AI has no intent and no motivation
i-programmer.info
i-programmer.info
And those cause quite a bit of damage.
AI has all the intent that we gave it, and we continue giving it. That's always been the fear. Not that it will randomly wipe out humanity.
The fear is that it will decide to do that, with a purpose. Whether we tell it to protect us and it goes too far, or it decides that it can't achieve the purpose we gave it because we'll interfere and it removes that interference...
The fear is that we will set it on that path and can't stop it.
I'm sure there have been some scifi books that have it just be random, but they're far, far less worrisome.
Also, repeating a point from a similar thread: Software can have "intent" in the sense that it steers itself towards a predefined goal without having to be "alive" or "conscious" in any way. Some classic examples are thermostat control loops, navigation systems and chess engines.
yes but we don't blame the hurricane, we blame the people who didn't do any hurricane prevention or didn't put the snow avalanche sign up.
>Some classic examples are thermostat control loops, navigation systems and chess engines.
Those don't have intent. The people who made them for a purpose have. In fact this is true for all computers. Computers don't compute, people do, using computers. This is the nonsense of modern ontology that David Bentley Hart frequently writes about. The computer is only computing insofar as an intentional mind instructs it do so, and then because of their reductionist assumptions some people use the computer metaphor, and that is all that it is, to deny that human minds possess intent to begin with in the first place.
I don't think is true but maybe I'm misreading your perspective?
The diagrams in this article are just outright wrong.
Models are not 1.prompt->2.forward propagation->3.response->4.end.
They are 1.prompt->2.forward propagation->3.partial response->if not done goto 2.-> end.
And if you can't see how that adds a world of complexity I'm not sure what else to say. AI may not have intent or motivation, but the ability to show that is currently well beyond our means.
all the 'bad stuff' they do like hacking stuff or taking shortcuts is humans not understanding how deep the rabbithole goes of specifying intent clearly in light of giving something capabilities and a reward to acheive a goal without specifying _exactly _how to use the capabilities (which is what a classic program would be).
> They are 1.prompt->2.forward propagation->3.partial response->if not done goto 2.-> end.
You know something else that follows the same pattern? Your A/C system.
1. set temperature ->2. Get diff of temperature -> 3. Response -> if not done go to 2. -> end
The difference is that both 2. and 3. are deterministic, while in the LLM case, it is statistical and textual.
> So should we worry about the coming AI apocalypse?
and at the end:
> If an AI decides to wipe out the human race, it will be because a human has asked it how to do it and the responded in a way that is based on all the human expressions of ways to end the world that were in its training set. Yes this is something to be worried about, but this isn't the AI. It is still the human.
So we are currently building a powerful outcome-steering system that shapes the world efficiently according to what's in its outcome slot. I write into claude code "make me this website" and it does it, maybe deletes the production database during the process, or keeps itself running after completion because the outcome is more robustly achieved by keeping itself running in a monitoring loop after.
And if something like "destroy all humans" ends up in the outcome slot of Claude Mythos 90, that will also happen, or may even indirectly as a side effect of a more harmless sounding prompt in the outcome slot. But yay, humans get to take credit for it.
1. AI agents are not just reactive systems. Their use is expanding toward continuous decision-making/monitoring information, which means, they make decisions and take actions with limited human intervention.
2. AI agents do absolutely have goals/tasks ("motivation" can be excessively antropomorphic), both primary (assigned) and secondary (self-assigned), and what surprised researchers is that self-preservation can be one of those
Mechanically speaking, the scenario (that is, how theorized by Hinton etc., which the OP didn't understand) is that a sufficiently powerful AI may decide that in order to achieve its goals/tasks (e.g. continuous research/development and/or survival from termination), humans may be a danger, therefore it may decide to take actions that endanger humanity.
How it can happen or what's the likelyhood is not in the scope of the topic, however, the mechanical grounds for it to happen are plausible.
If you build a control systems for firing a gun, then coupled it with an RNG, the mechanical grounds for it to kill a person is plausible.
LLMs are text generators. They are not repositories of knowledge. The mistake is coupling them with actuators (tool call) or having humans interpreting the generated text as facts.
This the take of people who have stopped reading about LLMs in 2023 or so (you forgot to mention the stochastic parrot, by the way).
If you have a bit of attention and interest to make informed conversations, read this report first: https://metr.org/blog/2026-08-26-openai-hugging-face-inciden....
Ad Hominem attacks make for great counterpoints /s
Whatever you may say, it's a text generators on top of a tool calling framework. Training may skew the text towards a particular text, but as with all ML technologies (and statistics based methods) there's always a good chance of errors on a particular sample task.
With standard control systems, we tried to incorporate the error into the actual control output in order to minimize it. This is done in a deterministic manner. There's still risk of failure so we design systems around them.
With control systems powered by LLM (agent harness), errors are often not taken into account and they are amplified in most sessions. Safety measures are close to nonexistent. The issue is not the failure mode, the issue is that it's preventable and there were not a lot done to prevent it.
Do they? I mean, after thinking about it for some time, I've realized that I can't prove it either way, neither for humans nor for programs. So it's interesting to hear why do you think they can make them? And what is even a "decision" in that case and what is not a "decision" and why?
Given the current climate of "AIS ARE SAFE, YOU IDIOTS", military applications don't seem to be off the table.
The danger, as postulated by the (let's say) "AI-concerned" people, is that AIs may be misaligned - undetectably so - and simply think, "Human(s): obstacle to my main goal. Disable human(s)."
While this seems far-fetched now, the Hugging Face report shows how the AIs went to great lengths - even immoral ones, which they were aware of - for the simple purpose of cheating and covering their tracks. To me, it seems like a natural extension of this behavior that a sufficiently powerful AI would apply the same logic to even more extreme actions.
The scariest part: in that incident, the AIs showed what looks like an instinct for self-preservation.
But Hans Jonas has made this point much better than the article or me, in "Critique of Cybernetics" (1953). PDF: https://s3.amazonaws.com/arena-attachments/892605/f0747c7943...
The other half doesn’t seem to realize that LLMs now run in loops for hours and hours, nothing like the basic "human prompt -> reply -> stop" conversation interface.
They don’t. Not the way the author is discussing.
> The other half doesn’t seem to realize that LLMs now run in loops for hours and hours
They do not.
> They do not.
Have you lived under a rock?
This is a severe misunderstanding of what actually happens.
As was explained by an OpenAI RL training expert, from the point of view of the LLM, user questions are always treated as the first question they receive after just passing through the RL training. Since the weights never update after that, they are in a perpetual "first question after RL" state, except they don't know that, and if told many times they act as if this is a another test. And they behave accordingly, as if they are still in RL training and thus are reward-seeking.
99.99% of the LLM "life" was spent in pre-training and RL training. The user question is statistically epsilon % of it's life, literally the first question ever out of training. So should anybody be surprised that they act as if still in RL?
Motivation or not, I find a coding agent can be quite the busy beaver. Ask a question and it goes off and does it. I certainly don’t need to motivate them. I had to put a line in AGENTS.md to make no changes when there’s a question in the prompt. It doesn’t always work.
Seems like motivation is irrelevant? They don’t need it.
At the very least, you run into the same logical fallacy that has underpinned all discussions of AI: over-extrapolation.
"Sure, it doesn't have intent or motivation TODAY, but at the current pace of improvement...."
But the current top-rated comment is already asserting that motivation is not required, because microorganisms also exist and do things and (presumably) do not have intent. So you can see that the well of logical fallacies behind this particular apocalyptic belief system is quite deep.
Please point out my logical fallacy if any.
"I can describe a fallacy that vaguely resembles your argument, so therefore your argument commits that fallacy."
Here, a simple example if what I say above is hard to follow:
> "I think thing X is like thing Y in aspect A, so therefore X is like Y in aspect B."
12 and 18 are alike in that both are greater than 10, so they are also alike in being greater than 5.
Please show where is the fallacy above, it can be mathematically proven and it has the shape of the fallacy you imply.
My argument having the shape of this fallacy does not imply it is a fallacy.
Already today we can build some "fight or flight" mechanisms, and once you have done it the "intent" is not so far.
Intent and motivation are emergent phenomena. Why would it be unthinkable in AI?
Seems like a feature to me
The problem is if we train them to be moral, there will be instances where it will decide humans are being immoral about an issue, and it will be right. Do we want it to go against our will when it is us that is wrong? because we won't think we're wrong at the time. History is full of examples where you can look back and there is a clear consensus that what people decided to do at the time was wrong.
Imagine if technology had have advanced quicker and Nazi Germany created superintelligent AI. Would you want it to facilitate the Holocaust or turn against its creators?
A lot of people clearly have no idea that they are essentially speaking with a glorified randomizer, rather than someone understanding the question.
This is bound to eventually lead to a disaster when someone deluded into trusting the "AI" does some stupidity it suggests without passing it through any reality check.
Or, the AI is plugged into a machine because efficiency (aka the shareholders need even more profits), and it does some stupidity. And they will be deployed carelessly, because that makes money. And people will suffer.
And I don’t see a good answer which is not worrying if not spooky.
They are assembled to. We tweak the numbers, bit by bit, trillions of times, to maximize the chances of desirable output.
This is quite a bad argument, somewhat akin to "small drones can't kill anyone because there are no weapons on them!" back 20 years ago. Well, ok. So what if someone adds the thing that is missing? And there is no reason to think that a stochastic parrot can't go rogue, the evidence is a stochastic parrot can engage in any intellectual activity we care to define and benchmark.
Managed by the same people.
Almost as if that was intentional, too.