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Humans can almost always give an explanation judgement but, for intuitive judgements at least, the reasons we give are frequently wrong or incomplete. People s

Humans can almost always give an explanation judgement but, for intuitive judgements at least, the reasons we give are frequently wrong or incomplete. People seldom notice that we rate essayists with more symmetric faces as better at writing but we have this bias and tons more besides. But I don't think that there's any reason to doubt that when using abstract reasoning, Kahneman's system 2, our explanations of our thought processes can't be accurate. It's system 1 that's opaque to accurate introspection.

szemet 8y ago
Aren't we - as a group - better in this? I'm thinking about the scientific method, and the common differentiation there between the context of discovery and the context of justification. So you are free to discover a mathematical theorem by intuition or during daydreaming (like the molecular structure of benzene) - anything goes. But in the context of justification, you have to be much more disciplined - even if you trust your own intuitions and don't need to persuade yourself (of course generally you should not trust your intuition in scientific context that much;), you have to persuade others who are missing your insight. edit: And of course - in the end - to accept something as a true A.I. system, it probably has to persuade us that its intuitions are right, using the type justifications we accept. (So even if it has better types of justification - if we won't get it, they has to dumb it down to our level of scientific understanding)
- red75prime 8y ago
  We are verifying the results of our opaque brain processes. We cannot yet verify that our explanations of those processes are correct.
Nasrudith 8y ago
Given some results regarding brain damage we might just be rationalizing afterwards separate from the problem solving. Severed corpus callosum I believe it was. Or that effect might just be how a brain keeps functioning after losing some pieces - better off evolutionarily have data integrity issues than shut down if a checksum fails. I believe that ML can technically give you an answer but it ammounts to a summation of its training set and how it parses the data. Which isn't too readable to even mathematicians and leaves it vulnerable to stuff like adding a small pixel cloud to cause it to see a toy turtle as an assault rifle. Our errors certainly exist for visual processing but they tend to be more distorion than that.

szemet 8y ago

Aren't we - as a group - better in this? I'm thinking about the scientific method, and the common differentiation there between the context of discovery and the context of justification. So you are free to discover a mathematical theorem by intuition or during daydreaming (like the molecular structure of benzene) - anything goes. But in the context of justification, you have to be much more disciplined - even if you trust your own intuitions and don't need to persuade yourself (of course generally you should not trust your intuition in scientific context that much;), you have to persuade others who are missing your insight. edit: And of course - in the end - to accept something as a true A.I. system, it probably has to persuade us that its intuitions are right, using the type justifications we accept. (So even if it has better types of justification - if we won't get it, they has to dumb it down to our level of scientific understanding)

red75prime 8y ago
We are verifying the results of our opaque brain processes. We cannot yet verify that our explanations of those processes are correct.

Nasrudith 8y ago

Given some results regarding brain damage we might just be rationalizing afterwards separate from the problem solving. Severed corpus callosum I believe it was. Or that effect might just be how a brain keeps functioning after losing some pieces - better off evolutionarily have data integrity issues than shut down if a checksum fails. I believe that ML can technically give you an answer but it ammounts to a summation of its training set and how it parses the data. Which isn't too readable to even mathematicians and leaves it vulnerable to stuff like adding a small pixel cloud to cause it to see a toy turtle as an assault rifle. Our errors certainly exist for visual processing but they tend to be more distorion than that.