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E-raamat: AI Development and the 'Fuzzy Logic' of Chinese Cyber Security and Data Laws

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  • Ilmumisaeg: 16-Dec-2021
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781009081108
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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 16-Dec-2021
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781009081108
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The book examines the extent to which Chinese cyber and network security laws and policies act as a constraint on the emergence of Chinese entrepreneurialism and innovation. Specifically, how the contradictions and tensions between data localisation laws (as part of Network Sovereignty policies) affect innovation in artificial intelligence (AI). The book surveys the globalised R&D networks, and how the increasing use of open-source platforms by leading Chinese AI firms during 20172020, exacerbated the apparent contradiction between Network Sovereignty and Chinese innovation. The drafting of the Cyber Security Law did not anticipate the changing nature of globalised AI innovation. It is argued that the deliberate deployment of what the book refers to as 'fuzzy logic' in drafting the Cyber Security Law allowed regulators to subsequently interpret key terms regarding data in that Law in a fluid and flexible fashion to benefit Chinese innovation.

Arvustused

'In examining 'fuzzy logic' in China's Cyber Security Law, this book provides invaluable insights into how China can be a powerful force in AI and tech innovation. It will have a significant impact on the way in which we conceive of technology regulation in China and elsewhere.' Andrew Godwin, Melbourne Law School, The University of Melbourne 'As China navigates tensions between state control and the imperatives of innovation in internet technology, this book offers timely insights. It digs deeply into the 'fuzzy logic' of rules on data localisation, and frames a compelling argument that will help shape scholarly and policy debates in coming years.' Adam K Webb, Co-Director and Professor of Political Science, Hopkins-Nanjing Center 'The Chinese tech scene presents us with a bewildering picture of deeply intertwined technological, political and commercial questions and interests. This complexity equally affects Chinese policymaking, particularly in fields related to data and artificial intelligence. This volume aims to enlighten the way by which China gropes its way forward carefully, but decisively.' Rogier Creemers, Assistant Professor, Leiden University 'Parasol brings ground-up observations of how China's tech ecosystem really works, and skillfully integrates those with important insights from academia and beyond. He cuts right through the tired debates about whether China can innovate, and deftly illustrates how the 'fuzzy logic' of Chinese tech policy is enabling local experimentation that drives the ecosystem forward. Parasol's book provides excellent intellectual scaffolding for those of us trying to make sense of how Chinese tech got where it is today, and where it's going next.' Matt Sheehan, Fellow, The Paulson Institute 'a timely, insightful and well-researched contribution to the literature on China and technology Parasol's fascinating book is likely to find its way onto postgraduate reading lists and presents ideas and hypotheses that can be tested and expanded in future scholarship.' Tim Stevens, The China Quarterly

Muu info

Explains the rapid rise of China's innovation system and provides a roadmap for the prospects of China's AI development.
Acknowledgements xiii
List of Abbreviations
xiv
Introduction 1(20)
0.1 Innovation versus Restriction
4(3)
0.1.1 Internet Plus
4(1)
0.1.2 Network Sovereignty
5(2)
0.2 Fuzzy Logic: The Chinese Approach to Innovation Regulation
7(8)
0.2.1 Policy Petri Dishes in Chinese Innovation
9(2)
0.2.2 Fuzzy Logic
11(4)
0.3 Significance of Data Localisation
15(3)
0.4 Research Methodology
18(3)
PART I Historical and Doctrinal Background
1 Innovating in China's Entrepreneurial Ecosystem
21(15)
1.1 `China Cannot Innovate'
21(3)
1.2 The Origin of China's Policy Petri Dishes
24(2)
1.3 China's Unique Ecosystem: Adept at Catching Up
26(3)
1.4 Top-Down or Bottom-Up Innovation?
29(3)
1.5 Entrepreneurial Ecosystems with Chinese Characteristics
32(3)
1.6 Conclusion: Assumptions on Chinese Innovation Challenges
35(1)
2 The Extent of Fuzzy Logic: The Tech Giants and Their `Illegal' Legal Structure
36(26)
2.1 `Fuzzy Logic' Laws
37(2)
2.1.1 What Is Meant by a `Fuzzy Logic' Law in China?
38(1)
2.2 Offshore Legal Structures: The Variable-Interest Entity (VIE)
39(11)
2.2.1 The VIE Structure
40(2)
2.2.2 Evading China's Investment Laws
42(1)
2.2.3 Paradoxical Side Effects of Fuzzy Logic on VIEs
43(3)
2.2.4 Disputes between Chinese Tech Firms and Activist VIE Investors
46(4)
2.3 The End of VIEs or a False Alarm?
50(2)
2.3.1 Future Legal Implications and Risks
51(1)
2.4 China Unable to Lure the Champions Home: 2018
52(4)
2.4.1 Maintaining the Fuzzy Logic: CDRs and the 2019 Foreign Investment Law
53(3)
2.5 US Blacklistings in 2019--2020: Are VIEs Still Relevant?
56(3)
2.6 Conclusion: Still Too Big to Fail
59(3)
3 China's Cyber Policies: Conflict between Innovation and Restriction
62(18)
3.1 Internet Plus versus Network Sovereignty
62(1)
3.2 Internet Plus
63(2)
3.2.1 Background to Internet Plus: China's Informatisation Strategy
64(1)
3.3 China's Cyber Institutions
65(5)
3.4 The Language of Internet Plus: Promoting Global Cooperation
70(2)
3.5 Network Sovereignty
72(5)
3.6 Network Sovereignty, Content Censorship, Internet Plus and the Influence of the BATs
77(1)
3.7 Conclusion: Unresolved Questions
78(2)
4 China's Data Security Policies Leading to the Cyber Security Law
80(14)
4.1 Planning for China's Cyber Regime: `Cyber Security and Informatisation Are Two Wings of One Body'
81(2)
4.2 The Critical Need for a Cyber Security Regime in China
83(2)
4.3 Network Sovereignty Laws Prior to the Cyber Security Law
85(2)
4.4 China's Anti-Terrorism Law
87(5)
4.4.1 Data Encryption and Backdoor Keys in the United States
89(3)
4.5 Conclusion: Policy Indicators?
92(2)
5 The Cyber Security Law: Fuzzy Logic in a Touchstone Law
94(35)
5.1 Background: Initial Drafting, Consultation then Delayed Implementation
96(2)
5.2 The Law: Vague Regulations Make Compliance Difficult
98(9)
5.2.1 Vague Rules: To Whom Does the Law Apply?
98(4)
5.2.2 Vague Rules: Data Localisation (Data Storage Requirements and Data Exits)
102(3)
5.2.3 Vague Rules: Unclear Product Review Requirements
105(2)
5.3 Backdoors under the Cyber Security Law?
107(3)
5.4 Third Parties in Security Reviews under the Cyber Security Law
110(5)
5.5 Evolving and Contradictory Subordinate Regulations on Data Transfers and Network Security
115(3)
5.6 Unresolved Issues: The Current Status of Cross-Border Data Flows under Article 37 of the Cyber Security Law
118(6)
5.6.1 `Important Data'
121(1)
5.6.2 `Network Operators' Remains Broad and Undefined
122(2)
5.7 Conclusion: Fuzzy Logic, Even in a Touchstone Law
124(5)
PART II Impact on Artificial Intelligence
6 The Impacts of Data Localisation on Globalised Ecosystems and Chinese Tech
129(25)
6.1 Background
130(3)
6.2 What Is Data Localisation?
133(1)
6.3 Two Major Motivations for Data Localisation: Protecting Personal Data and Ensuring Government Control over Data
133(4)
6.4 Existing Theories about Data Localisation Laws
137(10)
6.4.1 Arguments against Data Localisation Laws: Protectionism versus Data Protection
138(3)
6.4.2 Data Localisation Is `Technically Unviable' and Counterproductive to Data Protection Goals and National Security Concerns
141(3)
6.4.3 Increased Costs for Companies and Consumers
144(3)
6.5 Implications of the Rise of AI: Fuzzy Logic Masks Motivations for Data Localisation
147(5)
6.6 Conclusion: Costs-Benefits Can Change
152(2)
7 Data Protection but Not Data Privacy: `Data Protection Shall Not Hinder AI'
154(55)
7.1 Background: New Data Protection Regime Still Emerging
155(4)
7.1.1 Increased Data Protection under the Cyber Security Law
159(1)
7.2 Enforced Real-Name User Registration
159(7)
7.2.1 Real-Name User Registration
161(3)
7.2.2 Data Protection, not Privacy
164(2)
7.3 Data Protection a Key Social Issue, among Many `Trust' Scandals
166(9)
7.4 Polling: Growing Awareness of Data Privacy Issues
175(2)
7.5 BATs and Other Tech Firms Face Regular Data Protection Penalties, but Push Back against Authorities
177(3)
7.6 Privacy Standards Follow the Cyber Security Law on `Data Protection'
180(7)
7.6.1 What Is Protected Personal Information?
185(1)
7.6.2 What Were the Drafters of the Original Privacy Standards Intending?
186(1)
7.7 Definitional Fuzzy Logic in the Privacy Standards: Fuzzy Logic for Applying the standards
187(5)
7.7.1 `Sensitive Personal Information' and `Core Business Functions'
189(3)
7.8 Periodic Data Protection Impact Assessments
192(2)
7.9 2021: China's Data Security Law and Personal Information Protection Law to Become Fuzzy Logic Law?
194(7)
7.9.1 Consent and Storage of `Sensitive Personal Information'
196(1)
7.9.2 Data Localisation Expanded in 2021 and Beyond?
197(4)
7.10 Real-Name Registration, AI Development and Why Private Companies Control China's Datasets
201(6)
7.11 Conclusion: Inherent Fuzzy Logic Leading to Data Privacy Contradictions That May Benefit AI Development
207(2)
8 The Current State of AI Research Is Perfectly Suited to China's Fuzzy Logic System
209(51)
8.1 Why Has AI Developed So Quickly in China? The Current State of AI
213(8)
8.2 An AI `Sputnik Moment' for China
221(2)
8.3 AI Research Is Collaborative, Providing the Ideal Environment for China to Establish Pilot Rollouts
223(4)
8.4 Why Has AI Developed So Quickly in China? Private Firm/Government Symbiosis and Public--Private Petri Dishes
227(5)
8.5 Smart Cities as Petri Dishes for AI Development
232(6)
8.6 Incorporation of AI into Smart City and Innovation Policies: The AI Plan
238(5)
8.7 The AI Plan and Smart City Policies as Top-Down Signalling
243(4)
8.8 The Role of Public--Private Partnerships in China's National AI Platforms
247(4)
8.9 Public--Private Standard Setting and Interoperability
251(3)
8.9.1 Questions Remain Regarding the AI National Team
252(2)
8.10 Local Government Responses to Central Top-Down Signalling
254(2)
8.11 Will Network Sovereignty Threaten AI Development in China?
256(2)
8.12 Conclusion: Public--Private Symbiosis
258(2)
9 Open-Source AI Platforms and the Cyber Security Law
260(69)
9.1 What Are Open-Source AI Platforms?
262(3)
9.2 History of Open-Source Platforms in China
265(10)
9.3 Benefits of Open-Source Platforms for Innovation in AI
275(11)
9.3.1 Attracting Talent through Open Innovation
276(2)
9.3.2 Transparency: Researchers Demand Repeatability
278(4)
9.3.3 Cloud Computing Onboarding
282(3)
9.3.4 Maintenance and Crowdsourced Innovations
285(1)
9.4 Global Nature of Open-Source AI Platforms and Role of Global R&D Centres in AI Development in China
286(7)
9.4.1 Global R&D Centres
289(4)
9.5 Chinese Government Approach to Open-Source AI Platforms: Public--Private Platforms for Domestic Open Innovation
293(8)
9.5.1 The `Open-Source' Aspects of the National AI Platforms
293(8)
9.6 Key Features of Open-Source AI Relevant to Applying the Cyber Security Law
301(5)
9.7 Case Studies of Open-Source AI Platforms in China
306(20)
9.7.1 Apollo: `Android for Automated Vehicles'
313(5)
9.7.2 Apollo's Data-Sharing Policies
318(4)
9.7.3 GPS Mapping Laws: Network Sovereignty as Economic Protectionism?
322(4)
9.8 Conclusion: Linked Open-Source Ecosystems?
326(3)
Conclusion: Effect of Data Localisation on Chinese AI Innovation
329(14)
10.1 Fuzzy Logic
330(5)
10.1.1 `Important Data' Remains Undefined in 2021
330(2)
10.1.2 Concluding Remark: Fuzzy Logic Is Intentional
332(3)
10.2 Future Uncertainties
335(8)
10.2.1 Potential Future Developments in AI Policymaking
336(2)
10.2.2 Future Impact of Fuzzy Logic Regulatory Practice on Tech Firms and Entrepreneurs
338(5)
Bibliography
343(59)
A Journal Articles
343(7)
B Books
350(4)
C Reports
354(2)
D Other Secondary Sources: English Language
356(32)
E Other Secondary Sources: Chinese Language
388(7)
F Chinese Laws
395(1)
G Chinese Regulations, Notices, Guides and Standards
396(3)
H Chinese Policies, Plans and White Papers
399(1)
I Other Legislation
400(2)
Index 402
Max Parasol is a Research Fellow at UNSW Sydney, researching FinTech. He is a qualified lawyer with extensive experience working in Private Equity. He completed a PhD from the University of Technology Sydney on the Chinese AI ecosystem. Previously he practised as a lawyer in Shanghai, Western Australia, and Victoria and completed a masters degree at Nanjing University/Johns Hopkins University in Chinese. As a Senior Fellow at Monash University, he created a unit about China's innovation ecosystem. He studied, researched and worked in China for more than five years and speaks, reads and writes Chinese.