It’s about human understanding, to be sure, but I take it to be showing that rule-following (AI) is insufficient to produce it (ie, understanding such as humans have, or AGI).
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Replying to @Plato4Now @NegarestaniReza
You could say it’s an argument against GOFAI, and in favor of machine learning
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Replying to @SimonDeDeo @NegarestaniReza
I’m almost with you. I’d say it gives an argument in favor of machine “learning,” while showing that such learning could not be understanding.
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PS the learning that they do these days is super underdetermined—there’s no teacher.
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Replying to @SimonDeDeo @NegarestaniReza
Right. I don’t think understanding requires a teacher. If it did, that would preclude (scientific) advancement. The problem with machine “learning” is not that there’s no teacher but that there’s no understanding.
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I think machine “learning” is like the way a virus “learns” to infect a host. When it succeeds, and accomplishes the task, it does so through a complex mechanism, but not by understanding.
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Replying to @Plato4Now @SimonDeDeo
Since Kant we have a semblance of comprehension as how even the faculty of understanding can be functionally decomposed. It is a qualitatively exceptional faculty precisely because it is composed of myriad multi-level functions which can be not that different from a virus/prion.
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Complex systems are the products of structural and statistical complexity, generative entrenchment and dynamic constraints.
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Replying to @NegarestaniReza @SimonDeDeo
I’m happy to accept that. I’m not sure what each of those terms mean, but you’ve written a book about it so I defer! What I can’t accept is that the understanding is a complex system. Any complexity would spoil its claim to knowledge.
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I agree, the term complexity is free-floating. By that terms I only mean scale-, level-, context-sensitivity a al Remo Badii and James Ladyman but with some caveats.
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