Mr Zhenbin Zuo
- Research student
Contact
About
Lecturer (Assistant Professor) in Law, University of Essex, School of Law, 1/9/2023 - present
Jones Day Fellow, School of Law, Peking University, 21/8/2024 - present
Research Associate, University of Cambridge, Centre for Business Research 1/9/2023 - present
University of Cambridge, Faculty of Law, Doctor of Philosophy (PhD), 2019 - 2024
Max Planck Institute for Comparative and Private International Law (Hamburg), Exchange Researcher, 07-09/2023
Harvard Law School, Visiting Scholar at the East Asian Legal Studies, 2019
Harvard Law School, Master of Laws (LLM), 2017 - 2018
Peking University, Law School, Master of Laws (LLM), 2016 - 2019
Renmin University of China, Bachelor of Law (LLB) & Bachelor of Business Administration (BA), 2012 - 2016
Other professional experience
Trainee at the European Court of Human Rights, Research Division, Strasbourg, 2016
Legal intern at Clifford Chance LLP antiturst team, Beijing, 2015
Research
Computational law
Algorithmic and data governance
Law and economics
Regulation and governance
Chinese law and society
Thesis: Law v Algorithmic Governance: China's Social Credit Systems and other Data Experiments
This dissertation proposes an institutionalist framework and a ‘scaling and layering’ hypothesis to understand the emerging theoretical domain of algorithmic governance. More specifically, the dissertation is concerned with the debate on the relationship between ‘law’ and ‘code’, with law referring here to various accepted or well established forms of text-based legal governance, and code to emerging forms of algorithmic governance, using machine learning and other aspects of artificial intelligence (‘AI’). The dissertation uses China’s Social Credit System (SCS) and other data/code experiments as case studies to test the validity of the proposed framework and hypothesis.
The contributions made by the dissertation are twofold: (1) theoretical and (2) empirical. Theoretically, the dissertation provides a rationale for viewing law and algorithmic governance as complements of, rather than substitutes for each other. This rationale is to be found in the inherent trade-off which exists between scaling and layering in complex forms of legal and algorithmic governance across extended geographies and populations. Empirically, the dissertation presents new evidence on China’s SCS, providing a more systematic and realistic picture of its development alongside various data experiments at both local and national level, and using the scaling-layering framework to revealing gains and problems from its mode of operation.
Supervisor(s): Professor Simon Deakin
Research centres: Centre for Business Research (CBR)