I was delighted to be invited to speak at Ohio State's Moritz College of Law to issues of "Government “Social Credit” Scores for Individuals in China and the West: Smarter Governance or Social Control?" More information on the event here. My great thanks to Dennis D. Hirsch, Professor of Law Ohio State Moritz College of Law and Faculty Director, Program on Data and Governance, for the invitation, and to Porter Wright Morris and Arthur for their support of this lecture series.
The title of the lecture gives away its central objective--to consider the now unmistakable movements of two quite distinct political and ideological systems, the United States and China, toward an embrace of cultures of data driven governance as a supplement to and perhaps even as a substitute for the traditional means by which states authoritatively bound its citizens (constitution, statutes, cases, etc.). It does so by looking at the quite distinct ways in which the United States and China have approached the construction of systems of behavior control through data driven analytics the consequences of which are implemented through algorithms.
That this topic of discussion is possible at all owes much to globalization as it has developed over the last several decades. Globalization has made states less fussy about the means they use to govern. Two trends converging made that palatable. First, governmentalization of the private sector brought regulatory contracting to the private sector. Second, the entry of the state into markets as a private participants, brought the techniques of the market to the public sector. Both trends--conflating public and private governance--made it easy to cross lines (and regulatory taboos) that once held more power. Added to that were changes in underlying ideologies of the principles of regulation--from getting someone to "do" or "not do" something, to a still evolving contemporary zeitgeist emerging around cultures of accountability and compliance (with different but converging sensibilities in the public and private sectors) built around objectives or principles based rule making. The door opened, and the United States and China walked through.
In China, this process has been highly centralized, political, and public law driven. It is also fairly transparent. The result has been the commencement of a construction of a Social Credit system which when completed will move governance toward a new era (to invoke the ideological line embraced after the 19th Communist Party Congress).
In the United States (and other liberal democratic free market states), the process has been highly decentralized, privatized, and markets driven. Engagement by the state has been episodic and opportunistic, as well as contradictory. This mirrors a vastly different ideological foundation from that of the Chinese. The result has been the development of a highly fractured and layered polycentric systems of functionally differentiated public and private regimes of data driven governance (in the sense of the exercise fo a power to manage targeted behaviors).
In both cases, the progress toward coherent and more comprehensive systems are aided and constrained both by the state of technology (the so-called big data or AI challenge), as well as by the normative implications of those techniques (the challenge of big data and AI for the hierarchies of political authority within either system). As important, neither system has yet managed the difficult conceptual tasks of harnessing the distinctive capabilities of data, of analytics, and of algorithm in ways that leverage system building. Lastly neither system has yet to face the fundamental ordering challenge of this "social credit" data-driven governance enterprise--the relationship between these modalities of behavior control and those traditionally used by the state (constitution, law, statute, administrative regulation, etc.).
It is to these issues that the lecture will focus. The PPT hopefully will provide a taste of that discussion.
The title of the lecture gives away its central objective--to consider the now unmistakable movements of two quite distinct political and ideological systems, the United States and China, toward an embrace of cultures of data driven governance as a supplement to and perhaps even as a substitute for the traditional means by which states authoritatively bound its citizens (constitution, statutes, cases, etc.). It does so by looking at the quite distinct ways in which the United States and China have approached the construction of systems of behavior control through data driven analytics the consequences of which are implemented through algorithms.
That this topic of discussion is possible at all owes much to globalization as it has developed over the last several decades. Globalization has made states less fussy about the means they use to govern. Two trends converging made that palatable. First, governmentalization of the private sector brought regulatory contracting to the private sector. Second, the entry of the state into markets as a private participants, brought the techniques of the market to the public sector. Both trends--conflating public and private governance--made it easy to cross lines (and regulatory taboos) that once held more power. Added to that were changes in underlying ideologies of the principles of regulation--from getting someone to "do" or "not do" something, to a still evolving contemporary zeitgeist emerging around cultures of accountability and compliance (with different but converging sensibilities in the public and private sectors) built around objectives or principles based rule making. The door opened, and the United States and China walked through.
In China, this process has been highly centralized, political, and public law driven. It is also fairly transparent. The result has been the commencement of a construction of a Social Credit system which when completed will move governance toward a new era (to invoke the ideological line embraced after the 19th Communist Party Congress).
In the United States (and other liberal democratic free market states), the process has been highly decentralized, privatized, and markets driven. Engagement by the state has been episodic and opportunistic, as well as contradictory. This mirrors a vastly different ideological foundation from that of the Chinese. The result has been the development of a highly fractured and layered polycentric systems of functionally differentiated public and private regimes of data driven governance (in the sense of the exercise fo a power to manage targeted behaviors).
In both cases, the progress toward coherent and more comprehensive systems are aided and constrained both by the state of technology (the so-called big data or AI challenge), as well as by the normative implications of those techniques (the challenge of big data and AI for the hierarchies of political authority within either system). As important, neither system has yet managed the difficult conceptual tasks of harnessing the distinctive capabilities of data, of analytics, and of algorithm in ways that leverage system building. Lastly neither system has yet to face the fundamental ordering challenge of this "social credit" data-driven governance enterprise--the relationship between these modalities of behavior control and those traditionally used by the state (constitution, law, statute, administrative regulation, etc.).
It is to these issues that the lecture will focus. The PPT hopefully will provide a taste of that discussion.
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