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But what is a problem that specifically requires intelligence to solve? How do we know we're measuring intelligence, and not the programs aptitude for the parti

But what is a problem that specifically requires intelligence to solve? How do we know we're measuring intelligence, and not the programs aptitude for the particular problem?

Houshalter 13y ago
Why does it matter? If if solves the problem then it's as good as if it was fully intelligent. Who cares what goes on inside the black box? If you worried about it overfitting to a specific problem, give it lots of problems and weight the solutions by complexity. So you heavily favor simple algorithms that can learn to solve a large class of problems, over ones that are more adapted for those specific problems.
- benched 13y ago
  All I'm learning from this thread is that some people see infinite regression where others see tautology. edit: what I mean: Person 1: "What if we're just measuring the color of the sky? What if we're just measuring blueness? What if we're just measuring a wavelength of light? ... ..." Person 2: "The sky looks blue."
  - Houshalter 13y ago
    What do you mean?
- rectangletangle 13y ago
  It definitely could still be useful. However it may not posses "general intelligence," and therefore may not be applicable to as many scenarios as human like intelligence is.
- mannykannot 13y ago
  "Who cares what goes on inside the black box?" That's the most interesting and informative issue presented by this scenario. The problem with the sort of test you propose is that just because a human uses intelligence to solve a problem, it does not follow that the task requires intelligence. For example, playing chess. From an engineering point of view, your black box may be as good as the real thing, though you couldn't really trust it beyond the areas of its demonstrated competence. Knowing how it works, however, would be the most significant achievement. Furthermore, it's going to be hard to build one of these black boxes without a reasonably good idea of how it is going to work. There is also the risk that your weighting scheme will rule out the only algorithms that have a chance of succeeding, because I bet they are pretty complex.

But what is a problem that specifically requires intelligence to solve? How do we know we're measuring intelligence, and not the programs aptitude for the particular problem?

Houshalter 13y ago

Why does it matter? If if solves the problem then it's as good as if it was fully intelligent. Who cares what goes on inside the black box? If you worried about it overfitting to a specific problem, give it lots of problems and weight the solutions by complexity. So you heavily favor simple algorithms that can learn to solve a large class of problems, over ones that are more adapted for those specific problems.

benched 13y ago
All I'm learning from this thread is that some people see infinite regression where others see tautology. edit: what I mean: Person 1: "What if we're just measuring the color of the sky? What if we're just measuring blueness? What if we're just measuring a wavelength of light? ... ..." Person 2: "The sky looks blue."
- Houshalter 13y ago
  What do you mean?
rectangletangle 13y ago
It definitely could still be useful. However it may not posses "general intelligence," and therefore may not be applicable to as many scenarios as human like intelligence is.
mannykannot 13y ago
"Who cares what goes on inside the black box?" That's the most interesting and informative issue presented by this scenario. The problem with the sort of test you propose is that just because a human uses intelligence to solve a problem, it does not follow that the task requires intelligence. For example, playing chess. From an engineering point of view, your black box may be as good as the real thing, though you couldn't really trust it beyond the areas of its demonstrated competence. Knowing how it works, however, would be the most significant achievement. Furthermore, it's going to be hard to build one of these black boxes without a reasonably good idea of how it is going to work. There is also the risk that your weighting scheme will rule out the only algorithms that have a chance of succeeding, because I bet they are pretty complex.