Multidisciplinary Perspectives on Artificial Intelligence and the Law

• Autore: Sousa Antunes Henrique
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: First edition.
• Descrizione fisica: 1 online resource (457 pages)
• Altri autori: FreitasPedro Miguel OliveiraArlindo L Martins PereiraClara Vaz de SequeiraElsa Barreto XavierLuís
• Nota di contenuto: Intro -- Preface -- About the Book -- Acknowledgments -- Contents -- Editors and Contributors -- About the Editors -- Contributors -- Part I Scientific, Technological and Societal Achievements in Artificial Intelligence -- Introduction -- Artificial Intelligence: Historical Context and State of the Art -- 1 Historical Origins -- 2 Can Machines Think? -- 3 Objections to Artificial Intelligence -- 4 Intelligence as Symbol Manipulation -- 5 Machine Learning -- 5.1 Basic Concepts -- 5.2 Statistical Approaches -- 5.3 Similarity-Based Approaches -- 5.4 Decision Trees -- 5.5 Neural Networks -- 6 The Deep Learning Revolution -- 7 Applications in Analytics and Automation -- 8 Conclusions -- References -- The Impact of Language Technologies in the Legal Domain -- 1 Introduction -- 2 Language Processing Technologies for Processing Textual Data -- 2.1 Text Anonymization -- 2.2 Document Classification -- 2.3 Information Retrieval -- 2.4 Information Extraction -- 2.5 Summarization -- 2.6 Question Answering and Conversational Systems -- 2.7 Predictions Supported on Textual Evidence -- 2.8 Summary -- 3 Spoken Language Technologies -- 3.1 Automatic Speech Recognition -- 3.2 Speaker Recognition and Speaker Profiling -- 3.3 Speech Synthesis and Voice Conversion -- 4 Conclusions -- References -- Societal Implications of Recommendation Systems: A Technical Perspective -- 1 Introduction -- 2 Recommendation Systems -- 3 When Recommendation Systems Work -- 3.1 Implications for Consumption -- 3.2 Implications for Democracy -- 4 When Recommendation Systems Fail -- 4.1 Learning from Biased Data: Implications for Individuals -- 4.2 From Bad Algorithms to Discriminatory Policies -- 5 A Way Forward -- 6 Conclusions -- References -- Data-Driven Approaches in Healthcare: Challenges and Emerging Trends. ; 1 Patient-Centered Care, Value-Based Care and the P4 Medicine Paradigm: Divergent or Complementary? -- 2 Data-Driven Healthcare -- 3 Ethics and Legal Challenges Posed by Artificial Intelligence -- 4 Investments Trends in Healthcare Artificial Intelligence -- References -- Security and Privacy -- 1 Introduction -- 2 Defining Security and Privacy -- 2.1 Security Properties -- 2.2 Privacy Properties -- 3 Security and Privacy Problems -- 3.1 Access Control -- 3.2 Vulnerabilities and Attacks -- 3.3 Malware -- 3.4 The Human Factor -- 4 Scientific and Technological Achievements -- 4.1 Cryptography -- 4.2 Hardware-Based Security -- 4.3 Cloud Computing -- 4.4 Digital Money, Assets and Identity -- 5 Security, Privacy, and Machine Learning -- 6 Censorship Resistance -- 6.1 Anonymity Networks -- 6.2 Multimedia Protocol Tunneling -- 6.3 Avoiding ML Attacks -- 7 Conclusion -- References -- Part II Ethical and Legal Challenges in Artificial Intelligence -- Introduction -- Before and Beyond Artificial Intelligence: Opportunitiesand Challenges -- 1 Few Presuppositions that Shape the Reflection on AI -- 2 Can Machines Imitate Humans? -- 2.1 The Key Question -- 2.2 The First AI Steps -- 2.3 The Encouraging Achievements -- 3 Can Humans Imitate Machines? -- 3.1 Functional Level -- 3.2 Structural Level -- 3.3 Identity Level -- 4 How Should (Ethics)/Ought (Law) Humans and Machines Relate? -- 4.1 Ethical Requirements -- 4.2 Law and Legal Procedures -- 5 Concluding Remarks -- References -- Autonomous and Intelligent Robots: Social, Legal and Ethical Issues -- 1 Introduction -- 2 Industrial Robots and Automation vs Service Robots -- 3 Robots and Humans: The Rise of Intelligent and Social Robots -- 4 Ethical, Social and Legal Impacts -- 4.1 Ethical Issues -- 4.2 Social Issues -- 4.3 Legal Issues -- 5 Conclusions -- References. ; The Ethical and Legal Challenges of Recommender Systems Driven by Artificial Intelligence -- 1 Introduction -- 2 What are AI's Recommender Systems? -- 3 Ethical and Legal Challenges Associated with RS -- 3.1 Opacity -- 3.2 Discriminatory Bias -- 3.3 Privacy and Data Protection Violations -- 3.4 Diminished Human Autonomy and Self-Determination -- 3.5 Polarization and Manipulation of Democratic Processes -- 4 Recommender Systems: Legal and Regulatory Challenges -- 4.1 Lack of Transparency -- 4.2 Trade Secret -- 4.3 Constantly Changing Technology -- 4.4 Difficulties of Implementation of Data Subjects' Rights in Practice -- 4.5 Difficulties of Rules' Application -- 4.6 Beyond Damage Prevention -- 5 Strategies and Possible Solutions to the Challenges Created by RS -- 5.1 Best Practices Beyond Law -- 5.1.1 Regulation by Technology: Strategies by Design and by Default -- 5.1.2 Implementation of (Human Rights) Impact Assessments -- 5.1.3 Guarantee of Greater Transparency and Explanation of AI (Explainable AI) -- 5.1.4 Codes of Conduct (Self-Regulation) -- 5.1.5 Digital Education in AI -- 5.2 Specific Legal Regulation for AI Systems -- 5.2.1 Digital Services Act (DSA) -- 5.2.2 Proposal of an Artificial Intelligence Act (AIA) -- 6 Conclusion -- References -- Metacognition, Accountability and Legal Personhood of AI -- 1 Introduction -- 2 What Is the Common Denominator in Agency? -- 3 What Is a Voluntary Act? -- 4 What Makes an Agent a Legally Responsible One? -- 5 Metacognition: Shaping Legal Responsibility -- 6 Accountability and Legal Personhood -- 7 Conclusions -- References -- Artificial Intelligence and Decision Making in Health: Risks and Opportunities -- 1 Introduction -- 2 Decision-Making Processes in Health and AI -- 2.1 The Health Area the Use of AI and Decision-Making Processes: Opportunities and Risks to Treat Electronic Health Records (EHR). ; 2.2 The Opportunities -- 2.3 The Risks -- 3 Complex Bioethics Model (CBM) and AI -- 4 Conclusion -- References -- The Autonomous AI Physician: Medical Ethics and Legal Liability -- 1 Introduction -- 2 Artificial Intelligence in Pathology -- 3 The Autonomous AI Physician: Parameters -- 4 Ethical and Legal Implications of the Autonomous AI Physician -- 4.1 Ethical Consideration: Transparency -- 4.2 Ethical Considerations: Reliability and Safety -- 4.3 Ethical Consideration: Bias -- 4.4 Legal Considerations: Data Privacy -- 4.5 Legal Consideration: Liability -- 5 Regulating the Autonomous AI Physician -- 5.1 Healthcare Industry Regulation -- 5.2 Government Regulation -- 5.2.1 Safety Regulation -- 5.2.2 Data Regulation -- 5.3 Liability for Injuries -- 5.3.1 Products Liability -- 5.3.2 Organizational, Vicarious, and Enterprise Liability -- 5.3.3 Medical Malpractice -- 5.3.4 Contractual Assignment of Liability -- 5.3.5 Special Adjudication Systems -- 6 Conclusion -- References -- Ethical Challenges of Artificial Intelligence in Medicine and the Triple Semantic Dimensions of Algorithmic Opacity with Its Repercussions to Patient Consent and Medical Liability -- 1 Introduction: Advantages of Artificial Intelligence (AI) in Medicine -- 2 Triple Semantic Dimensions of Algorithmic Opacity and Its Repercussions to Patient Consent and Medical Liability -- 3 Ethical Dimensions of Using Artificial Intelligence (AI) in the Healthcare Sector: Setting the Parameters for Data-Informed Duties in Tort Law -- 4 Concluding Notes: The Future of Artificial Intelligence (AI) in Medicine and the Importance of Medical Education in Digital Health and New Technologies -- References -- Part III The Law, Governance and Regulation of Artificial Intelligence -- Introduction -- Dismantling Four Myths in AI & -- EU Law Through Legal Information `About' Reality -- 1 Introduction. ; 2 Digital Sovereignty -- 3 Digital Constitutionalism -- 4 The Brussels Effect -- 5 `HAI' (Human-Centric Artificial Intelligence) -- 6 Conclusions -- References -- AI Modelling of Counterfactual Thinking for Judicial Reasoning and Governance of Law -- 1 Introduction and Motivation -- 2 Some Societal and Historical Background -- 3 On Counterfactual Reasoning -- 4 Counterfactual Reasoning and Conflicts of Interest in Large Populations -- 5 Stag Hunting and Law: From Plea Bargaining to International Agreements and AI Regulation -- 6 Evolutionary Games with Counterfactual Thinking (CT) -- 7 Concluding Remarks -- References -- Judicial Decision-Making in the Age of Artificial Intelligence -- 1 Introduction -- 2 The Sentencing Process -- 3 S v Loomis -- 4 The "Technology Effect" -- 5 "Automation Bias" and the Anchoring Effect -- 6 Conclusion -- References -- Liability for AI Driven Systems -- 1 Presentation of the Problems -- 2 Subjective Liability in Case of Alternative Causation -- 3 Strict Liability -- 4 Exemption from Liability for Damage Caused by an AI System -- References -- Risks Associated with the Use of Natural Language Generation: Swiss Civil Liability Law Perspective -- 1 Technical Basics on Natural Language Generation -- 1.1 Introduction to Technical Aspects -- 1.2 Risks of Reinforcement Learning -- 1.2.1 Undesirable Language Generation -- 1.2.2 Code Generation and Vulnerable Code Data -- 1.3 Detection of Machine Generated Text -- 1.4 Operator Influence on Output -- 1.4.1 General Remarks -- 1.4.2 Data and Methods -- 1.4.3 Samples of Operator Influence -- 2 Legal Aspects -- 2.1 Introduction to Legal Analysis -- 2.2 Liability for Autonomous Actions of AI in General -- 2.2.1 Unforeseeable Actions of Self-Learning AI as a Challenge for Tort Law -- 2.2.2 Respondent to Tort Claim -- 2.2.3 Causality as the Limiting Factor of Liability. ; 2.3 Directive on Defective Products.
• Titolo autorizzato: Multidisciplinary Perspectives on Artificial Intelligence and the Law
• ISBN: 3-031-41264-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910799281803321
• Lo trovi qui: Univ. Federico II
• Serie: Law, Governance and Technology Series