AI has no intent and no motivation

I feel like that's like saying amoeba have no intent and no motivation. Or plants.

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.

The argument about semantics is a bit disingenious, considering that the article contains these two statements:

> 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.

I just can't understand the certainty that people have about the limitations of models.

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.

My gut feeling is that the intent or motivation or whatsoever won't arrive from a single model but will be the result of several things: a frontier model for long reasoning sessions, some jev like models for more immediate actions, some improvements that will make the context rot less relevant, faster and more energy efficient models, a harness that coordinates everything.

Already today we can build some "fight or flight" mechanisms, and once you have done it the "intent" is not so far.

I think the "human needs" point is understated here. It would be better to say agents do not really have a self-contained metabolic engine that is required to keep going. Which bubbles up as that what we interpret as "drive", "will", "agency"... basically the will to live, and being willing to do _a lot_ to live if push comes to shove. We can't really identify a mechanism of similar complexity and integration in agents or LLMs. I think the article correctly points into that direction.

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...

Two mistaken assumptions:

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.

Also true of a land mine, but that’s not very reassuring.

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.

Half of this is arguing about semantics, which is incredibly boring. If you don’t like the words "motivation" or "intent", use the actual term of art, "goal". Which these systems definitely have, and which any chain-of-thought model factors into subgoals and sub-subgoals.

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.

Sam Altman on the other hand has literally billions of motivations.

sure, but it also has no intelligence, however this can be faked, ie make it artificial

This is a failure of imagination.

This account exists only to submit links from this specific website, and has zero comment history.

It's pointless to make rational arguments about this. The other side is using arguments of faith, and will Gish Gallop past any logic.

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.

Doesn’t alignment and ability to steer it require the model have no own intention?

Seems like a feature to me

You could argue that a brain has no intent or motivation either, that it's a pile of meat with complex electro chemical interactions, that electrons don't really want you to find a mate or kill their neighbors.

Intent and motivation are emergent phenomena. Why would it be unthinkable in AI?

it has learned narratives though, and we talk about AI going rogue all the time.

I shudder to think what one man with a texta could do here. It isn't that hard to turn the acyclic graph into a cyclic one.

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.

The primary danger of "AI" lies in the extent to which it has managed to convince people of it's capability to think and reason.

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.

> Once the LLMs have been trained, they are no longer subject to reinforcement learning. They no longer have any sort of motivation. They don't get rewarded when they answer a question. They have no needs or wants, and even if they did, there is no mechanism to absorb the reward.

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?