I have just posted a draft manuscript for comment. Entitled (for the moment) Data Driven Governance: Building Data Driven Accountability Based Regulatory Systems in the West and Social Credit Regimes in China, the draft has two principal objects. The first is to consider the parallel efforts of both Western states and China to develop data driven accountability fueled governance systems. The second is to suggest the scope of the challenges that such system construction will likely encounter.
The development of data driven governance has provoked substantial angst and uncertainty everywhere. There is good reason for this angst, but perhaps not for the usual reasons conventionally advanced. Data driven governance systems (including the quite ambitious project of Chinese social credit) grounded in accountability and managed through the self-reflexive operations of an analytics that incorporates social, economic, political or religious objectives through algorithm represents a new form of governance, with its own language, its own structures, and its own ecologies. It exists still within traditional systems of law and regulation and was originally understood as a technique for the implementation of the policies and objectives of those systems. Those traditional systems have developed their own language, modalities, ideologies and structures within which the integrity of the system can be maintained. Yet in this "new era" of governance, data driven governance already exhibits signs of producing its own language, its own structures and its own modalities for enhancing and protecting system integrity within ideological parameters in the context of which the traditional language and forms of constitutional political government operated through complex bureaucracies intertwined with judiciaries and popular representative organs may n longer be particularly relevant.
This "new era" of governance thus not not necessarily call for yet more efforts to "tame" data driven governance within the cage of traditional government and its structures and methods of operation. Instead it may require the development of new sensibilities, new interpretive language, and the recognition of new classes of system operators whose injection into the process of governance may profoundly affect the way societies understand and engage with governance organs. This trend may be understood (and encouraged) within those organizations at the vanguard of these changes (within vanguard enterprises in the West (and public security apparatus) and embedded within certain organs of collective organization in China). Yet among those deeply embedded within conventional governance-power systems it has produced resistance or efforts at domestication, which pepper scholarly journals and the regulatory efforts of state and international organs. Yet rather than or in addition to resistance and domestication, it may now be time to turn to the business of building principles of Demokratie, Sozialstaat, Bundesstaat und Rechtsstaat into and through the language of data and data analytics to ensure that algorithmic governance, like that of the law-regulatory systems that preceded it, will operate under appropriate ideological constraint. And if the politician, the lawyer, and the bureaucrat will not engage in these projects, then it is likely that the engineer, the econometrician and manager may. Power relations will not be the same thereafter.
The development of data driven governance has provoked substantial angst and uncertainty everywhere. There is good reason for this angst, but perhaps not for the usual reasons conventionally advanced. Data driven governance systems (including the quite ambitious project of Chinese social credit) grounded in accountability and managed through the self-reflexive operations of an analytics that incorporates social, economic, political or religious objectives through algorithm represents a new form of governance, with its own language, its own structures, and its own ecologies. It exists still within traditional systems of law and regulation and was originally understood as a technique for the implementation of the policies and objectives of those systems. Those traditional systems have developed their own language, modalities, ideologies and structures within which the integrity of the system can be maintained. Yet in this "new era" of governance, data driven governance already exhibits signs of producing its own language, its own structures and its own modalities for enhancing and protecting system integrity within ideological parameters in the context of which the traditional language and forms of constitutional political government operated through complex bureaucracies intertwined with judiciaries and popular representative organs may n longer be particularly relevant.
This "new era" of governance thus not not necessarily call for yet more efforts to "tame" data driven governance within the cage of traditional government and its structures and methods of operation. Instead it may require the development of new sensibilities, new interpretive language, and the recognition of new classes of system operators whose injection into the process of governance may profoundly affect the way societies understand and engage with governance organs. This trend may be understood (and encouraged) within those organizations at the vanguard of these changes (within vanguard enterprises in the West (and public security apparatus) and embedded within certain organs of collective organization in China). Yet among those deeply embedded within conventional governance-power systems it has produced resistance or efforts at domestication, which pepper scholarly journals and the regulatory efforts of state and international organs. Yet rather than or in addition to resistance and domestication, it may now be time to turn to the business of building principles of Demokratie, Sozialstaat, Bundesstaat und Rechtsstaat into and through the language of data and data analytics to ensure that algorithmic governance, like that of the law-regulatory systems that preceded it, will operate under appropriate ideological constraint. And if the politician, the lawyer, and the bureaucrat will not engage in these projects, then it is likely that the engineer, the econometrician and manager may. Power relations will not be the same thereafter.
The Abstract and Introduction follow. The draft may be accessed HERE. Comments and reactions most welcome!
Larry Catá Backer[1]
Abstract: Data driven
governance systems are transforming the regulatory landscape of both states and
other governance institutions. Grounded in principles of accountability and
embedded in incentive based systems for reducing risk and managing behaviors
through mechanisms of choice and markets, these governance systems may well
reshape the way states and other governance organs are constituted and operate.
This short essay has two objectives. The
first is to examine the challenges that social credit, ratings or assessment
systems pose for effective implementation. Social Credit itself refers
generally to a new mode of data driven governance through which data analytics
are used to create and operate algorithms that provide a basis for rewards and
punishment for targeted behaviors. More specifically, social credit references
the specific project of the Chinese state to create a comprehensive legal and
regulatory mechanism grounded in data driven metrics that they have named
"social credit." To that end, Section II considers first the
difficulties of separating the role of social credit as a set of techniques and
as a means of advancing ideological principles and objectives, in the context
of Chinese efforts. Section III then examines
some of the ways in which Western efforts at social credit institutions have
sought to meet similar challenges. The section first explores the context of
social credit systems in the West, and its operationalization, principally in
the private sphere and through the use of market mechanisms for behavior
management. It then examines the way that social credit might be used in the
West as a technique of governance and as a means of embedding international
standards in domestic behavior. The essay concludes by suggesting that social
credit represents the expression of new forms of governance that are possible
only through the correct utilization of big data management. The shift in regulatory forms also point to
significant shifts in the relationship between law, the state and
government. Accountability regimes
grounded in behavior standards enforced through data driven analytics may well
change the focus of public law from constitution and rule of law to analytics
and algorithm.
I.
Introduction
About a decade ago, when the attention of influential
thinking about governance was occupied elsewhere (Napolitano, 2011; Reyes, 2013),
one might have noted a curious development in the nature of the forms of
governance and its objectives within Western liberal democracies.
Surveillance has morphed
from an incident of governance to the basis of governance itself. It is both
government (apparatus) and governmentality (its self-conception and complicity,
the prisoner becomes his own keeper). In this sense, surveillance has become
the new regulatory mechanism. And law is becoming its servant. And the state,
either as the traditionally conceived apex of political order, or as the
repository of large aggregations of power within an international state system,
now serves as a (but not the) nexus point for the regulatory power of
technique. It is in this sense that we can speak of the “death” of the “state”
or the “rise” of a transnational political system, or the “death” of the
public/private divide or even the construction of non-public autopoietic systems.
(Backer, 2008).
These changes, one might
think, had the potential to change significantly the relationship of the state
to law, and of the character and role of law in the governing of states. Yet
an initial consideration might have dismissed this trend as irrelevant to the
development of the productive force of law and its system. The phenomenon
wasn't law; it had been the object of an abstract and remote elite political
philosophy since the 1970s (Foucault, 1997); and it appeared most valuable for
the extent to which one could pronounce this area "eccentric" rather than
for any value where it counted--for tangible value for academics concerned
about the collective intellectual movements of their field. Indeed, “it is
debated whether this increase in scholarly attention for governance (purely)
mirrors a rise in governance as a social phenomenon or (merely) indicates it is
a fashionable research topic.” (Mascini & Erp, 2014).
Still,
changes appeared to signal a new era of management that would fuse the
authority of public and private institutions in new and uncharted ways. The
trend was especially evident in the governance of behavior traditionally beyond
the reach of states—transnational economic activity (Ruggie, 2013). There was a sense that the appropriate
approach to the management of behavior (by states or private institutions) was
increasingly centered on the ability of decision makers to deploy data within
algorithms to develop finely tuned systems of reward and punishment to manage
appropriate behavior, to hold individuals accountable, and to contribute to
social development (e.g., Shiller, 1993). Due diligence and the construction and operation
of monitoring systems to provide accountability through standards developed by
law (or markets) appeared to produce that blending of public and
private—political and economic systems—that might overcome the difficulty of
extending law and rule of law beyond the state (UNHRC, 2008; Jayasuriya, 1998).
A intuition emerged, especially among scholars, that “corporate human rights
needs to be addressed at a variety of jurisdictional levels—national, regional,
transnational and international—by a variety of actors—states, international
organizations, corporations and NGOs.” (Simons & Macklin, 2014, p.
271).
That
move toward systems of discretionary decision making built on
data-algorithm-consequence models would have to further the command of law and
the public policies of which law was an expression (an especially potent idea in the management of human rights
impacts of enterprises, e.g., Deva, 2012; Simons & Macklin, 2014, pp.
178-271). It was management that
counted, perhaps more than law, and institutions that served principle through
the management of market driven behaviors, not political institutions. Within
this context, it appeared increasingly clear that rule of law was moving toward
data driven systems implemented through development of compliance practices of
individuals and enterprises, and overseen by administrators exercising
constrained decision making authority for the public good. Regulatory governance appeared to push
institutions not toward law based government but to accountability based
governance (Scott, 2004; Backer, 2019). Accountability refocused government
from the state and form law, to regulation, and the metrics required to bring
those subject to standards to account. “Decentered approaches to regulation
emphasize complexity, fragmentation, interdependencies, and government
failures, and suggests the limits of the distinctions between the public and
private and between the global and the national.” (Levi-Faur, 2011; p. 6).
And it also expanded an already quite substantial breadth for
regulating—there was nothing beyond the power of accountability, and thus of
management, through regulation if useful (Ibid., p. 9 “the expanding part of
governance is regulation, that is, rulemaking, monitoring, and enforcement”
Ibid., p. 16).
None
of this, however, appeared to disturb the supremacy or coherent integrity at
the heart of law or in the construction of public rule systems, even as spaces
for data driven governance seeped into the regulatory state apparatus. But
suddenly all that appeared to change. The trigger was the action by China, which
appears to have ascended to the position of principal global driving force in
political theory and action, when the Chinese State Council published its 2014 Notice
concerning Issuance of the Planning Outline for the Construction of a Social
Credit System (2014-2020) (the “State Council 2014 Notice”) (PRC, 2014). It
proposed using the technologies of big data and big data management along with
the possibilities of artificial and machine learning to develop comprehensive
data driven structures for management around algorithms that can produce real
time reward-punishment structures for social-legal-economic and other
behaviors. This project, a development of
ratings and rewards systems, means to unify and integrate systems of
monitoring, of transparency and of compliance within the traditional
law-administrative regulation construct of state systems, appears to be
one of the most innovative and interesting efforts of this decade. In the
process, of course, social credit, or data driven governance and accounting-punishment-reward
systems can significantly up-end the now century’s old structures of rule of
law by effectively making its structures irrelevant.
Social credit can be understood in two senses.
First, Social Credit itself references the specific project of the Chinese
state to create a comprehensive legal and regulatory mechanism that they have
named "social credit." Second, it refers generally to a new mode of
governance that recombines law and governance, and the public and private spheres
in new and hybrid ways that will likely transform the structures and principles
on which legal, governance, and societal regulatory systems are now understood
and through which they acquire their legitimacy. In both senses, the structures of social
credit are similar. In each case the system seeks to rate or score or assess
the object of regulation through a process that requires the acquisition of
specific and relevant data, which is then interpreted through the application
of an algorithm to produce an assessment or a score or a measure which can be
used to assess compliance with underlying objectives. Those scores than serve
to guide the application of legal or administrative decisions—they can trigger
rewards or suggest punishment (Backer 2017).
The triangular relationship between
governmentalization (of both public and private institutional actors with
managerial power), the mass of the population (which is its object and now its
foundation), and the ‘statistics’ (that both define and serve to manage the mass
of the population) is the essence of the problem of transparency in the
twenty-first century. (Backer 2013). At
its limit, the enterprise of social credit suggests both the emergence of a new
field of law as well as the negation of the privileging of law within economic
and political structures. On the one hand, one might be tempted to see in the
social credit enterprise a notion of the dissolution of the constitution of law
within itself; that is that the structures of legality, and its constitution,
will have consumed itself. What will emerge from that self-consumption will be
the methods and systems that it had once generated and which had been deployed
in the service of the constitutional project—that the success of the
constitutional notion will ultimately consume it so that where once there was
constitution there will only be mechanics; where once there was principle,
there will only be data; and where once there were norms, there will be
“statistics.” (Sokhi-Bulley, 2011; Cf., Desrosieres,
2011). This is bound up in the more fundamental idea of the end of law and the
irrelevance of lawyer except as technician of a new system the lawyer no longer
controls. On the other hand, the success of social credit may require and
indeed may be dependent on the simultaneous development of a law for the
digital and data age. That is, in the digital age, society (however
constituted) is even more in need of law's nomos and narrative. That nomos and
narrative may vary depending on the societal and political context, but it must
nevertheless develop alongside the re-constitution of the principles, customs
and manners of governance. To understand social credit, one must understand the
evolving structures of the relationships, in law and politics, of the
relationships between states, its masses, and the institutions through which it
operates. In that respect, data driven governance systems are transforming the
regulatory landscape of both states and other governance institutions. Grounded
in principles of accountability and embedded in incentive based systems for
reducing risk and managing behaviors through mechanisms of choice and markets,
these governance systems may well reshape the way states and other governance
organs are constituted and operate.
This short essay has two objectives. The first is to examine the challenges that
social credit, ratings or assessment systems pose for effective implementation.
To that end, Section II considers first the difficulties of separating the role
of social credit as a set of techniques and as a means of advancing ideological
principles and objectives. In this
section, social credit is examined as an aspect of big data management with
substantial governance and normative effects.
In that context, a number of issues are identified: social credit as a
project of informatics, as systems of control and management, and as a
governance mechanism. The section seeks to examine the proposition that to
understand the shaping of law today (and soft law as well) one must understand
social credit. The implications for the structure of government and for the
exercise of social and political leadership might be profound. Section III then
examines some of the ways in which Western efforts at social credit
institutions have sought to meet similar challenges. The section first explores
the context of social credit systems in the West, and its operationalization,
principally in the private sphere and through the use of market mechanisms for
behavior management. It then examines the way that social credit might be used
in the West as a technique of governance and as a means of embedding
international standards in domestic behavior.
The
essay concludes by suggesting that social credit represents the expression of
new forms of governance that are possible only through the correct utilization
of big data management. The extent to
which state authorities in China are willing to utilize big data management
will shape the form, scope and direction of the governance possibilities
inherent in social credit initiatives at the local, provincial and national
levels. But not just China; the quite visible move toward social create in the
West, albeit in a fragmented and functionally differentiated way among public
and private institutions, also point to significant shifts in the relationship
between law, the state and government.
Accountability regimes grounded in behavior standards enforced through
data driven analytics may well change the focus of public law from constitution
and rule of law to analytics and algorithm (cf., Morabito, 2015; Logan, 2010). In both China and the West, it is likely that
a new language will be required to frame these emerging structures of control.
[1] W. Richard and Mary Eshelman Faculty Scholar and Professor of Law and International Affairs, Pennsylvania State University; Board Member, Foundation for Law and International Affairs; Coalition for Peace & Ethics. The ideas in this essay was first presented at the Conference: The Chinese Social Credit System 2017, held at Shanghai Jiaotong University 23 September 2017. It draws on and expands the essay produced for that event and published as 测度、评估和奖励：中国和西方建立社会信用体系的挑战？(Cutting-edge measures, assessments, and rewards: The challenge of establishing a social credit system in China and the West?), “互联网金融法律评论（jiflsjtu）”微信公众平台。前沿栏目·第三季第21篇（总第182篇）. (Shanghai Jiaotong University “Internet Financial Law Review (jiflsjtu). My thanks to Flora Sapio (University of Naples), Sun Ping and Tong Zhiwei (华东政法大学英文版 ; East China University of Political Science and Law), and Duoqi Xu, Shanghai Jiao Tong University KoGuan School of Law; Director, Shanghai Jiao Tong University Research Center for Internet Law Innovation for their very helpful comments on earlier versions of this draft and for their support and engagement in this project.
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