Comment by glenstein | Hacker News Reader

Comment by glenstein | Hacker News Reader

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>Have you considered the institutional knowledge could actually be actively preserved and distributed with AI?

Well that's what this whole debate comes down to. And, to my mind at least, it's a rare case of an actually interesting question about AI, because like the article says, it can plausibly deteriorate exactly that kind of knowledge. But as you note, it can also maintain it.

I think there's a sense in which it might do both at the same time. AI's version of on call tacit knowledge might be something like lazy-loading just-in-time tacit knowledge, but at the cost of who knows what cognitive paths we might have by keeping that knowledge resting in-house. We would gain real efficiency but we wouldn't know we wouldn't know.

>The kind of tacit knowledge that is situated and not readily preserved in a book might be absorbed by thinking machines and proliferated to the next person who needs it. The caveats would be trade secrets, skill differentiators, that people might not be willing to discuss, and manufacturing secrets of national importance. Maybe you can think of others.

It's funny that you credit AI with this (and I don't disagree), because tacit knowledge was exactly the thing Hubert Dreyfus spent a career insisting computers would never have, and his wisdom was taught to generations of undergraduates across the country and world who treated it as received wisdom and still is regarded as such in certain academic corners.

> I think there's a sense in which it might do both at the same time.

This is probably true.

Many artisan fabric techniques were lost when industrial looms displaced those jobs. But heavy industry enabled cloth to be manufactured at a rate that people were free to spend their time and money on other priorities - and now (centuries later) the society is in a sufficiently advanced stage of development that the old techniques are being rediscovered.

Perhaps the example underscores the importance of thoughtful preservation of insitutional knowledge.

> tacit knowledge was exactly the thing Hubert Dreyfus spent a career insisting would never happen

Could you elaborate on this? It sounds like something any anthropologist would laugh at; there's always an oral culture.

I edited that sentence to try and clarify a bit, but Dreyfus was a continental philosopher out of Berkley active basically from the 1950s to the 2010s. He engaged in decades of friendly debates with other philosophers about the limits of computers.

When he described those limits, he always frustrated computer scientists and analytic philosophers because he spoke in a kind of informal philosophical vocabulary and didn't really formalize his ideas. So he would say computers didn't have things like "tacit knowledge" or "insight" and he railed against "symbol manipulation". Famously he declared chess would never surpass human expert play. He wrote a book called "What Computers Can't Do" and another called "What Computer's Still Can't Do".

I personally think his argument was laughably wrong if well intentioned. But some people think it was respectable. I think in the present day, he's often rehabilitated with a kind of apologetic reinterpretation, such that things like transformers, weights, vectors, etc were what he really meant all along.

I think he was not wrong that some higher layer of sophistication would prove to be necessary, but he was wrong, I think definitively, to think that "symbol manipulation" of computers was a kind of category error. Even today's best models are still running on logic gates over 1's and 0's, and it was his failure of imagination to doubt that those could be the conceptual bedrock for AI, tacit knowledge and all.

He passed away in 2017, which is too bad because I would have loved to have seen his interpretation of things like GPT-6 Astra.

Ah I see! The change helps.

> think that "symbol manipulation" of computers was a kind of category error

This is where we do drift off into the semantic bog. If there is tacit knowledge in an LLM, then where is it? It must be in the weights, and it must have somehow come from the training data. Therefore the weights represent "compressed" knowledge. Is that then not "tacit" since it's explicitly encoded?

You'll get no disagreement from me here. But be ready because some people live to debate this, and Dreyfus is the poster child for a whole philosophical tradition.

I think what it comes down to, is trying to turn the specialness of human intelligence into undefinable magic, essentially playing god of the gaps with the concept of human insight. So by design, it has to be something that can't be amenable to any formal representation like weights.

> Famously he declared chess would never surpass human expert play. He wrote a book called "What Computers Can't Do" and another called "What Computer's Still Can't Do".

He never made such a claim. In the introduction to the 1972 print of this book he discusses the forecasts from Turing to his time of computers' abilities to play chess and the then state of the art. He criticizes the early optimism in 1950s mentioning that in 1957 H. Simon though in 10 years computers would excel in chess.

Dreyfus goes on to discuss the history of forecasts and progress in computer chess in a nuanced and highly informative analysis.

Whatever your opinion of his work I don't think it's fair to say his arguments are "laughably wrong" at any turn. I haven't read his books in detail but from what I know he made great contributions to the dialogue about technology and I don't know any instance of his making crass predictions or anything that he wrote that could be labelled "laughable".

Dreyfus certainly claims he was mischaracterized, but what he "really" said always turns out to be a conveniently moving target.

He thought that the complexity of chess rendered it solvable in principle but "uncomputable" in practice. You're right that he was speaking to the times he was familiar with, and what he meant by "impossible in practice" was something like letting a 1Mhz computer explore all the possible chess moves from now until the heat death of the universe. Relying on that to insist that computers defeating humans in his lifetime was consistent with what he envisioned stretches past charitability and into sophistry.

And I don't think you can extend him that charity without doing the same in the other direction, which would also collapse his basic thesis. Dreyfus was disproportionately preoccupied with retelling the failures of the 1950s over and over again using them to represent the whole of computing while the world moved on, and extending the same charitable repairs in favor of AI research make it something less easily caricatured, and still based on the same logic gates and 0s and 1s he was criticizing.

If that's not enough, Dreyfus explicitly said that what was lacking in chess programs was (1) any practical ability to do the brute forcing needed, (2) any kind of nim-style logical shortcuts around brute forcing or (3) any kind of expert level heuristics because he categorically believed those simply weren't programmable. And he believed that those exhausted the options. [1]

There's no version of this that can be correct because even if you think he's right that chess engines got better by progressing to some different conceptual paradigm, that paradigm is still embodied in same logic gates and 1's and 0's that he thought only pertained to prior paradigms he was criticizing. He was wrong to assume such things as "heuristics" were outside of that scope.

1. https://repository.essex.ac.uk/42372/1/Martin%20and%20Willia...

I might have expressed myself poorly. I do not mean to claim Dreyfus is worth reading because correct, but that he is worth reading despite wrong.

I do object to calling his writing "laughable".

Thank you for the article, it seems quite interesting on skimming and I will save it for later.

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