Regulating Artificial Intelligence (eBook)

Thomas Wischmeyer, Timo Rademacher (Herausgeber)

eBook Download: PDF

2019 | 1st ed. 2020
XIV, 388 Seiten
Springer International Publishing (Verlag)
978-3-030-32361-5 (ISBN)

Infos

This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that currently shape or restrict the design or use of AI, and develops policy recommendations for those areas in which regulation is most urgently needed. By gathering contributions from scholars who are experts in their respective fields of legal research, it demonstrates that AI regulation is not a specialized sub-discipline, but affects the entire legal system and thus concerns all lawyers. 

Machine learning-based technology, which lies at the heart of what is commonly referred to as AI, is increasingly being employed to make policy and business decisions with broad social impacts, and therefore runs the risk of causing wide-scale damage. At the same time, AI technology is becoming more and more complex and difficult to understand, making it harder to determine whether or not it is being used in accordance with the law. In light of this situation, even tech enthusiasts are calling for stricter regulation of AI. Legislators, too, are stepping in and have begun to pass AI laws, including the prohibition of automated decision-making systems in Article 22 of the General Data Protection Regulation, the New York City AI transparency bill, and the 2017 amendments to the German Cartel Act and German Administrative Procedure Act. While the belief that something needs to be done is widely shared, there is far less clarity about what exactly can or should be done, or what effective regulation might look like. 

The book is divided into two major parts, the first of which focuses on features common to most AI systems, and explores how they relate to the legal framework for data-driven technologies, which already exists in the form of (national and supra-national) constitutional law, EU data protection and competition law, and anti-discrimination law. In the second part, the book examines in detail a number of relevant sectors in which AI is increasingly shaping decision-making processes, ranging from the notorious social media and the legal, financial and healthcare industries, to fields like law enforcement and tax law, in which we can observe how regulation by AI is becoming a reality.

Thomas Wischmeyer is an assistant professor for public law and information law at the University of Bielefeld. He has been an academic visitor to several law schools, including Yale Law School and the Jean Monnet Center of New York University School of Law. Thomas Wischmeyer publishes and teaches on European and German constitutional law, administrative law and legal theory. His current research focuses on IT security and the role of law in the information society. 

Timo Rademacher is Assistant Professor of Public Law and New Technologies at the University of Hannover. He has obtained his degrees - inter alia - from the Universities of Heidelberg (Dr. iur.) and Oxford (MJur). In Hannover, he publishes on and teaches European and German constitutional and information law. His current research aims at the development of a regulatory framework for the use of Big Data analytics by State and EU public bodies.

Inhalt

Preface: Good Artificial Intelligence 5
Mission and Methodology 5
Artificial Intelligence 6
Structure and Content 7
References 9
Contents 10
Contributors 12
Artificial Intelligence as a Challenge for Law and Regulation 14
1 Fields of Application for Artificial Intelligence 15
2 Levels of Impact 16
3 Legal Aspects 18
4 Modes of Governance 19
5 Exercising the State´s Enabling Responsibility Through Measures for Good Digital Governance 20
5.1 Displacements in the Responsibility of Public and Private Actors 20
5.2 Innovative Case-law as an Example 22
5.3 System Protection 23
5.4 Systemic Protection 24
5.5 Regulatory Guidelines 24
5.6 Regarding Regulatory Possibilities 25
6 Obstacles to the Effective Application of Law 27
6.1 Openness to Development 27
6.2 Insignificance of Borders 28
6.3 Lack of Transparency 30
6.4 Concentration of Power 30
6.5 Escaping Legal Constraints 31
7 Types of Rules and Regulations 31
7.1 Self-structuring 32
7.2 Self-imposed Rules 32
7.3 Company Self-regulation 33
7.4 Regulated Self-regulation 33
7.5 Hybrid Regulation 35
7.6 Regulation by Public Authorities 35
7.7 Techno-regulation 36
8 Replacement or Supplementation of Legal Measures with Extra-Legal, Particularly Ethical Standards 36
9 On the Necessity of Transnational Law 37
References 38
Part I: Foundations of Artificial Intelligence Regulation 43
Artificial Intelligence and the Fundamental Right to Data Protection: Opening the Door for Technological Innovation and Innova... 44
1 The Objective of the Chapter: `Opening the Door´ 45
2 Why a Door Needs to Be Opened 46
2.1 The Traditional Basic Concept of Data Protection Law: Strict Limits for the Use of AI 46
2.2 Constitutionalisation of a Non-constitutional Regulatory Model: The Right to Informational Self-determination in Germany a... 49
Innovation of the Fundamental Rights by Using a Regulatory Model of Ordinary Law 49
Distinction Between the Legal Construction and the Theoretical Concept: The Right to Informational Self-determination as an In... 50
Supra-individualistic Elements in the Jurisprudence of the Federal Constitutional Law 51
2.3 Interim Conclusion 52
3 How the Door Can Be Opened 53
3.1 Article 8 CFR as an Obligation of the Legislator to Regulate Data Processing, Not as a Right to Informational Self-determi... 54
Wording and History of Legislation 54
Structure 55
Article 8 as a Modern Fundamental Right to Data Protection: Combination of Openness to Innovation and Effective Protection 56
3.2 Looking at the CJEU: The Window of Opportunity 58
4 No Door Without a Frame: The Legislator and Legal Scholarship Have a Responsibility 59
4.1 Legislator: Framing AI 59
4.2 Legal Scholarship: Plea for More Bottom-up Research 61
References 61
Artificial Intelligence and Autonomy: Self-Determination in the Age of Automated Systems 64
1 Introduction and Practical Applications 65
1.1 Health or Life Insurance and Health Status 65
1.2 Financial Transactions and Financial Creditworthiness 66
1.3 Chinese Social Credit System and Personal Behaviour in General 67
2 Potential Risks from Automated Systems on Self-Determination 68
2.1 The Function of Automated Systems 68
2.2 Concrete Structures of Risks 69
Potential to Influence Automated Decisions in General 69
Approximation and Standardisation 71
Lack of Comprehensibility 72
3 Legal Framework Conditions: Individual Self-Determination 73
3.1 Legally Affected Rights 73
3.2 Requirement of Legal Regulation or Personal Responsibility? 74
4 Possibilities for Legal Responses 75
4.1 Instruments with Direct Effect 75
Preliminary Question: The Legal Relevance of Influencing People 75
Illegal Influences in the Sense of the Unfair Commercial Practices Directive 76
Randomly Appearing Criteria: Relevance of a Reasonable Expectation Horizon 78
Factual Criteria: Profiling and Consent 79
4.2 Instruments with Indirect Effect 81
References 82
Artificial Intelligence and Transparency: Opening the Black Box 85
1 Introduction 86
2 Generating Knowledge Through Access to Information 89
2.1 Epistemic Constraints 90
2.2 Normative Constraints 92
2.3 Functional Constraints 95
3 Creating Agency Through Explanations 97
3.1 Causal Explanations 98
3.2 Counterfactual Explanations 100
3.3 Explanations in Context 102
4 The Way Forward 103
4.1 Principles 103
4.2 Practice 104
References 107
Artificial Intelligence and Discrimination: Discriminating Against Discriminatory Systems 112
1 Introduction 113
2 Discriminatory Systems? 113
2.1 Flawed Data Collection 114
2.2 Flawed Data Aggregation 115
2.3 Normative Unresponsiveness 115
3 Current Antidiscrimination Law Doctrine and AI 118
3.1 From Causality to Correlations 118
Imputed Causality 119
Indirect Discrimination 120
3.2 Statistics on Statistics 122
4 Towards a Paradigm of Knowledge Creation 124
4.1 A Need for Concepts 124
4.2 A Need for Facts 125
4.3 Statistics in Court 126
5 Conclusion 127
References 128
Artificial Intelligence and Legal Personality: Introducing ``Teilrechtsfähigkeit´´: A Partial Legal Status Made in Germany 131
1 Introduction 132
2 The `Dual Dilemma´ 133
2.1 The Case for Agency 133
2.2 The First Dilemma 135
2.3 The Case for Legal Personality 136
Contract Formation 137
Torts 138
2.4 The Second Dilemma 140
3 A `Halfway Status´ Made in Germany: Introducing Teilrechtsfähigkeit 141
3.1 Teilrechtsfähigkeit 141
3.2 Teilrechtsfähigkeit for Intelligent Agents 144
Contract Formation and Torts 144
Side Note: Criminal Law 146
4 Of Mice and Machines 147
5 Conclusion 148
References 149
Part II: Governance of and Through Artificial Intelligence 151
Artificial Intelligence and Social Media 152
1 Of Arms Races and Filter Biases 153
2 Phenomenology 156
2.1 Key Features of Social Media 156
2.2 Social Media AI 157
3 Concepts of Social Media Regulation 158
4 Protective Social Media Regulation 159
4.1 Communication Through AI As an Exercise of Fundamental Rights 160
4.2 Restricting AI-Based Communication on Social Media Services 162
Grounds for Restriction 163
Means of Restriction 165
4.3 Responsibilities of Social Media Providers 166
Responsibility for Unwanted Content (`Output-Responsibility´) 167
Responsibility for Unwanted Blocking (`Input-Responsibility´) 170
5 Facilitative Social Media Regulation 173
5.1 Purposes and Instruments of Facilitative Regulation of Social Media AI 174
5.2 Constitutional Framework of Facilitative Regulation of Social Media AI 175
6 Conclusion 177
References 178
Artificial Intelligence and Legal Tech: Challenges to the Rule of Law 181
1 Introduction 182
2 Fields of Application 183
2.1 Definitions 183
2.2 Legal Tech in Private Use: Status Quo and Trends 185
2.3 Legal Tech in Public Use: Status Quo and Trends 186
3 Conceptual Differences Between `Law´ and `Code´ 188
3.1 Application of the Law As a Social Act 188
3.2 Code As a Technical Act 189
3.3 Misconceptions of `Code´ 190
3.4 Need for Regulation 191
4 Constitutional Framework 191
4.1 Rule of Law and Democracy 191
4.2 Right to Privacy 193
4.3 Right to Non-discrimination 195
5 Proposals for `Regulation by Design´: A Balancing Act 196
5.1 Regulatory Realignment 196
5.2 Legal Protection by Design As a Starting Point 197
5.3 Regulatory Guidelines 198
5.4 The `Human Factor´ 200
5.5 Balancing Act 200
6 Conclusion 201
References 202
Artificial Intelligence and Administrative Decisions Under Uncertainty 205
1 Introduction 206
2 Frictions: Machine Learning Versus Administrative Law 207
2.1 Investigation 208
2.2 Prediction 209
2.3 Decision 210
3 Challenges: Machine Learning and Administration Under Uncertainty 211
3.1 Generalizability 212
Neglect of Selection Effects 212
The Bias-Variance-Tradeoff and Bias Aversion 213
3.2 Counterfactual Reasoning 216
Experimental Administration 216
Pseudo-Causal Explanations 217
3.3 Error Weighting 219
3.4 Proportionality 220
3.5 Gaming 223
3.6 Complexity 224
4 Conclusion 225
Appendix 226
References 227
Artificial Intelligence and Law Enforcement 230
1 Introduction: Smart Law Enforcement 231
2 The Status Quo of Smart Law Enforcement 232
2.1 `Watching´ 232
2.2 `Reading´ 234
2.3 `Listening´ 236
2.4 `Smelling´ 236
2.5 Everywhere, Always, and Remembering It All 237
3 Constitutional Frameworks 237
3.1 Germany 238
3.2 European Union 241
3.3 United States 243
4 Three Core Issues 246
4.1 A Challenge: State-of-the-Art Information or Undemocratic In-Formation? 248
4.2 A Chance: Biased Enforcement or Transparent Biases? 251
4.3 A Choice: Human or `Perfect´ Enforcement of the Law? 252
5 Conclusion 255
References 255
Artificial Intelligence and the Financial Markets: Business as Usual? 260
1 AI in the Financial Markets 261
1.1 Business-Customer-Relations: `Robo-advisers´ 261
1.2 Financial Markets and Institutions: `Cyborg Finance´ 263
1.3 Compliance: `RegTech I´ 265
1.4 New Players: `FinTech´ 266
2 Regulatory Approaches Towards AI in the Financial Markets 267
2.1 Global Level 267
2.2 European Level 268
2.3 National Level 269
United States 269
Germany 270
United Kingdom 271
3 Governance Through and of AI in the Financial Markets 272
3.1 Regulation and Supervision Through AI: `RegTech II´ 273
Supervision: `Robocops´ 273
Regulation: `Machine Readable and Executable Rulebook´ 273
3.2 Vital Aspects of Future AI Governance 274
Assigning Responsibility 274
Redefining Systemic Relevance 275
Insisting on Auditability 275
Adapting Reporting and Disclosure 275
Reducing Regulatory Arbitrage 276
Consumer Protection 276
Regulatory Independence 277
4 AI and the Financial Markets: To a New Tomorrow 277
4.1 First-Mover Advantages 278
4.2 Yesterday´s Mistakes 278
References 279
Artificial Intelligence and Public Governance: Normative Guidelines for Artificial Intelligence in Government and Public Admin... 282
1 A Design Challenge for Government and Administration in Germany 283
1.1 The Definition of Artificial Intelligence 283
1.2 AI Applications in Government and Administration 285
2 Points of Reference: Between Ethics and Politics 287
3 Guidelines 288
3.1 Law 288
Motivation, Limitation and Design 288
The New Legislation on Automated Administrative Decisions 290
3.2 Technology 291
3.3 Organization 291
3.4 Strategies 293
3.5 Visions 294
4 Outlook 295
References 295
Artificial Intelligence and Taxation: Risk Management in Fully Automated Taxation Procedures 299
1 Introduction 300
2 Legal Bases 300
2.1 Fully Automated Taxation Procedure 300
2.2 Risk Management Systems 302
2.3 Compatibility of Confidentiality Requirements with Basic Data Protection Regulations 303
3 The Use of AI Within RMS 304
3.1 Suitability of AI Within RMS 305
3.2 Controlling AI-based RMS 307
4 Conclusion 308
References 308
Artificial Intelligence and Healthcare: Products and Procedures 311
1 A Brief Case Study 312
2 Legal Framework: European Medical Devices Law in a Nutshell 314
3 Medical Device Term, Section 3 No. 1 MPG 315
3.1 Physiological Component 316
3.2 Mechanism of Action 317
3.3 Intended Purpose 317
4 Market Access Regulation of Software As a Medical Device 318
4.1 Categories of Medical Software 318
Embedded Software 319
Stand-Alone Software 319
Accessories on Medical Devices 320
Software for General Purposes 321
Subject of Monitoring Under Medical Devices Law 322
4.2 Classification Rules 322
Risk Classes 322
Risk Dimensions of Software As a Medical Device 324
In Particular: Classification of Stand-Alone Software 326
4.3 Control-Related Process Modules 328
5 Post Market-Entry Surveillance of Software As a Medical Device 330
5.1 Statutory Provisions of the MPG 331
5.2 Challenging Information Issue 332
Emergence of the Information Deficit 332
The Amendments by the MDR As a Solution Approach? 333
6 Outlook 336
References 336
Artificial Intelligence in Healthcare: Doctors, Patients and Liabilities 340
1 Introduction: Artificial Intelligence in Medicine 341
1.1 Applications of Artificial Intelligence in Medicine and Their Benefits and Limitations 341
1.2 A Particular Definition for AI in Medicine: Evidence or Reason? 342
2 AI´s Influence on the Status and Role of Physicians and Patients in Their Relation to Each Other in Medical Ethics 345
2.1 The Physician-Patient Relationship in Medical Ethics 345
2.2 Principles of Medical Ethics and Their Implementation in the Physician-Patient Relationship 346
2.3 Challenges Presented by AI in Medical Ethics 347
3 AI´s Influence on the Status and Role of Physicians and Patients in Their Relation to Each Other in Liability Law 350
3.1 Issues of Medical Malpractice Law 351
3.1.1 Informed Consent, Liability for Lack of Information 351
3.1.2 Liability for Errors in Treatment and the Burden of Proof 353
3.2 Issues of Product Liability Law 356
3.3 Conclusions Based on Liability Law 357
4 The Status and Role of Physicians in Their Relation to Patients 358
References 361
Artificial Intelligence and Competition Law 364
1 Introduction 365
2 Artificial Intelligence 366
2.1 Definition(s) 367
2.2 The Current Legal Framework 367
3 Artificial Intelligence and Its Challenges for Competition Law 368
3.1 Market Definition 368
The Competition for AI 368
The Competition with AI 369
3.2 Market Dominance 370
The Ninth Amendment of the German ARC 2017 370
`Data Power´ 371
Transparency of Market-Related Information 372
3.3 Abuse of Market Power 374
Standard-Essential Know-How 374
The Use of AI 375
3.4 Prohibition of Cartels and Other Anti-Competitive Agreements 376
Exchange of Information and Hub-and-Spoke-Scenarios 377
`Agreements´ Between AI Systems 378
3.5 Merger Control 378
3.6 Liability 379
3.7 Conclusions 381
Public Enforcement and the Future Legal Framework 381
Responsibility for Anti-Competitive Behavior 382
`Duty to Maintain Safeguards´ or `Störerhaftung´ in Competition Law? 383
Legal Personality of AI Systems 385
References 386

Produkt-Details

• Erscheint lt. Verlag: 29.11.2019
• Zusatzinfo: XIV, 388 p. 1 illus.
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Recht / Steuern ► Allgemeines / Lexika
• Themenwelt: Recht / Steuern ► EU / Internationales Recht
• Themenwelt: Recht / Steuern ► Öffentliches Recht
• Schlagworte: AI regulation • Algorithmic Transparency • algorithms • Anti-Discrimination Law • Artificial Intelligence • internet of things • Legal Tech • Predictive Policing • privacy • Social Media Algorithms
• ISBN-10: 3-030-32361-7 / 3030323617
• ISBN-13: 978-3-030-32361-5 / 9783030323615