Algorithmic Marketing and EU Law on Unfair Commercial Practices

Description

Artificial Intelligence (AI) systems are increasingly being deployed by marketing entities in connection with consumers’ interactions. Thanks to machine learning (ML) and cognitive computing technologies, businesses can now analyse vast amounts of data on consumers, generate new knowledge, use it to optimize certain processes, and undertake tasks that were previously impossible. Against this background, this book analyses new algorithmic commercial practices, discusses their challenges for consumers, and measures such developments against the current EU legislative framework on consumer protection. The book adopts an interdisciplinary approach, building on empirical findings from AI applications in marketing and theoretical insights from marketing studies, and combining them with normative analysis of privacy and consumer protection in the EU. The content is divided into three parts. The first part analyses the phenomenon of algorithmic marketing practices and reviews the main AI and AI-related technologies used in marketing, e.g. Big data, ML and NLP. The second part describes new commercial practices, including the massive monitoring and profiling of consumers, the personalization of advertising and offers, the exploitation of psychological and emotional insights, and the use of human-like interfaces to trigger emotional responses. The third part provides a comprehensive analysis of current EU consumer protection laws and policies in the field of commercial practices. It focuses on two main legal concepts, their shortcomings, and potential refinements: vulnerability, understood as the conceptual benchmark for protecting consumers from unfair algorithmic practices; manipulation, the substantive legal measure for drawing the line between fair and unfair practices. Acknowledgment Contents Abbreviations List of Tables Chapter 1: Some Preliminary Remarks 1.1 Marketing at the AI Turn 1.2 More Than Privacy: Commercial Fairness and Consumer Protection 1.3 A Contextual Definition of Artificial Intelligence 1.4 The Structure of the Book References Part I: Introducing Algorithmic Marketing Chapter 2: Algorithmic Marketing 2.1 Presenting the Algorithmic Marketing Concept 2.2 Algorithmic Marketing: A Brief History 2.2.1 Expert Systems, Expert Business 2.2.2 Database Marketing and the First Applications of Neural Networks 2.2.3 Software Agents in E-commerce 2.2.4 The Uptake of Big Data and Machine Learning: Data-Driven Advertising 2.2.5 Deep Learning and AI-Powered Marketing 2.3 Algorithmic Marketing: Main Technologies 2.3.1 Big Data 2.3.2 Machine Learning 2.3.2.1 Supervised Learning 2.3.2.2 Unsupervised Learning 2.3.2.3 Reinforcement Learning 2.3.3 Deep Learning 2.3.4 Natural Language Processing 2.3.5 Speech Recognition 2.3.6 Computer Vision 2.4 Algorithmic Marketing: Actors and Models 2.4.1 In-House AI 2.4.2 AI as a Platform 2.4.3 AI in Marketing and Advertising Services 2.4.4 AI as a Product References Part II: Algorithmic Marketing Practices Chapter 3: Data-Driven Surveillance 3.1 The New Marketing Research 3.1.1 Data Gathering and Exchanges 3.1.2 Profiling and Audience Creation 3.1.3 Scores and Other Predictions 3.2 Data Research Through the Prism of Surveillance 3.2.1 The Characteristics of Big Data Surveillance 3.2.2 Algorithmic Assemblage and the Production Paradigm 3.3 Commercial Surveillance and the Struggle for Privacy 3.3.1 Introducing Consumer Privacy 3.3.2 Consenting Privacy Away 3.3.3 The Economic Value of Personal Information References Chapter 4: Predictive Personalisation 4.1 The One-to-One Experience 4.1.1 Targeted Advertising 4.1.2 Recommendations 4.1.3 Dynamic Websites 4.2 Unveiling Personalisation 4.2.1 Persona and Personalisation 4.2.2 Control Through the Choice Interface 4.3 Challenges to Consumer Autonomy 4.3.1 Preference Formation and Autonomy Traps 4.3.2 Choice Traps, Dark Patterns, and Persuasion Profiling References Chapter 5: Empathetic Connection 5.1 The Two Faces of Empathetic Connection 5.2 Emotional Marketing 5.2.1 Psychographic Profiling 5.2.2 Sentiment Analysis 5.2.3 Emotion Analytics 5.3 The Problem of Emotional Monetisation 5.3.1 The New Hidden Persuaders 5.3.2 Strategies of Emotional Monetisation 5.4 Human-Like Communication 5.4.1 Chatbots 5.4.2 Voice Assistants 5.5 The Troubles with Voice Interfaces 5.5.1 The Power of Human 5.5.2 Entering the Private Sphere References Part III: Algorithmic Marketing and EU Law on Commercial Practices Chapter 6: EU Law on Unfair Commercial Practices 6.1 Commercial Practices on Trial 6.2 Introducing EU Law on Unfair Commercial Practices 6.3 Assessing the Business-Consumer Relationship 6.3.1 The Market-Based Rationale for Fairness 6.3.2 The Average and the Vulnerable Consumer 6.3.3 Professional Diligence and Self-regulation 6.4 Regulatory Disconnection: Plotting the Legal Analysis References Chapter 7: Digital Vulnerability 7.1 The Vulnerable Consumer in EU Law 7.1.1 The Initial Interest of Consumer Law in the Weaker Party 7.1.2 Vulnerability as a Social Concept for Marginalised People 7.1.3 Vulnerability as a Diminished Capacity of Certain Groups of Consumers to Deal with Commercial Practices 7.2 Vulnerability in the Directive on Unfair Commercial Practices 7.3 A Look at the Contemporary Discussion on Consumer Vulnerability 7.4 Layers of Digital Vulnerability 7.4.1 The Layer of Personal Characteristics 7.4.2 Situational Layers 7.4.3 The Privacy Layer 7.4.4 The Architectural Layer 7.5 Policy Implications References Chapter 8: Algorithmic Manipulation 8.1 A Renewed Interest in Regulating Market Manipulation 8.2 Manipulation and EU Consumer Law: The Quest for a Principle of Consumer Autonomy 8.3 Algorithmic Marketing and the UCPD: Material Distortion 8.4 Algorithmic Marketing and the UCPD: Misleading Practices 8.4.1 Misleading Data Practices 8.4.2 Misleading Personalization 8.4.3 Misleading Practices and Emotions 8.5 Algorithmic Marketing and the UCPD: Aggressive Practices 8.5.1 Algorithmic Undue Influence 8.5.2 Digital Harassment and Privacy 8.6 The Requirement of Professional Diligence 8.7 Legal Enforcement 8.7.1 Barriers to Enforcement 8.7.2 The Perspective of Reversing the Burden of Proof 8.8 Policy Implications References Chapter 9: EU Law on Fair Trading 2.0: A New Hope 9.1 A Future To Be Avoided 9.2 Algorithmic Marketing and the Potential Implications of the AIA, DSA, and DMA Proposals 9.3 The Unfair Commercial Practices Directive: De Lege Lata and De Lege Ferenda References