Algorithmic Regulation and Personalized Law
A Handbook
Zusammenfassung
This Handbook explores the ways in which the use of big data analytics and artificial intelligence could recalibrate the relationship between law and individuality and change the foundational structures of our legal systems. In this perspective, the volume contributes to the emerging literature on "granular law" or "personalized law". Bringing together contributions by eminent scholars from both sides of the Atlantic, it aims to serve both as a gateway to this emerging and promising field and as a catalyst for new scholarly research. In particular, this Handbook explores the concept of personalized law, its implementation in contract, consumer and tort law, as well as the related implications for behavioural sciences, smart contracts, non discrimination and enforcement.
Abstract
This Handbook explores the ways in which the use of big data analytics and artificial intelligence could recalibrate the relationship between law and individuality and change the foundational structures of our legal systems. In this perspective, the volume contributes to the emerging literature on "granular law" or "personalized law". Bringing together contributions by eminent scholars from both sides of the Atlantic, it aims to serve both as a gateway to this emerging and promising field and as a catalyst for new scholarly research. In particular, this Handbook explores the concept of personalized law, its implementation in contract, consumer and tort law, as well as the related implications for behavioural sciences, smart contracts, non discrimination and enforcement.
- I–XV Titelei/Inhaltsverzeichnis I–XV
- 1–4 Introduction: Personalization and Granularity of Legal Norms in the Data Economy: A Transatlantic Debate (Busch/De Franceschi) 1–4
- 5–114 Part 1: The Concept of Personalized Law 5–114
- 5–53 A. Personalizing Default Rules and Disclosure with Big Data (Porat/Strahilevitz) 5–53
- I. Introduction
- II. Theories of personalized default rules
- 1. Contract law default rules
- 2. Majoritarian default rules
- 3. Minoritarian (or penalty) default rules
- 4. Third-party effects
- III. The feasibility of personalized default rules
- 1. Big Data and Big Five
- 2. Big Data in the law
- 3. Big Data guinea pigs
- IV. Possible Objections and Limitations
- 1. Cross Subsidies
- 2. Strategic Behavior
- 3. Abuse by Merchants
- 4. Uncertainty
- 5. Case law Fragmentation
- 6. Statistics, Stereotyping, and Valuable Default Rules
- 7. Subordination, adaptive preferences, and personalization
- 8. Privacy
- 9. “But I Can Change!” and opting in
- V. Personalized disclosure
- VI. Conclusion
- 54–97 B. Personalizing Negligence Law (Ben-Shahar/Porat) 54–97
- I. Introduction
- II. Personalized negligence under existing law
- 1. Diminished capacity
- 2. Elevated capacity
- 3. Resource-based personalization
- 4. Personalization through insurance?
- 5. Summary
- III. The efficiency of personalized standards
- 1. Levels of care
- 2. Levels of activity
- 3. Victim care
- 4. Ex ante investment in improving private characteristics
- 5. Summary
- IV. Justice considerations
- 1. Corrective justice
- 2. Distributive justice
- V. Broadening personalization
- 1. Procedures for implementing personalized standards
- 2. Which personal information?
- VI. Conclusion
- 98–114 C. The Death of Rules and Standards (Casey/Niblett) 98–114
- I. Introduction
- II. The emergence of microdirectives and the decline of rules and standards
- 1. Background: Rules and standards
- 2. Technology will facilitate the emergence of microdirectives as a new form of law
- 3. Examples
- 4. The different channels leading to the death of rules and standards
- III. Conclusion
- 115–184 Part 2: Critique and Theoretical Perspectives 115–184
- 115–136 D. The Law between Generality and Particularity. Chances and Limits of Personalized Law (Grigoleit/Bender) 115–136
- I. Introduction
- II. Distinctions and notional specifications
- 1. Technology-related specifications
- 2. Law-related specifications
- III. Evolutionary perspectives
- 1. Torts: The reasonable standard of care
- 2. Contracts
- IV. Revolutionary perspectives
- 1. The digital revolution as a factual phenomenon
- 2. Limitations to changes of the very structure of the legal system
- V. Conclusions
- 137–154 E. Granular Norms and the Concept of Law: A Critique (Auer) 137–154
- I. The Inevitability of Legal Typification
- II. The Problem of Algorithmic Discrimination
- III. The Scope of Granular Law and the Rise of Consumerism
- IV. Regulation and the Rule of Law
- V. Granularization and the Problem of Rule-Following
- 155–171 F. Logopoeia: Normative Typification and Granular Norm’s Informational Differentiation (Femia) 155–171
- I. More acts or more words: negotia, pragmata, activities
- II. Two ways of grasping reality: taming the chaos with Emilio Betti and Tullio Ascarelli
- III. End of the journey among the concepts’ penumbra. From type to typification, and from typification to dissemination
- IV. Big data: quantities make a qualitative shift in nomogenesis
- V. Nomogenesis at the intersection point between normative technique and informational limit
- VI. The loss of informational innocence
- VII. Norms on the move
- VIII. Les communications & les commerces
- IX. Politics or Algorithmics
- 172–184 G. “Granularization” and Cross-Subsidies: Liberal, Neoliberal and Socialist Perspectives (Denozza/Maugeri) 172–184
- I. Granularization: a consistent outcome of a neoliberal trend
- II. The costs of granularization: the many shortcomings of algorithmic governmentality
- III. Liberal general principles v. neoliberal “granularized” rules
- IV. Is granularization efficient? Abstraction and totality in neoliberal thought
- V. Granularization and cross subsidy
- VI. What’s wrong, if anything, with cross-subsidy?
- 185–240 Part 3: Personalization in Contract, Consumer and Tort Law 185–240
- 185–202 H. ‘Granular Legal Norms’ in the Financial Services Trade (Sirena) 185–202
- I. The advent of a digital law
- II. The trend towards the personalization of private law: from the ‘average consumer’ to the ‘images of the consumer’
- III. The discourse on granular legal norms (particularly with regard to the duties of disclosure provided by European contract law)
- IV. The personalization of financial services
- 1. The know-your-customer rule in investment services
- 2. The know-your-customer rule in insurance services
- 3. The know-your-customer rule in credit banking
- V. Some final remarks
- 203–220 I. De- or Re-typification through Big Data Analytics? The Case of Consumer Law (Micklitz) 203–220
- I. Clarification and Argument
- II. From Typification to Granularization prior to Big Data Analytics
- 1. Consumer images
- 2. Consumer law 2.0
- 3. Contractual underworld
- 4. Consumerization of consumer law
- III. From Granularization to Personalization through Big Data Analytics
- 1. Digitalization
- 2. Big data analytics
- IV. Big Data Analytics in Law Making and Law Enforcement
- 1. Evidence based policy through big data analytics
- 2. Shortcomings of statistics
- V. Prospects for big data analytics in consumer law
- 1. Information rights and obligations
- 2. Reducing the complexity of information through big data analytics
- 3. Complexities of consumer law enforcement
- 4. Reducing complexity of enforcement through big data?
- VI. Big Data Analytics and Re-typification
- 221–235 J. Personalization of the Law and Unfair Terms in Consumer Contracts (Patti) 221–235
- I. Introduction
- II. The setting within the European context
- 1. The theoretical framework
- 2. The European methodology
- 3. A personalized approach?
- III. The role of personalized law
- 1. Personalized default rules
- 2. Personalized Mandatory Rules
- IV. The enforcement
- V. Conclusion
- 236–240 K. Personalization of Tort Law? (von Bar) 236–240
- 241–292 Part 4: Technological and Behavioral Perspectives 241–292
- 241–263 L. Personalized Law and the Behavioral Sciences (Hacker) 241–263
- I. A very short introduction to behavioral law and economics
- 1. Behavioral economics
- 2. Legal applications
- II. The knowledge problem in behavioral law and economics
- 1. Uncertainty about the true rationality of market actors
- 2. Psychometrics and the quantification of bias
- 3. Personalized law as a solution to the knowledge problem
- III. Examples of personalized behavioral law
- 1. Disclosures
- 2. Default rules
- 3. Mandatory law
- IV. The limits of personalized behavioral law
- 1. The strength of empirical correlations
- 2. Algorithmic bias and discrimination
- V. Good governance of personalized behavioral law
- 1. Privacy respecting metrics
- 2. Oversight and algorithmic auditing
- VI. Conclusion
- 264–278 M. “Smart Contract”, “Granular Norms” and Non-Discrimination(Zeno-Zencovich) 264–278
- I. Only words
- II. How “smart” can contracts be?
- III. Creditworthiness
- IV. “Granular norms”
- V. Non-discrimination in the age of big data
- 279–292 N. Algorithmic Regulation and (Im)Perfect Enforcement in the Personalized Economy (Busch) 279–292
- I. Introduction
- II. Big Data and the Crisis of Generalities
- III. Making Laws for the Personalized Economy
- 1. Granular Legal Norms: The Demise of Typifications?
- 2. Use Cases of Personalized Law
- 3. Fighting Fire with Fire: Adverse Targeting meets Personalized Law
- IV. Governance of Algorithms for Personalized Law
- 1. Personalized Law as Algorithmic Regulation
- 2. Privacy and Choice
- 3. Quality of Data and Models
- 4. Compliance Monitoring and Algorithmic Auditing
- V. Conclusion
