Why Causal AI Models Outrun Bayesian Networks

The two types of models have some superficial similarities, but they also have significant differences. Bayesian networks (BNs) simply describe patterns of correlations between variables. Causal AI models capture the underlying processes that drive those statistical relationships. This paradigm shift makes Causal AI models more flexible, versatile, and powerful than Bayesian networks.