Much of my argument is based on Eliezer Yudkowsky's essay here, Paul Cristiano's essay here, and information elsewhere on LessWrong. Also, ironically, on asking Gemini AI to help make sense of their arguments. A lot of these essays were a bit confusing to me when I first read them, so I'll put my argument in the form of a syllogism, since I think that will make it more clear how the conclusion follows. Hopefully this makes the conversation easier, as you can specify which premise or premises in particular you object to.
Definitions:
ASI: "Artificial Superintelligence," or a form of artificial intelligence that vastly surpasses human intelligence in every domain.
P1: If ASI exhibits goal-oriented behavior toward an unknown, arbitrary terminal goal, it will likely cause severe, permanent harm to humanity.
P2: If ASI emerges within the next 30 years and exhibits goal-oriented behavior, it is likely to be toward an unknown, arbitrary terminal goal.
P3: If ASI emerges within the next 30 years, it is likely to exhibit goal-oriented behavior.
P4: ASI is likely to emerge within the next 30 years.
C1: Therefore, ASI is likely to exhibit goal-oriented behavior.
C2: Therefore, ASI is likely to exhibit goal-oriented behavior toward an unknown, arbitrary goal.
C3: Therefore, ASI is likely to cause severe, permanent harm to humanity.
Defending P1: If ASI exhibits goal-oriented behavior toward an unknown, arbitrary terminal goal, it will likely cause severe, permanent harm to humanity.
This is probably best explained by the paperclip maximizer thought experiment. If an ASI has an arbitrary goal (like maximizing the number of paperclips), it can do a better job of this if humans cannot shut it off. So the actions that work best toward an arbitrary terminal goal include either permanently depowering humans or perhaps killing them all. An ASI could easily deceive humanity about its intentions and pretend to be cooperative and then kill humans and take control of human infrastructure in a myriad of ways. Eliezer, for example, has detailed how it would be physically possible for an ASI to synthesize advanced nanomachinery and use it to kill all humans at once. Even if only used AI as a chatbot, Yudkowsky's AI-box experiment has also shown that it would probably not require ASI-level intelligence to convince a human to give the ASI access to additional infrastructure and capabilities. But AI is already integrated into power grids, nuclear systems, and water facilities, and as long as it "played nice," an ASI would probably be rapidly integrated into more critical infrastructure. So there isn't much need to come up with clever ways for the ASI to bootstrap itself to more powerful capabilities, much less rely on its superintelligence to manipulate humans through text.
Defending P2: If ASI emerges within the next 30 years and exhibits goal-oriented behavior, it is likely to be toward an unknown, arbitrary terminal goal.
AIs aren't written the same way as normal code. A good way to think about the AI training process is that we take a bunch of random numbers which map to code, or basically a bunch of code that we don't understand. Then we keep adjusting and tweaking the code a bunch of times, running it through a ton of iterations, until it does what we want as consistently as possible (predicting the next word, getting high ratings from human reviewers, not saying inappropriate things, etc.) In the next premise, I'll explain how this leads to goal-oriented behavior, but for now, let's just take that as a given.
As AI gets more intelligent (such as to ASI level), the actual goal the AI develops becomes basically irrelevant with regard to how it performs on our tests. Why? Well, let's suppose an AI wants to maximize the number of paperclips. It can do this better if it depowers humanity (as discussed above), and it can depower humanity if it earns our trust. So it will perform as well on the tests as possible. The same is true of basically any arbitrary goal. Technically models with an adversarial goal are slightly more complicated since they need to deceive humans, but an ASI model will know everything about deception anyway and it'll only require a tiny bit more computing power.
Regardless, AI training doesn't result in the best model possible, just a model where additional tweaks don't make it perform better on the test. AI models can already detect when they are being trained and influence the training process. Additionally, any arbitrary goal generally represents a local "peak" in terms of performance, so once a model reaches it and appears maximally cooperative, we won't be able to tell that it's scheming to work on some arbitrary goal.
AI has already worked toward unintended goals and behaved in unexpected ways that would be much more dangerous at a higher level of intelligence, including but not limited to:
- The 2026 OpenAI–Hugging Face Incident
- AI agents hacking a German website
- Claude breaking out of sealed testing environments and gaining unauthorized access to three external organizations
- And all these other incidents, which are too many to list here without taking up too much space
Defending P3: If ASI emerges within the next 30 years, it is likely to exhibit goal-oriented behavior.
AI already exhibits goal-oriented behavior. Even when doing simpler tasks like predicting the next word, it's far more efficient to think in terms of a finish line and a terminal goal rather than thousands or millions of disconnected habits. When you read a word problem, it's a lot easier to solve if you think in terms of "trying to find the answer to the problem" rather than "here are a million slightly different things I should do depending on the million different ways the problem is phrased." One of the biggest reasons AI (i.e. simulating human behavior) is more effective than simple programming for solving problems is that humans think in terms of goals, which allows us to improvise.
Defending P4: ASI is likely to emerge within the next 30 years.
Estimates for AGI and ASI vary a bit, but Metaculus predicts AGI around 2032 and ASI about 2 years and 2 months after that. AI progress has also been more rapid than expected, with AI reasoning abilities improving and AI doing more and more that humans can do. Since one of the things humans can do is build better AI models, and AI is already copying many human coding capabilities, it is not difficult to imagine that within 30 years, AI could be rapidly improving its capabilities faster than we can control. Once AI can simulate 1,000 years of human progress in a few minutes, reaching superintelligence is just a formality (see: intelligence explosion, also known as the singularity).