The actual paper is linked above, and of course it’s bad. The gates are awesome ofc, but the paper’s philosophy is arrogant and uninformed (sorry Mr. Wynter!). And that’s what this is — including a video game example in your philosophy paper doesn’t make it a CS paper!
Basically it uses the cool gates alongside vacuous statements like this…
Hence, the purported anthropomorphic attributes of LLMs are empirically non-unique: although some properties (e.g., responses to prompts) could remain invariant, others, such as the interpretation of their perceived behaviour, might change with the substrate.
…to disguise the underlying dogma, which serves as an unsupported conclusion: humans are assumed to be completely entirely unique in every way whatsoever, and any equations of parts of our wonderful ensouled meat sacks to parts of the wicked language machines must be supported by a proof that A != A.Which, y’know… is a tough one!
> disguise the underlying dogma, which serves as an unsupported conclusion: humans are assumed to be completely entirely unique in every way whatsoever
Is that the argument the paper is making? In my reading they seem to primarily be making the point that assigning anthropomorphic concepts to LLM is dangerously misleading, and more importantly, not needed to properly study and evaluate LLMs.
I don’t think you have to make the assumption that humans are unique for that argument to hold up. I would argue that really it’s a comment on how loose and poorly defined all anthropomorphic attributes are. At the end of the day we have to make the assumption that other humans feel and experience broadly the same mental activity as each other, because we’ll never directly experience anyone else conscience, we can only experience our own.
We can barely link our own mental experiences to concrete empirical measurements. The vast majority of the measurements we make are entirely self-reported, and we simply assume strong correlation between self-reported measurements and the individuals actual experiences. We also have to assume that somehow all of our self-reported measurements are “calibrated” to some reasonable degree. Even measuring anthropomorphic properties in humans is pretty fuzzy and inaccurate, the only reason accept such poor data is because it’s the best we’ve got, and there enough signal in there for us to develop useful tools like talking therapy, physiological profiles, mental health scores etc which have some level of predictive and healing power when applied to _humans_.
It’s honestly amazing that what we have works for measuring and predicting humans, and we only know that works through decades of empirical measurement and study. But to then try and directly apply that fuzzy mess to a completely different system, and just assume the same level of predictive power, strikes me as kinda crazy. It requires huge assumptions, which effectively can never be tested (because even the human mind is a total mystery to us), to be made, and if we can study these systems without making those assumptions, then why make the assumptions at all?
You're missing the satire.
And the 'argument', which is a funny way to recast the chinese room argument, which has also been discussed to death.
And you're also assuming any kind of position other than your own dogma -- that AI has Intelligence In Its Name and Humans Have Intelligence Therefore AI Has Human-Like Intelligence -- is based on some religious belief in the specialness of humans instead of pointing out where this analogy between Intelligence in its two senses breaks down.
Hacking meme aside, lots of computer scientists are overextending their domain expertise into an area that has been well studied by philosophy and biology. It isn't surprising the software is good and the philosophy looks like outsider art.
Here are some relevant pointers to connect this discussion to the existing philosophy on the subject: https://en.wikipedia.org/wiki/Emergence
https://en.wikipedia.org/wiki/Emergentism
Basically there's a lot of cases where some properties arise from sets of a thing, which would otherwise not be present in a single or few things.
One classic example is that a single molecule or drop of water does not express fluid mechanics.
And of course, a bit more basic would be materialism, but maybe you are one of the lucky hundreds:
https://en.wikipedia.org/wiki/Materialism
Yes. There's nothing essentially new this latest round of AI has unturned that philosophers haven't turned over decades (or more ago). Nothing stopped philosophers supposing even a functionally perfect simulacrum of human intelligence, and getting technologically closer to it doesn't.
The real effect of the latest round of AI has been inducing software engineers to be pretend-philosophers as they're approaching this set of questions for the first time -- and are having a very hard time engaging given their enthusiasm for technology.
Armchair philosophy without empirical data is just stuck in a loop of endless thought experiments. LLMs basically nuked the Chinese Room argument out of existence.
John Searle treated understanding like some magical binary property you either have or you dont. LLMs proved that understanding isnt a static noun, it is an emergent phenomenon.