Minds before Machines: An Anatomical Review of the Discrete–Continuous Epistemic Divide, Whitehead's Process Metaphysics and the Coming Contest of Cognitive Styles in Computing

A widely shared argument holds that dominant Western mathematical styles, epitomised by Bourbaki's axiomatic structuralism, have trained engineers to see the world as discrete objects under linear rules, and that this habit has locked computing into sequential digital silicon, while Eastern correlative and process traditions are freer to treat computation as the physical behaviour of a continuous medium. This paper reviews an AI-generated four-part analysis of that argument, which deliberately set aside its geopolitical framing, and augments it into a verified academic treatment. Following the KSCCN practice of anatomical review, it separates the source's verified claims from its overstatements and checks each against primary literature: the empirical programme on analytic and holistic cognition, the sinological literature on correlative thinking, the history of the continuum, Whitehead's process metaphysics and recent work in optical and analog computing. The review confirms that the contrast between object-analytic and field-relational styles is a real historical and cognitive tendency, but finds that it does not divide civilisations cleanly: every combination of discrete or continuous and substance or process thinking has Western, Chinese and Indian representatives. Three original analyses are added: a map of traditions on two ontological axes, a computation showing how far typical cultural effect sizes are from a categorical divide, and a numerical simulation of a lens-based optical correlator showing in what precise sense a continuous medium can compute. The paper concludes that the coming contest is between epistemic commitments embedded in substrates and institutions rather than between civilisations, and that technodiversity, not civilisational victory, is the productive outcome, with implications for states that are adopting rather than inventing computing paradigms.