This book (from a philosophy professor AFAIK unaffiliated with any AI company) makes what I find a pretty compelling case that it's correct to be uncertain today about what if anything an AI might experience: https://faculty.ucr.edu/~eschwitz/SchwitzPapers/AIConsciousn...

From the folks who think this is obviously ridiculous, I'd like to hear where Schwitzgebel is missing something obvious.

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anonymous908213 4 hours ago | parent | next [-]

At the second sentence of the first chapter in the book we already have a weasel-worded sentence that, if you were to remove the weaselly-ness of it and stand behind it as an assertion you mean, is pretty clearly factually incorrect.

> At a broad, functional level, AI architectures are beginning to resemble the architectures many consciousness scientists associate with conscious systems.

If you can find even a single published scientist who associates "next-token prediction", which is the full extent of what LLM architecture is programmed to do, with "consciousness", be my guest. Bonus points if they aren't already well-known as a quack or sponsored by an LLM lab.

The reality is that we can confidently assert there is no consciousness because we know exactly how LLMs are programmed, and nothing in that programming is more sophisticated than token prediction. That is literally the beginning and the end of it. There is some extremely impressive math and engineering going on to do a very good job of it, but there is absolutely zero reason to believe that consciousness is merely token prediction. I wouldn't rule out the possibility of machine consciousness categorically, but LLMs are not it and are architecturally not even in the correct direction towards achieving it.

	▲	kalkin 4 hours ago \| parent \| next [-]
		He talks pretty specifically about what he means by "the architectures many consciousness scientists associate with conscious systems" - Global Workspace theory, Higher Order theory and Integrated Information theory. This is on the second and third pages of the intro chapter. You seem to be confusing the training task with the architecture. Next-token prediction is a task, which many architectures can do, including human brains (although we're worse at it than LLMs). Note that some of the theories Schwitzgebel cites would, in his reading, require sensors and/or recurrence for consciousness, which a plain transformer doesn't have. But neither is hard to add in principle, and Anthropic like its competitors doesn't make public what architectural changes it might have made in the last few years.
	▲	asfsadfuyrer 3 hours ago \| parent \| prev [-]
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KerrAvon 4 hours ago | parent | prev [-]

It is ridiculous. I skimmed through it and I'm not convinced he's trying to make the point you think he is. But if he is, he's missing that we do understand at a fundamental level how today's LLMs work. There isn't a consciousness there. They're not actually complex enough. They don't actually think. It's a text input/output machine. A powerful one with a lot of resources. But it is fundamentally spicy autocomplete, no matter how magical the results seem to a philosophy professor.

The hypothetical AI you and he are talking about would need to be an order of magnitude more complex before we can even begin asking that question. Treating today's AIs like people is delusional; whether self-delusion, or outright grift, YMMV.

	▲	kalkin 4 hours ago \| parent [-]
		> I'm not convinced he's trying to make the point you think he is What point do you think he's trying to make? (TBH, before confidently accusing people of "delusion" or "grift" I would like to have a better argument than a sequence of 4-6 word sentences which each restate my conclusion with slightly variant phrasing. But clarifying our understanding of what Schwitzgebel is arguing might be a more productive direction.)