Multidisciplinary Perspectives on Artificial Intelligence and the Law.
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Superior document: | Law, Governance and Technology Series ; v.58. |
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Place / Publishing House: | Cham : : Springer International Publishing AG,, 2024. ©2024. |
Year of Publication: | 2024 |
Edition: | First edition. |
Language: | English |
Series: | Law, Governance and Technology Series
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Physical Description: | 1 online resource (457 pages) |
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Sousa Antunes, Henrique. Multidisciplinary Perspectives on Artificial Intelligence and the Law. First edition. Cham : Springer International Publishing AG, 2024. ©2024. 1 online resource (457 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Law, Governance and Technology Series ; v.58. Description based on publisher supplied metadata and other sources. 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. Freitas, Pedro Miguel. Oliveira, Arlindo L. Martins Pereira, Clara. Vaz de Sequeira, Elsa. Barreto Xavier, Luís. 3-031-41263-X Law, Governance and Technology Series |
language |
English |
format |
eBook |
author |
Sousa Antunes, Henrique. |
spellingShingle |
Sousa Antunes, Henrique. Multidisciplinary Perspectives on Artificial Intelligence and the Law. Law, Governance and Technology Series ; 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. |
author_facet |
Sousa Antunes, Henrique. Freitas, Pedro Miguel. Oliveira, Arlindo L. Martins Pereira, Clara. Vaz de Sequeira, Elsa. Barreto Xavier, Luís. |
author_variant |
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Freitas, Pedro Miguel. Oliveira, Arlindo L. Martins Pereira, Clara. Vaz de Sequeira, Elsa. Barreto Xavier, Luís. |
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author2_role |
TeilnehmendeR TeilnehmendeR TeilnehmendeR TeilnehmendeR TeilnehmendeR |
author_sort |
Sousa Antunes, Henrique. |
title |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_full |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_fullStr |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_full_unstemmed |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_auth |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_new |
Multidisciplinary Perspectives on Artificial Intelligence and the Law. |
title_sort |
multidisciplinary perspectives on artificial intelligence and the law. |
series |
Law, Governance and Technology Series ; |
series2 |
Law, Governance and Technology Series ; |
publisher |
Springer International Publishing AG, |
publishDate |
2024 |
physical |
1 online resource (457 pages) |
edition |
First edition. |
contents |
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. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>10672nam a22004573i 4500</leader><controlfield tag="001">993646967404498</controlfield><controlfield tag="005">20240131172003.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr#|||||||||||</controlfield><controlfield tag="008">240122s2024 xx o ||||0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3-031-41264-8</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)29476193800041</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MiAaPQ)EBC31063537</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(Au-PeEL)EBL31063537</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1416848336</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)9929476193800041</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">K4240-4343</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sousa Antunes, Henrique.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multidisciplinary Perspectives on Artificial Intelligence and the Law.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham :</subfield><subfield code="b">Springer International Publishing AG,</subfield><subfield code="c">2024.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2024.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (457 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Law, Governance and Technology Series ;</subfield><subfield code="v">v.58.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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).</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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 &amp -- EU Law Through Legal Information `About' Reality -- 1 Introduction.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2.3 Directive on Defective Products.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Freitas, Pedro Miguel.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Oliveira, Arlindo L.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Martins Pereira, 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