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.

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.

Humans can and we are really good at it.

I suspect that you made that comment because you think in the terms of rigorous detection of causality, not everyday effective detection of causality heuristically.

Nowadays yes. For most of history though (and still commonly today), causal explanations for plenty of things involved some flavor of the supernatural.

Yes - humans do it abductively, which isn't rigorous but serves our purpose most of the time. You can't trust a self driving system with abduction though - it's the style of reasoning that gave us rain dances and homeopathy.

>You can't trust a self driving system with abduction though

All wetware based self driving systems on the road use heuristics in their wetware system.

You can't hope to have self driving without heuristics. That's what deep learning is.

I'm sure there was a philosopher who said that his deepest wish was to know just one cause. Been trying to find out who said it for ages with no luck, so maybe I'll just attribute it to myself.

David Hume perhaps? He reasoned that causality was not empirical and therefore was a habit of thinking humans acquired from constant conjunction of events. Kant was troubled by that so he elevated causality to a category of thought, like space and time, which the mind used to structure sensations.

+1 to Hume. He described causality as being a glorified expectation which is subject to change at any time.