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From Pattern Recognition to Economic Disequilibrium: Emmanuil Braverman’s Theory of Control of the Soviet Economy
This paper is focused on the economic works of the Soviet machine learning pioneer Emmanuel Braverman who published, during the 1970s, a series of papers introducing disequilibrium fixed-price models of the Soviet economy. This highly original theory, developed independently from the Western analyses of disequilibria, proposed some rationing mechanisms capable, under some conditions, to bring a system to the state of equilibrium. However, in a fixed-price economy equilibria are not necessarily optimal or effective, therefore specific observational and analytical procedures aiming at defining the states of the systems’ elements and interventions bringing a system to a better state, had to be invented. This analytical framework was interpreted by Braverman as a “qualitative system of control” of the Soviet economy as a sort of a third-way solution between neoclassical models of spontaneous coordination of autonomous agents and theories of optimal planning. As I argue in this paper, this innovative approach, very different from the styles of reasoning in mathematical economics of his time, was grounded in his work on pattern recognition and was informed by a cybernetic vision of control as information processing and communication in complex systems. This work can be considered as a precursor of the contemporary approaches to algorithmic economic governance.