Causal reasoning is what intelligence needs to be safe and super.

safe A system is safe when the probability of harm associated with its existence and use is reasonably low. Harm is a counterfactual notion: an undesired outcome that would not have occurred without the system. Safety therefore cannot be specified or checked without causal models.

super Causal reasoning, as formalized by Judea Pearl, is what lets a system work out the result of an intervention and reason about scenarios that differ in their conditions but share the same structural mechanisms. A system that does this worse than humans is not superintelligent.

X Y U X′ Y′
A twin network. The factual world (solid) and the world that didn’t happen (dashed) share the same background conditions U.

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Photo of Alberto D. Horner

AI Consultant with research experience in Causal AI and a biweekly contributor to the causalpython.io newsletter.