Hume's Representational Conditions for Causal Judgment: What Bayesian Formalization Abstracted Away

“A new paper argues that Bayesian approaches to AI have overlooked three key insights from Hume's philosophy: the need for experiential grounding, structured knowledge networks, and felt conviction in inference. These representational conditions could fundamentally improve how AI systems learn and reason about causality, bridging classical philosophy with modern machine learning.”