Comment by mjburgess | Hacker News Reader

Comment by mjburgess | Hacker News Reader

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I think this debate has historically suffered from being conducted purely philosophically. Hediegger, Dreyfus (Ponty et al.) needed a bit more science and mathematics to see through the show.

All we need to do to make the Heideggerian point is ask the RL researcher what his reward function is. Have him right it out, and note, that its a disjunction of properties which already carve the environment of the robot.

In otherwords, the failure of AI is far less of a mystery than philosophy alone seems to imply. Its a failure in a very very simple sense if one just asks the right technical questions.

For RL, all we need ask is, "what will the machine do when it encounters an object outside of your pregiven disjunction?"

The answer, of course, is fall over.

Hardly what we fear when the wolf learns our movements, or what we love when a person shows us how to play a piano for the first time. The very thing we want, and we are told we have, isnt there... and it's not "not there" philosophically... its not there in the actual journal paper.

The Heideggerian point is a start, but I don't think it's enough to just point out a failure like this. This allegation is something like "The answer is already encoded in the question" like of trick, similar to one played in Foucault's episteme, where science itself is always-already a social construction without which it is impossible to happen.

The trick is challenging on first sight but it won't go very far, because it just tells us what ML lacks but doesn't tell us what ML can have and how to go there. We need a new kind of Turing test that actually reflects the power of human intellect.

I suspect even thinking there's a "test" has it wrong.

Yes, there's an experimental test -- as in, testing to see if salt is salt. But I dont think there's a formal test... as soon as you specify it, you've eliminated the need for intelligence. Intelligence is in that process of specification.

In otherwords, we should be able to ask the machine "what do you think of woody allen's films?" and rather than just taking any answer.. we need an empirical test to see if the machine has actually understood the question. Not a formal test.

There is no doubt a sequence of replies which will convince a person that the machine has understood the question: just record them, and play them back.

We're not interested in the replies. We're interested in whether the machine is actually thinking about the world. Is it evaluating the films? What are its views? What if I show it a bad film and say it wasnt by woody allen? What then?

There's something wrong in seeing this as a formal, rather than experimental, process. For any given machine we will need specific hypothesis tests as to its "intelligence", and we will need to treat it like any other empirical system.

OK, maybe "Turing test" was a bad hint because too often its extension turns into a philosophical rabbit hole of defining intelligence.

I want to get back to your initial statement about uncovering and structures, which I think is still grounded in the empirical realm. I think a less ambitious new test could be about the "uncovering" between analog data and the structures. To be real uncovering, the structures must be symbolic, not just transformed analog representation, and the symbolic structures must be useful, e.g. provide radical reduction of computational complexity compared to equivalent computation with analog data.

The point is to test if the machine can make the right abstraction (real uncovering) and also connect the abstraction with the data, not just games with words.

> For RL, all we need ask is, "what will the machine do when it encounters an object outside of your pregiven disjunction?"

> The answer, of course, is fall over.

There is no reason to think humans are qualitatively different in this regard, it is just that it does not happen very often. One case where it does is that humans pilots, no matter how competent, are incapable of flying without external visual references or instrument proxies for them.

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