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Re:Understanding Causality Is the Next Challenge for Machine... by evjrob on Thursday October 29, 2020 @01:56PM (#24933185)
I think it's clear that humans at least try to pick out the causal factors, and reason causally about the outcomes of specific actions. Non human animals do too; they can learn to take specific actions for food rewards in a Skinner Box for example. Now I agree humans get it wrong a lot of the time, and other animals might get it wrong even more than we do.

I don't think our fallibility in causal reasoning makes it useless to pursue as a goal in artificially intelligent systems. It doesn't need to be perfect, just useful and better than not having it. Afterall, our perception systems are pretty fallible too, otherwise things like optical illusions wouldn't exist.

Re:Understanding Causality Is the Next Challenge for Machine... by lambdatronics on Sunday November 01, 2020 @04:55PM (#24962867)
It always bugs me when optical illusions are brought up as instances of failure of the our perception system. These contrived conditions are really the 'exceptions that prove the rule:' our visual system has powerful inference capability running below the level of conscious perception, and most of the time it works so well we can't fathom the distinction between the model we infer and the sense data that the system works from. For instance, we perceive one scene with depth, when what we start with is two scenes with slight discrepancies.

Somewhat tangentially, I recall a psych paper where the researchers found that people perceive images in mirrors to be located behind the surface of the mirror. The researchers apparently thought that the image was at the surface of the mirror (ie, they misunderstood basic optics), and concluded that they'd discovered an optical illusion.