From Proudhon and Sorel to Protocols: A Qualitative-to-Algorithmic Framework for the Political Economy of Decentralized AI

This article develops an interdisciplinary framework linking nineteenth-century anti-authoritarian political theory — specifically Pierre-Joseph Proudhon’s mutualism and Georges Sorel’s revolutionary syndicalism. Using an original three-phase methodology termed Qualitative-to-Algorithmic Mapping (QAM), the study extracts socio-philosophical variables from the primary textual corpus of both authors, operationalizes them as measurable parameters, and situates them against publicly available secondary data drawn from decentralized computing protocols. The analysis suggests, at a theoretical and exploratory level, that principles of reciprocity and organic self-organization can function as optimization heuristics for resource allocation in networks that lack a central coordinating authority, plausibly reducing single-point-of-failure risk and increasing censorship resistance. The article closes by proposing a broader analytic frame, the Political Economy of Decentralized AI, together with a governance model in which data sovereignty is returned to the contributing user through digitally mediated mutualist structures. Throughout, the paper is explicit about the interpretive and non-empirical status of its central claims, treating the Proudhon–Sorel–AI mapping as a heuristic device for hypothesis generation rather than a demonstrated causal mechanism.