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.
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.
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.
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.