AI & Causality

Structural limits of observational learning for interventional competence

Modern AI systems are trained largely on observational data: patterns, correlations, and records of what has already happened. While it is familiar that correlation is not causation, less is known about what this implies for learning dynamics, intervention, and structural limits on generalization. This manuscript gives theorems characterizing fundamental limits of observational learning.

Marcus A. Thomas