The 2021 yearbook of the digital ethics lab / / edited by Josh Cowls, Jessica Morley

• Pubblicazione: Cham, Switzerland : , : Springer, , [2021]; ©2021
• Descrizione fisica: 1 online resource (230 pages)
• Disciplina: 303.4
• Soggetto topico: Computer science - Moral and ethical aspects; Information technology - Moral and ethical aspects; Artificial intelligence - Moral and ethical aspects
• Persona (resp. second.): CowlsJosh; MorleyJessica
• Nota di contenuto: Intro -- Contents -- Contributors -- Chapter 1: Introduction -- Chapter 2: Are the Dead Taking Over Instagram? A Follow-up to Öhman & -- Watson (2019) -- 1 Introduction -- 2 Data -- 3 Methodology -- 4 Uncertainty -- 5 Findings -- 6 Discussion -- 7 Conclusion -- References -- Chapter 3: Emotional Self-Awareness as a Digital Literacy -- 1 Introduction -- 2 What Is Emotional-Self-Awareness? -- 3 Social and Emotional Learning -- 4 Digital Literacy -- 5 Towards a More Individualized Digital Literacy -- 5.1 Consuming Digital Information -- 5.2 Creating Digital Information -- 5.3 Learning About Digital Information -- 6 Conclusion -- References -- Chapter 4: The Marionette Question: What Is Yet to Be Answered about the Ethics of Online Behaviour Change? -- References -- Chapter 5: On the Limits of Design: What Are the Conceptual Constraints on Designing Artificial Intelligence for Social Good? -- 1 Introduction -- 2 The Philosophy of Information and the Logic of Design -- 3 Artificial Intelligence and Design for Social Good -- 4 Collective Action Problems and the Internal Constraints on Design -- 5 Cosmos, Taxis and the External Constraints on Design -- 6 The Pilgrim's Progress -- 6.1 Holistic Design -- 6.2 Dual System Approach -- 6.3 Gradual Implementation -- 6.4 Tolerant Design -- 6.5 Design for Serendipity -- 7 Conclusions -- References -- Chapter 6: AI and Its New Winter: From Myths to Realities -- References -- Chapter 7: The Governance of AI and Its Legal Context-Dependency -- 1 Introduction -- 2 Models of Legal Regulation -- 3 A Bunch of Laws for AI -- 4 Legal Context-Dependency -- 5 Models of Governance for AI -- 6 Conclusions -- References -- Chapter 8: How to Design a Governable Digital Health Ecosystem -- 1 Introduction -- 2 A Systemic Approach -- 2.1 Fairness at the Systems Level -- 2.2 Accountability and Transparency at the Systems Level. ; 3 A Proactive Approach to Ethical Governance -- 3.1 Data Access: Collectively Tackle the Issues of Confidentiality and Consent for the Public Good -- 3.2 Data Protection: Enable Competition to Ensure Fair Return on Data Investment -- 3.3 Accountability: Reframe Regulation as an Enabling Service -- 3.4 Evidence: Invest in "Safe" Environments for Experimentation -- 4 Keeping Society-in-the-Loop -- 5 Conclusion -- References -- Chapter 9: Ethical Guidelines for SARS-CoV-2 Digital Tracking and Tracing Systems -- 1 The Ethical Risks of COVID-19 Digital Tracking and Tracing Systems -- 2 Guidelines for Ethically Justifiable Design and Development of Digital Tracking and Tracing Systems -- 3 Only One Chance to Get It Right -- References -- Chapter 10: On the Risks of Trusting Artificial Intelligence: The Case of Cybersecurity -- 1 Introduction -- 2 Trustworthiness and Trust -- 3 AI for Cybersecurity Tasks -- 4 The Vulnerability of AI -- 5 Making AI in Cybersecurity Reliable -- 6 Conclusion -- References -- Chapter 11: The Explanation Game: A Formal Framework for Interpretable Machine Learning -- 1 Introduction -- 2 Why Explain Algorithms? -- 2.1 Justice as (Algorithmic) Fairness -- 2.2 The Context of (Algorithmic) Justification -- 2.3 The Context of (Algorithmic) Discovery -- 3 Formal Background -- 3.1 Supervised Learning -- 3.2 Causal Interventionism -- 3.3 Decision Theory -- 4 Scope -- 4.1 Complete -- 4.2 Precise -- 4.3 Forthcoming -- 5 The Explanation Game -- 5.1 Three Desiderata -- Accuracy -- Simplicity -- Relevance -- 5.2 Rules of the Game -- Inputs -- Mapping the Space -- Building Models, Scoring Explanations -- 5.3 Consistency and Convergence -- 6 Discussion -- 7 Objections -- 7.1 Too Highly Idealised -- 7.2 Infinite Regress -- 7.3 Pragmatism + Pluralism = Relativist Anarchy? -- 7.4 No Trade-off -- 7.5 Double Standards -- 8 Conclusion -- References. ; Chapter 12: Algorithmic Fairness in Mortgage Lending: From Absolute Conditions to Relational Trade-offs -- 1 Introduction -- 2 Discrimination in Mortgage Lending -- 2.1 Legal Framework for Discrimination -- 3 Sources of Discriminatory Bias -- 3.1 Over-Estimation of Minority Risk -- 3.2 Under-Estimation of Minority Risk -- 4 Impact of Algorithms -- 5 Methodology -- 5.1 Data -- 5.2 Algorithms -- 6 Limitations of Existing Fairness Literature -- 6.1 Ex Post Fairness -- 6.2 Group Fairness -- 6.3 Equalisation of Evaluation Metrics -- 6.4 Fairness Impossibility -- 6.5 Proxies of Race and Proxies of Risk -- 6.6 Existing Structural Bias -- 7 Ex Ante Fairness -- 7.1 Individual Fairness -- 7.2 Counterfactual Fairness -- 8 Limitations in Existing Approaches to Fairness -- 9 Proposal of Trade-off Analysis -- 9.1 Operationalisation of Variables -- 9.2 Financial Inclusion -- 9.3 Negative Impact on Minorities -- 10 Trade-off Analysis -- 10.1 Proxies of Race -- 10.2 Triangulation of Applicant's Race -- 11 Limitations and Future Work -- 12 Conclusion -- Appendix -- Features -- References -- Chapter 13: Ethical Foresight Analysis: What It Is and Why It Is Needed? -- 1 Introduction -- 2 Background -- 2.1 Definitions -- 2.2 A Brief History of Foresight Analysis -- 2.3 Relevant Concepts for Ethical Foresight Analysis -- 2.4 When is Ethical Foresight Analysis Useful? -- 3 Existing Methodologies of Ethical Foresight Analysis -- 3.1 Crowdsourced Single Predictions Frameworks (Delphi and Prediction Markets) -- 3.2 Evaluation -- 3.3 Technology Assessment (TA) -- 3.4 Evaluation -- 3.5 Debate-Oriented Frameworks (eTA) -- 3.6 Evaluation -- 3.7 Far Future Techniques (Techno-Ethical Scenarios Approach, TES) -- 3.8 Evaluation -- 3.9 Government and Policy Planning Techniques (ETICA) -- 3.10 Evaluation -- 3.11 Combinatory Techniques (Anticipatory Technology Ethics, ATE). ; 3.12 Evaluation -- 4 Discussion: Known Limitations of EFA -- 5 Recommendations for Potential Future Approaches to EFA -- 6 Conclusion -- References -- Chapter 14: Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions -- 1 Introduction -- 1.1 What Are the Fundamentally Unique and Plausible Threats Posed by AIC? -- 1.2 What Solutions Are Available or May be Devised to Deal with AIC? -- 2 Methodology -- 3 Threats -- 3.1 Commerce, Financial Markets, and Insolvency -- 4 Harmful or Dangerous Drugs -- 5 Offences against the Person -- 6 Sexual Offences -- 7 Theft and Fraud, and Forgery and Personation -- 8 Possible Solutions for Artificial Intelligence-Supported Crime -- 8.1 Tackling Emergence -- 8.2 Addressing Liability -- 8.3 Monitoring -- 8.4 Psychology -- 9 Conclusions -- 9.1 Areas -- 9.2 Dual-Use -- 9.3 Security -- 9.4 Persons -- 9.5 Organisation -- References.
• Titolo autorizzato: The 2021 Yearbook of the Digital Ethics Lab
• ISBN: 3-030-80083-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910508450803321
• Lo trovi qui: Univ. Federico II
• Serie: Digital Ethics Lab Yearbook