A Unified Bayesian Model of Moral Judgment: From Greene’s Dual-Process to Predictive Coding

This paper offers a Bayesian critique of Joshua Greene’s dual-process model of moral judgment, which implicitly posits a structural division between emotional and cognitive systems. Drawing on recent developments in computational neuroscience, particularly predictive coding, active inference, and constructionist theories of emotion, I argue that both emotional and cognitive functions emerge from a unified inferential system that minimizes prediction error across bodily and environmental domains. This view suggests that the functional duality observed in emotional and cognitive moral judgments does not necessarily imply a structural dualism in the brain’s computational system. Reframing moral judgment within a monolithic Bayesian framework dissolves traditional dichotomies such as reason versus emotion, and reconceives moral judgment as an embodied, context-sensitive process of predictive adaptation. This shift has significant implications for neuroethics and moral psychology, inviting a move beyond static dual process models toward a dynamic, integrative account of moral judgment.