And an Algorithm to Bind Them All? Social Credit, Data Driven Governance, and the Emergence of an Operating System for Global Normative Orders

Abstract

The 21st century has seen a reluctant acceptance of the de-centering of the state, and consequentially of the rise of multiple centers of governance with multiple forms of law. That acceptance has also produced a certain knowledge of the likelihood of space between these emerging centers of law/norms/governance. This space without a space, this in-between space of law (and governance), has itself assumed a spatial dimension. Yet the conventional focus on the inter-spatial carries with it the risk of never ending boundaries—of the permanent and quite dynamic cacophony of borders. The problem of the never-ending spaces between spaces, where every law system itself defines its own inter-spaces, might itself be undergoing an extra-spatial transformation. That extra-spatial form of governance—in which space loses its centrality and law changes it forms and function, is the object of the exploration attempted in this essay. The essay considers the emergence of data driven analytics, and machine driven (artificial intelligence (AI) based) algorithmic techniques as defining not just new modalities of governance but reshaping the conception of spatiality within which governance happens. Its thesis is simple: that AI and big data management suggests the fundamental reshaping of law and law systems, one in which it may be possible to cobble together traditional spatial and inter-spatial of law toward a comprehensive management of behavior neither dependent on the forms and techniques of law nor on the bureaucratic apparatus of state. This reshaping will have particular effect on the way on which the emerging polycentric systems of governance that have been the singular feature of globalized law frameworks may be enmeshed; that is how the regulatory algorithm may come to rule them all. This essay, then, explores some of the potential ramifications of big data management and machine learning on the organization of the multiplicity of emerging law and governance systems and how these are or will change legal practice. To that end the paper will consider the emergence of data driven governance regimes. The first is the Chinese “social credit” initiative, which emerged in its current form in 2014. Social Credit is the name given to the initiative undertaken by the Chinese government during the present administration that is meant to produce an all-around approach to ensuring compliance with law and social responsibility under the guidance of the state. The second is U.S. and Western private initiatives around emerging markets for data. These are framed around principles of governance, risk management and compliance principles. It explores their potential systemic qualities and their relationship to contemporary and traditional law and governance systems. It considers the way that social credit in its public forms (China) and in its private forms (U.S. and the West) point to the emergence of a potential data driven unifying structure for legal multiplicity even as it changes the practices of law. Lastly, the paper explores the nature of that unifying structure within domestic legal orders and within global trade regimes.

Keywords: China, social credit systems, machine learning, transnational law, legal theory, compliance, risk management, algorithms, data analytics

JEL Classification: F68, K33, K42, P16, P37