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You need to use the right level of abstraction for the problem at hand. For modeling intelligence, abstracting away the probabilistic/statistical aspects of cog

by upquark 13y ago

You need to use the right level of abstraction for the problem at hand. For modeling intelligence, abstracting away the probabilistic/statistical aspects of cognition greatly limits your options. Continuing the web development analogy, abstracting away statistics in cognitive science is like abstracting away JavaScript/HTML and using WYSIWYG GUI tools. With the same effect of only being applicable in toy problems and not scaling to real world scenarios :)

hharrison 13y ago
There's a huge middle ground between reducing cognition to statistics (as you seem to be proposing) and "abstracting away" the statistics. You seem to be accusing any approach that's not "statistics all the way down" of ignoring the statistical nature of the mind. When in fact, there are many approaches to cognition which make heavy uses of advances in statistical theory without reducing cognition to statistics. What you're proposing is an overly reductionist ontology, IMO, and yet I agree that statistics are important, if not critical. (Hint: not the boring linear kind of statistics that you so often see in Big Data)
- upquark 13y ago
  No I'm not arguing for a statistics-only scheme, just that you can't ignore it / abstract it away, and that its role is crucial in cognition. I think we agree with each other.
  - hharrison 13y ago
    Well, you said "you cannot not reduce it [AI] to statistics". And I'm saying, not only is it possible to not reduce AI to statistics, it is desirable. It's the reduce part that I have a hard time with.
    - upquark 13y ago
      Possibly poor wording, my intent was to say that you cannot dismiss or underestimate statistics in modeling the mind because the damn thing is a sophisticated statistical information retrieval system (with some higher-level structure on top for doing things like debating mind modeling on HN).
gtrak 13y ago
What makes the right level of abstraction right? Seems like the units of abstraction have to be amenable to application (analogy), but rightness is fluid. If you have a turing machine, it might make more sense to write a JS compiler first because of the familiarity and perceived difficulty of translating your thoughts, but that's a statistical process of your own head. If you're a fresh mind, you would never create a JS compiler. The aggregated feedback of our social consciousness over time is what sets the 'rightness' of any approach by modulating the difficulty and expressiveness of each concept to each individual.
- upquark 13y ago
  What makes it right is purely pragmatic and a function of our abilities and limitations, scientific and computational resources, time constraints, etc. We could in theory run quantum simulations for everything, given the resources, but we don't have them.

by upquark 13y ago

hharrison 13y ago

There's a huge middle ground between reducing cognition to statistics (as you seem to be proposing) and "abstracting away" the statistics. You seem to be accusing any approach that's not "statistics all the way down" of ignoring the statistical nature of the mind. When in fact, there are many approaches to cognition which make heavy uses of advances in statistical theory without reducing cognition to statistics. What you're proposing is an overly reductionist ontology, IMO, and yet I agree that statistics are important, if not critical. (Hint: not the boring linear kind of statistics that you so often see in Big Data)

upquark 13y ago
No I'm not arguing for a statistics-only scheme, just that you can't ignore it / abstract it away, and that its role is crucial in cognition. I think we agree with each other.
- hharrison 13y ago
  Well, you said "you cannot not reduce it [AI] to statistics". And I'm saying, not only is it possible to not reduce AI to statistics, it is desirable. It's the reduce part that I have a hard time with.
  - upquark 13y ago
    Possibly poor wording, my intent was to say that you cannot dismiss or underestimate statistics in modeling the mind because the damn thing is a sophisticated statistical information retrieval system (with some higher-level structure on top for doing things like debating mind modeling on HN).

gtrak 13y ago

What makes the right level of abstraction right? Seems like the units of abstraction have to be amenable to application (analogy), but rightness is fluid. If you have a turing machine, it might make more sense to write a JS compiler first because of the familiarity and perceived difficulty of translating your thoughts, but that's a statistical process of your own head. If you're a fresh mind, you would never create a JS compiler. The aggregated feedback of our social consciousness over time is what sets the 'rightness' of any approach by modulating the difficulty and expressiveness of each concept to each individual.

upquark 13y ago
What makes it right is purely pragmatic and a function of our abilities and limitations, scientific and computational resources, time constraints, etc. We could in theory run quantum simulations for everything, given the resources, but we don't have them.