprised by how little we have apparently thought about things that might lead someone else to fault that assumption. I did find one post specifically examining capability denial but it’s from 2 years ago, quite short, and mostly authored by GPT-4. Are there other assumptions that go into x-risk arguments that we should be similarly examining the reception of? Probably. None off the top of my head.
I was unable to find any polling on this phenomenon. I’m sure there has been some already that addresses this tangentially and I’d love to get my hands on it. I also think it would be a good idea to have a question in future polls like “To what extent do you believe current AI abilities are exaggerated or falsified?”
I feel like labs exaggerating capabilities could be one of the main things driving this phenomenon. Even Anthropic (usually the more responsible sibling) heavily exaggerates. But I’m not sure there’s much anyone can do about this, because labs as organisms need exaggeration like plants need sunlight—forsaking it is surrendering to the competition, it means you lose the talent and the investors. Still, it’s extremely bad that labs are doing this, it’s almost purposeful normalization of capability denial.
The strange thing about capability denial is that it might not affect timelines much, or at all, while greatly affecting outcomes. If labs and investors know capabilities are real, then they’re not going to care about it. Maybe they lose some revenue from the lower amount of public-facing AI use, maybe this spooks investors somewhat. But in some ways labs might prefer capability denial, because it means less scrutiny of what they’re doing, less reporting and safety requirements, because policymakers just aren’t afraid of AI at all.
I do think the more general anti-AI backlash will probably slow things somewhat, as argued here. Maybe there’s a good claim to be made that social factors have been of comparable importance in the adoption of most new technologies?
I don’t have any great ideas for how to stamp out the sparks of a conspiracy theory and there’s probably no magic bullets. We should also prepare for the outcome where they can’t be stamped out and capability denial is a commonly held belief. I haven’t yet put much thought into this eventuality. It does seem like rationalists have to be ready and waiting to latch on to any breach or mishap, especially if it injures or kills people, to promote the capability and simple power of AI. But we already knew that.
If there is any level of bubble pop for AI, it seems even more important to emphasize that AI is capable. Funding levels going off a cliff is an easy justification for capability denial.
Thanks to Thane Ruthenis for reviewing a draft of this post.
(I’d appreciate thoughts on writing style as well as content, I’ve not yet done much longform essay writing.)
There are lots of potent memes in this space, which I see invoked often on reddit threads. Some examples:
> Calling it “AI” is marketing bullshit that I will never forgive. It’s incredibly frustrating how few people see that.
> they are and always have been stochastic parrots
> Its not intelligent. It understands nothing. It’s a sophisticated search engine that can produce/create content from data sources.
> The word “AI” continues to confuse people. It’s simply a marketing term no different than Tesla’s “Full Self Driving.”
> A regurgitation machine.
> It is simply advanced text prediction
Can we get those memes to mutate to still be derisive and mocking, but no longer imply the AI isn’t strong? Seems easier than mutating away the derision. Would need to still embed the disapproval or it won’t stick
Another one is the imminent prediction that AI progress will soon stop or plateau because of diminishing returns or limitations of the technology. Even a professor I know believed that.
I think that’s a possibility but I think this belief is usually a consequence of wishful thinking and status quo bias rather than carefully examining the current evidence and trajectory of the technology.
I think this is just because currently AI systems are viscerally dumb. I think almost all people will change their minds on this eventually. I think people are at greater risk of forgetting they ever believed AI is dumb, than denying AI capabilities long after they’re obviously superhuman.
not if it’s always idiot-savant in some way
I’m not sure how to even engage with this category of claims because they totally ignore the obvious question that’s automatically implied when you assert them, that being how exactly human intelligence differs from whatever term you use to say that LLMs don’t have real intelligence.
Maybe belief in some of these terms is another good poll question. I suspect all of them are only going to get more common and dogmatic.
Pretty much anything you point out to these will be met with derision unfortunately. From the same thread (on /r/technology) as the above samples, and in response to reasonable comments:
> Jesus, you are not the brightest bulb are you?
> There’s always someone who wants to argue that LLMs have intelligence and aren’t simply designed to respond in specific ways.
> Truly a braindead take. Congrats
> All those words to, once again, reiterate that these things are incredible machines for making correlations, but not for establishing causations 🙄
> This is nonsense
Seeing “stochastic parrots” repeated by people who don’t know what “stochastic” is will never stop being funny.
I have noticed two important centers of AI capability denial, both of which involve highly educated people. One group consists of progressives for whom AI doom is a distraction from politics. The other group consists of accelerationists who only think of AI as empowering humans.
This does not refer to all progressives or all accelerationists. Most AI safety researchers and activists are progressives. Many accelerationists do acknowledge that AI could break away from humanity. But in both cases, there are clear currents of thought that deny e.g. that superintelligence is possible or imminent.
On the progressive side, I attribute the current of denial to a kind of humanism. First, their activism is directed against corporate power (etc) in the name of a more human society, and concern about AI doom just doesn’t fit the paradigm. Second, they dislike the utopian futurism which is the flipside of AI doom, because it reminds them of religion. The talking points which circulate seem to come from intellectuals and academics.
On the accelerationist side, it’s more about believing that pressing ahead with AI will just help human beings achieve their dreams. It’s an optimistic view and for many it’s their business model, so there can be elements of marketing and hype. The deepest talking points here seem to come from figures within the AI industry like Yann LeCun.
Maybe a third current of denial is that which says superintelligence won’t happen thanks to a combination of technical and economic contingencies—scaling has hit its limits, or the bubble is going to burst.
One might have supposed that religion would also be a source of capability denial, but I don’t see it playing an important role so far. The way things are going, the religious response is more likely to be a declaration that AGI is evil, rather than impossible.
Small note: negative consensus seems to be concentrated in the Anglosphere
In my role as a volunteer for PauseAI, I regularly talk to college students and random people on the street about AI risk and how we might mitigate it. The #1 objection I receive is that AI won’t be very powerful. I think we have underinvested in effectively communicating the capabilities of existing AI systems.
(The #2 objection is that there is nothing we can do about it. These are also the two most common objections I see in YouTube comments on AI-risk-related videos.)
Additionally (very frequently online and only rarely in person), I hear the claim that everyone who claims AI could be existentially dangerous (and who would otherwise be credible) are lying in order to hype AI companies and make money. I don’t have any data (even anecdotal) about whether providing very strong evidence against this claim tends to change the interlocutor’s mind. However, I do think that most people who make this claim are not engaging in conspiratorial thinking, and are rather merely ignorant of facts that if accepted would force them to either change their mind or knowingly accept a conspiracy theory.[1]
At the same time, I should point out that I have noticed a vibe change over the course of this year, such that people tend to be more willing today to engage with x-risk ideas without dismissing them outright. X-risk has had some time to enter into the mainstream via various news stories, and more people have interacted with AI tools that impressed them. (This shift is relative rather than absolute, so YMMV.)
For many people it may be useful to present the facts of current LLM performance in math and coding competitions and on benchmarks with held-out test sets, but the general public has very little concept of what those things mean. (“Of course it can do math and write code; it’s a computer!”) The things I expect to be more compelling are things like: “AI has designed and created a working biological virus from scratch”[2] and “publicly available chatbots from last year outperform almost all expert virologists in their own subspecialties at troubleshooting wet lab steps relevant to creating a bioweapon.”[3] Let me know your thoughts, and if you are aware of other pieces of evidence that are simultaneously shocking, scary, and easy to communicate.
Facts like: “about half of all published AI researchers say there’s a significant chance of human extinction from AI this century”, “the 2 most cited scientists in the world helped invent modern AI, and they are very worried about this”, “independent and academic AI researchers are also concerned about this risk, along with industry insiders”, “whistleblowers have risked millions of dollars to warn the public about this,” and “all the CEOs of the top 4 AI companies talked about extinction risk from AI years before any of those companies existed.”
https://www.washingtonpost.com/opinions/2025/09/25/artificial-intelligence-advance-virus-created/
https://www.virologytest.ai/
I’d make the case that instead of using this frame to model how non X-risk people see AI, it’s better applied as a way to model what the rationalist community looks like to them. A small group of people with an extreme, fringe belief that spends most of its time generating evidence for that belief. People aren’t going off the epistemic validity of that evidence, they’re going off their gut feeling that it’s weird for a small group of people to be so concerned in the absence of a lot of social proof.
With that in mind, I don’t think the public messaging strategy should focus heavily on proving AI is dangerous. The rationalist community spends a lot of time arguing that AI powerful → bad. But the public mostly already agrees with that conclusion, they just got to it from a different premise (job loss, environment, stifling of the human spirit, fear of change, etc). I think it’s important to strategically validate some of those—you really are going to lose your job!—and make the connection between losing your job and being very capable. While they might not end up with a perfect policy picture, they don’t need one. They just need to be worried enough to add pressure to their representatives, who can be targeted more deliberately.
I’ve seen arguments that people should disbelieve AI capability because it will cause the alleged bubble to pop faster. Arguments that AIs are capable are often seen by ai-hater-ai-doubters as advertising the AI. see also recent discussions
AI denial will almost certainly exist but i think it’s unlikely AI denial becomes a big thing, in the same way that flat erth denial is basically irrelevant in the world.
I hope that’s the case but feel there are drastically more and better reasons for people to believe in it compared to flat earth.
I could see a future where the labs and their corporate clients indirectly support capability denialism by disguising AI work as work by humans. Think catfishing but with AI on the other end.
Feeling frusterated while on hold? At least you know “Tiffany” with her sweet Southern accent is on the case.
Got laid off from your job? It looks like you’ve been replaced by a new applicant named “Sophie” who has a very professional LinkedIn pic.
Feeling suspicious about the number of layoffs you have heard about through the grapevine? You’re AI suspicions may be soothed after reading dozens of Reddit threads written by earnest Redditors about skill development and the laughability of the claim that AI is replacing you.
If this is our fated timeline, it would be hard to completely hide the fact that AI is booming (it seems like some stock market movement should indicate how much value AI is creating). But this strategy could leave the public in the dark while the leading AI company can focus on monopolizing without dealing with such trivial matters like AI safety and human survival.
One note: This is the most conspiratorial of all timelines. We will need to brainstorm good indicators if we end up in this timeline, because lizard people logic is not persuasive (“not seeing X is exactly what we would expect to see with the lizard people in charge!”).
EDIT: typo.
I suspect that one significant source of underestimating AI impact is that a lot of people had no good “baseline” of machine capabilities in the first place.
If you’re in IT, or as much as taken a CS 101 course, then you’ve been told over and over again: computers have NO common sense. Computers DO NOT understand informal language. Their capability profile is completely inhuman: they live in a world where factoring a 20-digit integer is pretty easy but telling whether there is a cat or a dog in a photo is pretty damn hard. This is something you have to learn, remember, understand and internalize to be able to use computers effectively.
And if this was your baseline: it’s obvious that current AI capabilities represent a major advancement.
But people in IT came up with loads and loads of clever tricks to make computers usable by common people—to conceal the inhuman nature of machines, to use their strengths to compensate for their weaknesses. Normal people look at ChatGPT and say: “isn’t this just a slightly better Google” or “isn’t that just Siri but better”. Without having any concept of the mountain of research and engineering and clever hacks that went into dancing around the limitations of poor NLP and NLU to get web search to work as well as it did in year 1999, or how hard it was to get Siri to work even as well as it did in an age before GPT-2.
In a way, for a normal person, ChatGPT just brings the capabilities of machines closer to what they already expect machines to be capable of. There’s no jump. The shift from “I think machines can do X, even though they can’t do X at all, and it’s actually just Y with some clever tricks, which looks like X if you don’t look too hard” to “I think machines can do X, and they actually can do X” is hard to perceive.
And if a person knew barely anything about IT, just enough to be dangerous? Then ChatGPT may instead pattern match to the same tricks as what we typically use to imitate those unnatural-for-machines capabilities. “It can’t really think, it just uses statistics and smokes and mirrors to make it look like it thinks.”
To a normal person, Sora was way more impressive than o3.
I belong to a private Discord full of geeky friends (as one does), and I constantly see this pattern you describe, where smart people dismiss AI risks because they dismiss AI capabilities. This takes several common forms:
Pattern-matching AI hype to crypto hype. Partly, this happens because some of the same arguably sociopathic VC scam artists are up to their elbows in both. “Arguably sociopathic scam artists” is sometimes a judgement made based on people’s prior social-graph proximity to the VCs in question.
An odd argument that “Of course the frontier labs say that their product has a 25% chance of causing human extinction. It’s a good sales pitch!” For me, this feels like a combination of a genuinely shrewd observation and a total failure to notice the giant pink elephant in front of them?
Focusing on the 20% of the time where AI fails at something trivial, and ignoring the 80% of the time where the dancing dog just pulled off 32 clean fouettés in a row. Like, the 80% of the time where Sonnet 4.5 nails it is the warning. When it stops failing the other 20% of the time, that’s potentially game over for the human race, you know?
A tendency to occasionally play with an AI model and then cache the worst experience out of 5 for about 12 months.
An overexposure to slop and to Google’s awful search AI.
The only way I’ve found to occasionally get someone over this hump is to give them a tool like Claude Code and let them feel the AI.
But the problem is, once you convince someone that AGI might happen, a disturbing number of people fail to really think through the consequences of really doing that. Which is perhaps why so many AI safety researchers have done so much to accelerate AI capabilities: once they believe in their bones, they almost inevitably want to build it.
So I constantly struggle with whether it actually helps to convince people of existing or future AI capabilities.