Think Piece: "And an Algorithm to Bind them All? Social Credit, Data Driven Governance, and the Emergence of an Operating System for Global Normative Orders" for Workshop: Entangled Legalities

(Pix © Larry Catá Backer 2006)

I am delighted to be part of the upcoming workshop entitled Entangled Legalities hosted by  the Graduate Institute of Geneva and its Global Governance Center (more HERE). Over the course of two days a group of participants from a variety of fields will consider the conceptual framing of what has emerged as the in-between spaces of law – the interfaces between bodies of norms – and the challenge to traditional legal orders that comes with the resulting governance polycentricity.

This post includes the "think piece" that is my contribution to the event. It is entitled And an Algorithm to Bind them All? Social Credit, Data Driven Governance, and the Emergence of an Operating System for Global Normative Orders. 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.

The abstract and Introduction follow.  The preliminary draft may be accessed HERE.This paper is at it very earliest stages and is part of a broader project on social credit and data driven governance, so comments and reactions, etc. most welcome.

Think Piece Draft:

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

Larry Catá Backer

Pennsylvania State University

Abstract: The 21^st 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.

I. Introduction

The 21^st century has seen a reluctant acceptance in theory of the de-centering of the state, and consequentially of the recognition rise of multiple centers of governance with multiple forms of law (Backer, 2012). That conceptual recognition comes at least a century behind early modern studies of its realities in some states (Patrignani, 2016; p. 711). That reluctance arises from the ideological consequences of such a conceptual acceptance, the undoing of the project of centering the state within global politics, and of law as a strictly defined and superior expression of the political authority of the state.  Indeed, “The main shortcoming of the extended conception of law advocated by anthropological and sociological approaches is the one pointed at by the so-called pan-legalist objection: the problem of the distinctiveness of law from other social normative orderings has been haunting the theorists of legal pluralism until today”  (Patrignani, 2016; p. 713; Croce, 2012).

That acceptance has also produced a certain knowledge of the likelihood of space between these emerging centers of law/norms/governance (Krisch, 2010; Berman, 2012), both within and among the conventional nation state (Davies, 2010). It is within this space that one might seek both meanings and the manner in which what Lohmann once described as structural coupling might occur (Luhmann,1982 ).  This space without a space, these in-between spaces of law (and governance), has itself assumed a spatial dimension.  It now is understood as both a connector (the trames through which spaces connect and communicate) but also as its own normative space within which those communications and connections are not merely mediated but managed (Calliess & Zumbansen, 2010).   

Yet the conventional focus on the inter-spatial carries with it both promise and challenge.  The promise: interspatial gap filling in all of its complexities and theoretical possibilities.  The challenge is centered on the risk of boundaries without end—of the permanent and quite dynamic cacophony of borders that is produced by the obsession with the interfaces between bodies of norms that themselves create borders within the space between norm systems for which other interfaces are necessary. 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 here. 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. These “social credit” systems have been established as a means to aid traditional governance; yet they have the potential to displace the structures of governance they are meant to serve. The thesis of this essay is simple: that AI and big data management systems (social credit initiatives) suggest 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 (Tolkien, 1954, ch. 2).[1] 

The interspatial, and its data driven forms, produces a quite distinctive template for the conceptual construction of law/norms between law/norm systems; and it emerges with its own language and sensibilities in ways that are not yet completely clear. Every political culture approaches the emerging realities of “artificial intelligence,” machine learning, and the data driven governance that is sometimes its object, in ways that tends to affirm cultural expectations and points of view. Where cultures are obsessed with particular conceptions of privacy and property, the result is an engagement that is centered on political constraints against states and enterprises, on the management of markets for data, and at the same time on an enhanced methodology of data driven analytics to deepen cultures of compliance, assessment and accountability.  Thus, the regulatory machinery of the European Union has lately been tasked to manage data under the presumption of a hierarchy of authority that further presumes the normative nature of law and the mechanical nature of data and its analytics. Data and data processing “should be designed to serve mankind. The right to the protection of personal data is not an absolute right; it must be considered in relation to its function in society and be balanced against other fundamental rights, in accordance with the principle of proportionality” (General Data Protection Regulation, 2016,  ¶4). There is a particular aversion to the forms of data driven intrusions from the economic sector (the “for hire” fields) on the formalities and rituals of exogenous democratic expression (Statt, 2018). And, of course, there is an equal obsession with theft of information (Narayanan & Shmatkov, 2008) and its misuse (General Data Protection Regulation, 2016).  And yet, even as its elites offer the protection of law, it manages that data that itself manages behavior. 

“A tiny microchip inserted under the skin can replace the need to carry keys, credit cards and train tickets. . . . The small implants were first used in 2015 in Sweden – initially confidentially – and several other countries. Swedes have gone on to be very active in microchipping, with scant debate about issues surrounding its use, in a country keen on new technology and where the sharing of personal information is held up as a sign of a transparent society.” (Thousands of People in Sweden get Microchip Implants for a New Way of Life,” 2015.)

Thus combined, there is a tension between the centrality of the individual as the incarnation of data, and the utility of data in the production of economic goods with great disciplinary effects.

On the other hand, where cultures are obsessed with communal solidarity and the protection of stability around socio-political core values as the basis for legitimate social organization and operation, then the result is an engagement that is centered on issues of surveillance, of detection, and of management of behavior around key societal principles.  There is a particular aversion of anti-social behavior as a politically destabilizing force (Zhang, Peng, Yu and Lu.,2013). Feng Xiang, a law professor at Tsinghua University recently spoke about the end of markets, “If AI rationally allocates resources through big data analysis, and if robust feedback loops can supplant the imperfections of ‘the invisible hand’ while fairly sharing the vast wealth it creates, a planned economy that actually works could at last be achievable.” (Feng Xiang, 2018). He might not be wrong about AI and markets, even the Cubans have sought to turn their economic planning into the rudiments of complex algorithms (Backer, 2017). Yet this culture shares with the other a mania for observation—and for punishment and reward based on that power to observe (Leng, 2018). And yet, even as there is a movement toward the overt management of behavior through data, there is as well an obsession to ground that regulatory approach within the structures of regulation—in this case a regulation that protects the integrity of data and its use by the state and its delegees. Data, and consequence (accountability for business, incentive to encourage preferred behaviors and punish violations of behavior norms) thus combined, focus on stability and order in social development.  

Yet both approaches fail to see the more important insight—that AI and big data management suggests the fundamental reshaping of law and law systems. 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.  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 two quite distinct forms 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. 

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[1] That extra-spatiality is nicely captured through what is now a sadly hackneyed and often quoted passage from a well-known book: “Three Rings for the Elven-kings under the sky, Seven for the Dwarf-lords in their halls of stone, Nine for Mortal Men doomed to die, One for the Dark Lord on his dark throne. In the Land of Mordor where the Shadows lie. One Ring to rule them all, One Ring to find them, One Ring to bring them all and in the darkness bind them. In the Land of Mordor where the Shadows lie.” (Tolkien, 1954 epigraph)