YSEC Yearbook of Socio-Economic Constitutions 2023 : Law and the Governance of Artificial Intelligence

• Autore: Gill-Pedro Eduardo
• Pubblicazione: Cham : , : Springer, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (356 pages)
• Altri autori: MobergAndreas
• Nota di contenuto: Intro -- Contents -- Law and the Governance of Artificial Intelligence -- 1 AI Governance -- 2 Law as a Governance Tool -- 3 The Challenges of Regulating AI -- 3.1 AI as the Subject of Governance -- 3.2 AI and the Disruption of Current Governance Regimes -- 4 Engaging with the Governance Challenge: This Volume´s Contribution -- 4.1 Conclusion -- References -- Part I -- AI Regulation in the EU: The Future Interplay Between Frameworks -- 1 Introduction -- 2 The Challenges of Regulating AI -- 3 The AI Act as the Heart of the Regulatory Framework -- 4 Other Relevant Pieces of Legislation -- 4.1 Data -- 4.1.1 The GDPR -- 4.1.2 The Data Governance Act -- 4.1.3 The Data Act -- 4.2 Safety: The General Product Safety Regulation -- 4.3 Liability -- 4.3.1 The AI Liability Directive -- 4.3.2 The Product Liability Directive -- 5 Interplay Issues -- 5.1 Regulatory Gaps -- 5.2 Inconsistencies Between Frameworks -- 5.3 Terminology -- 6 Concluding Remarks -- References -- The AI Act´s Research Exemption: A Mechanism for Regulatory Arbitrage? -- 1 Introduction -- 2 The Concept of Academic Research -- 3 The AI Act and the Research Exemption -- 4 Research Conducted for Commercial or Financial Reasons -- 5 Academic Research on the Path to Commercialization -- 6 Researchers Provide AI to Their Employing Institutions or Other Public Bodies -- 7 Researchers Build High-risk or Prohibited AI and Other Actors Copy It -- 8 Research that Takes Place ``in the Wild´´ or in Regulatory Sandboxes -- 9 Discussion -- 10 Conclusion -- Legislation -- Proposed Legislation -- Case Law -- References -- Journals and Articles -- Books and Chapters -- Proceedings and Conference Papers -- Online Publications -- Part II -- Governance of AI or Governance by AI: Limits, New Threats, and Unnegotiable Principles -- 1 Introduction -- 2 A Human-Rights-Based Approach -- 2.1 Group Privacy. ; 2.2 Biometric Psychography -- 2.3 Neurorights -- 3 Living Human Rights, or the Role of the Courts -- 4 Conclusions and Future Research -- References -- A Horizontal Meta-effect? Theorising Human Rights in the AI Act and the Corporate Sustainability Due Diligence Directive -- 1 Introduction -- 2 The Instruments -- 3 Human and Fundamental Rights at the Core -- 3.1 Human Rights in the Directive -- 3.2 Fundamental Rights in the Act -- 4 Weak Rights Transformed -- 4.1 Fuzzy Rights for the Foreseeable Future -- 4.2 `Appropriate Measures´ Instead of Human Rights -- 4.3 Acceptable Fundamental Rights Violations -- 5 Theorising the Horizontal Meta-effect -- 5.1 Sensing with Rights -- 5.2 Planning with and Acting on Rights -- 6 Political Implications and Future Trajectories -- References -- Everybody Wants To Rule the World: The Relevance of the Rule of Law for Private Law in the Context of Algorithmic Profiling of... -- 1 Introduction -- 2 The Problem Outline: The Erosion of Fundamental Rights in the Context of Algorithmic Profiling of Online Users -- 2.1 The Use of Algorithms for Online Profiling -- 2.1.1 Personal Data -- 2.1.2 Statistical Data -- 2.1.3 Proxies Data -- 2.2 The EU Legislative Framework of Algorithmic Profiling: Public Regulations v. Private Self-Regulation -- 2.2.1 General Data Protection Regulation -- 2.2.2 Proposal for an AI Act Regulation -- 2.2.3 Digital Services Act Regulation -- 2.2.4 Digital Markets Act Regulation -- 2.3 Fundamental Rights Are Threatened by Algorithmic Profiling Online -- 2.3.1 Right to Privacy -- 2.3.2 Right Not To Be Unlawfully Discriminated -- 2.3.3 Right to Freedom of Expression -- 3 The Solution: The Function of the Rule of Law to Secure the Respect of Fundamental Rights in the Context of Algorithmic Prof... -- 3.1 The Rule of Law in the EU: A Stronghold for the Protection of Fundamental Rights. ; 3.1.1 The Rule of Law in the EU -- 3.1.2 The `Public Law Presumption´ -- 3.1.3 The Rule of Law and Private Parties -- 3.2 The Relevance of the Rule of Law to Create Legal Guardrails Around Private Self-Regulation of Online Platforms -- 3.3 The Function of the Rule of Law to Secure the Respect of Fundamental Rights of Users from Algorithmic Profiling by Online ... -- 3.3.1 Non-Arbitrariness v. Freedom to Pursue One´s Own Ends -- 3.3.2 The ``Indeterminacy of the Law´´ Debate v. Self-Regulation of Private Parties -- 3.3.3 Predictability v. Opacity -- 3.3.4 Equality v. Digital Power Concentration -- 3.3.5 Protection of Fundamental Rights v. Relinquishing of Unwaivable Rights via Unilateral, `Mass-Market Boilerplate´ Provisi... -- 4 Conclusions -- Legislation and Legal Acts -- Case Law (in Antichronological Order) -- Online Resources -- References -- Books and Papers -- AI-Based Decision-Making and the Human Oversight Requirement Under the AI Act -- 1 Introduction -- 2 Regulation of High-Risk AI and Human Oversight -- 3 Use of High-Risk AI, Automated Decisions and the GDPR -- 4 Justification of Automated Decisions and High-Risk AI -- 5 Impact Assessments and High-Risk AI -- 6 Automated Decision-Making and Low-Risk AI -- 7 Conclusions -- EU Legislative Acts -- EU Proposals -- Other Public Print -- Case Law of the European Court of Justice -- Opinions European Court of Justice -- UK Case Law -- European Patent Office Case Law -- Online Resources -- References -- Monographs -- Chapters in Anthologies -- Articles -- Part III -- Algorithmic Hiring Systems: Implications and Recommendations for Organisations and Policymakers -- 1 Introduction -- 2 Organisations´ Views on the Potential Benefits of Using Algorithmic Hiring Systems -- 3 Four Emerging Risks in the Algorithmic Hiring System Context. ; 3.1 Data Privacy Concerns Resulting from Collecting Job Applicant Data -- 3.2 Data Privacy Concerns Resulting from Integrating Employee Surveillance Data with Algorithmic Hiring Systems -- 3.3 Algorithmic Hiring Bias Concerns Resulting from Job Applicant and Employee Data Collection -- 3.4 Concerns Regarding Ongoing Oversight of Algorithmic Hiring Systems -- 4 How Organisations Can Support the Responsible Development and Use of Algorithmic Hiring Systems -- 4.1 Develop a Culture of Control in the Development and Use of Algorithms in the Hiring Process -- 4.2 Ensure Robust, Centralised Control Over Algorithmic Hiring Systems -- 4.3 Ensure Ongoing Performance Monitoring of Algorithmic Hiring Systems and Accountability for Results -- 5 How Policymakers Can Support the Responsible Development and Use of Algorithmic Hiring Systems Within Organisations -- 5.1 Create AI Governance Frameworks that Foster Responsible Development and Utilisation of Algorithmic Hiring Systems Within O... -- 5.2 Protect Job Applicants and Employees from Risks Associated with Algorithmic Hiring Systems -- 5.3 Establish an AI Oversight and Coordination Agency that Oversees Algorithmic Hiring Systems and Collects Incidents Related ... -- 5.4 Collect, Analyse, and Report Failures and Incidents Caused by Algorithmic Hiring Systems -- 6 Summary and Conclusion -- References -- Journals and Articles -- Books and Chapters -- Proceedings and Conference Papers -- Online Publications -- Laws, Guidelines, Cases of International Institutions, Countries/Areas -- EU -- Cases -- Japan -- U.S.A. -- Newspapers and Press Releases -- AI Gender Biases in Women´s Healthcare: Perspectives from the United Kingdom and the European Legal Space -- 1 Introduction -- 2 The Gender Gap in Medicine and Healthcare -- 3 Systemic Biases in Women´s Healthcare and AI Algorithm Biases. ; 3.1 Androcentricity in Medicine and Healthcare -- 3.2 Algorithm Gender Biases in AI -- 4 The Regulatory Framework for AI in Healthcare -- 4.1 The European Union Artificial Intelligence Act (EU AI Act) -- 4.2 The Council of Europe Consolidated Working Draft Framework Convention on Artificial Intelligence, Human Rights, Democracy ... -- 4.3 The UK´s Pro-Innovation Approach to Artificial Intelligence Regulation -- 5 Incorporating Data Feminism as a Reflective Tool for Gender Equality -- 5.1 Intersectionality in Data Feminism -- 5.2 Using Data Feminism to Enhance Gender Health Equality -- 5.3 Beyond Data Feminism: Health Ecosystems, Bottom-Up Regulatory Approaches, and Gender Medicine for AI and Women´s Healthcare -- 6 Conclusion -- References -- The Role of AI in Mental Health Applications and Liability -- 1 Introduction -- 1.1 Why Are Mobile Health Applications a Vital Topic for European Healthcare Systems? -- 1.2 Preparedness of Society for Mental Health Apps as the Standard Device in Healthcare -- 1.3 Concerns in Using Mental Health Applications for Diagnosis, Treatment and Monitoring of Patients -- 2 Legal Basis for Using Mental Health Applications -- 2.1 What Happens if the Mental Health Application Is Considered a Medical Device? -- 2.2 Mental Health Applications Do Not Have To Be Certified as a Medical Device -- 3 Users´ Perspectives of AI in Mental Health Applications -- 3.1 Determination of Relevant Factors to Identify the Riskiness of MHAs -- 3.2 Classification of Mental Health Applications According to the Level of Risk for Users -- 3.3 Bias as a Possible Cause of Damage to the Health of Mental Health Apps Users -- 4 Liability Concerning the Mental Health Applications -- 4.1 Application of the Product Liability Directive on the Mental Health Applications -- 4.2 De Lege Ferenda: Better Protection of User? -- 5 Conclusion -- Legislation. ; Online Publications.
• Titolo autorizzato: YSEC Yearbook of Socio-Economic Constitutions 2023
• ISBN: 3-031-55832-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910855376903321
• Lo trovi qui: Univ. Federico II
• Serie: YSEC Yearbook of Socio-Economic Constitutions Series