Special Issue on AI and Law

Summary: 1. Introduction. – 2. Methodology of the Study. – 3. AI Concept and Rule in Contractual Negotiation. – 4. Legal Challenges Related to Contractual Negotiation through AI Technologies. – 4.1. Civil Liability for Damages Caused by Artificial Intelligence. – 4.2. Civil Types of Damages Resulting from AI Errors in Contract Negotiations. – 4.3. Conditions for Civil Liability for Errors Committed by Artificial Intelligence during Negotiations. – 4.4. Victim’s Obligations in Civil Claims Arising from AI Errors in Negotiation. – 4.5. Critical Reflections on Regulatory Complexity and Comparative Prospects. – 4.6. Distinguishing Contractual and Tortious Liability in AI-Related Case. – 4.7. Scope of Damage Covered Under Product Liability. – 5. Calculating the Compensation for the Damages Resulting from the AI Errors in Negotiation. – 6. Findings. – 6.1. Conclusions. – 6.2. Recommendations.

Summary: 1. Introduction. – 2. Methodology. – 3. Results and Discussion. – 3.1. Ethical and Copyright Challenges. – 3.1.1. Problems of Legal Regulation of Artificial Intelligence. – 3.1.2. Problems of Normative and Technical Regulation of Artificial Intelligence – 3.1.3. Problems of Ethical Regulation of Artificial Intelligence. – 3.2. Institutional and Procedural Safeguards. – 3.3 Liability and Protection of Citizens’ Rights. – 4. Conclusions.

Summary: 1. Introduction. – 2. Methodology. – 3. Results and Discussion. – 3.1. AI’s Transformative Potential in the Judicial Sector. – 3.2. Ethical Guidelines for AI in the Justice System. – 3.3. Assistive AI in Judicial Decision-Making. – 3.4. Procedural AI in Court Administration. – 3.5. Fully Autonomous AI (“Robot Judges”). – 3.6. EU AI Act (2024) and Soft Laws. – 3.7. International Legal Instruments. – 4. Conclusions.

Summary: 1. Introduction. – 1.1. Research Context and Significance. – 1.2. Research Problem and Gap. – 1.3. Research Objectives and Questions. – 1.4. Contribution and Structure. – 2. Literature Review and Conceptualizing Digital Human Rights. – 2.1. Overview and Rationale. – 2.2. Defining Digital Human Rights. – 2.3. Core Categories of Digital Human Rights. – 2.3.1. Privacy Rights in Digital Contexts. – 2.3.2. Right to Internet Access. – 2.3.3. Data Protection Rights. – 2.3.4. Right to Anonymity. – 2.3.5. Right to Be Forgotten. – 3. Digital Rights and AI in the MENA Context. – 3.1. Regional Regulatory Frameworks and Emerging AI Strategies. – 3.2. The Role of Islamic Legal and Ethical Principles. – 4. The Intersection Between AI Governance and Digital Human Rights in International Legal Frameworks. – 4.1. The European AI Act: A Milestone in Human-Rights-Centered Regulation. – 4.2. Soft-Law Approaches: UNESCO and OECD Frameworks. – 4.3. European Case Law and Regulatory Guidance on Emotion AI. – 5. Digital Human Rights Within the Saudi Arabia’s Legal Framework: a Preliminary Assessment. – 5.1. Personal Data Protection Law (PDPL). – 5.2. 2007 Anti-Cybercrime Law and Digital Rights Implications. – 6. Conclusions and Recommendations.

Summary: 1. Introduction. – 2. Methodology and Research Approach. – 3. Historical Context and Legislative Evolution. – 4. Role of Statutory Law in Regulating Artificial Intelligence. – 4.1. Statutory Laws and Its Limitations. – 4.2. The Difficulties of Juggling Innovation and Responsibility. – 4.2.1. Privacy & Social Implications. – 4.2.2. Bias and Discrimination Concerns. – 4.2.3 Economic Repercussions. – 5. Limitations of Legal Policies in Regulating Developments of AI. – 6. International Legal Difficulties Arising from The Use of AI. – 7. Conclusions and Suggestions.

Summary: 1. Introduction. – 2. Methodology. – 3. Understanding Emotion AI and Its Privacy and Ethical Concerns. – 3.1. Defining Emotion AI. – 3.2. The Rise of Privacy and Ethical Concerns with Emotion AI. – 3.2.1. Bias and Discriminationl. – 3.2.2. Transparency and Explainability. – 3.2.3. Consent and Data Security. – 3.2.4. The Risk of Manipulation. – 4. Data Protection Frameworks Relevant to Emotion AI. – 4.1. Emotion AI Through the Lenses of the GDPR. – 4.2. Emotion AI Systems Under EU AI Act. – 4.3. European Case Law and Regulatory Guidance on Emotion AI. – 5. Compliance Strategies for Privacy-By-Design in Emotion AI. – 5.1. Privacy-by-Design Core Principles. – 5.2. Implementing Privacy-by-Design in Emotion AI. – 5.2.1. Data Minimization and Purpose Limitation. – 5.2.2. Transparency and Consent. – 5.2.3. Security and Data Protection. – 5.2.4. Accountability and Algorithmic Transparency. – 5.2.5. User-Centric Design. – 5.2.6. Impact Assessments. – 6. Conclusions.

Summary: 1. Introduction. – 2. Methodology. – 3. Legal and Political Foundations in Europe. – 4. Germany: Use Cases, Regulation, and Development Pathways. – 5. Ukraine: Use Cases, Regulation, and Development Pathways. – 6. Safeguarding Rights, Evidence, and Fair Trial Standards. – 7. Conclusion.

Summary: 1. Introduction. – 2. Methodology. – 3. Literature Review and Theoretical Framework. – 4. Incrimination of Violation of the Presumption of Innocence. – 4.1 Violation of the Presumption of Innocence through Torture and Coerced Confessions. – 4.2. Violation of the Presumption of Innocence through Disclosure of Investigative Secrets. – 5. Incrimination of Influencing the Proper Administration of Justice. – 6. European Context and Case Law. – 6.1. European Legal Standards on Fair Trial and Media Freedom. – 6.2 ECtHR Jurisprudence on Balancing Media Freedom and Fair Trial Rights. – 6.3 Comparative Perspective: Jordan and Post-Social Legal Transitions. – 7. Conclusions.

Summary: 1. Introduction. – 2. Literature Review. – 3. Methodology. – 4. Criminal Liability Definition for Artificial Minds and ChatGPT. – 4.1. A Mind Without a Body: Who Prosecutes ChatGPT? – 4.2. When ChatGPT Speaks Without Criminal Intent: Can It Be Prosecuted? – 4.3. Attributing Criminal Liability in the Age of Intelligent Machines. – 5. Challenges in Assessing the Criminal Liability of Artificial Intelligence. – 5.1. The Crisis of Criminal Law in the Era of ChatGPT. – 5.2. The Causality Dilemma in the Era of Generative Artificial Intelligence. – 5.3. ChatGPT and the Mens Rea Dilemma. – 6. The Legal and Regulatory Challenges of Generative AI. – 6.1. The Algorithmic Regulatory Gap and Legal Accountability of ChatGPT. – 6.2. Algorithmic Intelligence and Legitimate Risks. – 7. The Future of Criminal Liability for Algorithmic Harm. – 7.1. Rebuilding Generative AI's Criminal Liability. – 7.2. Future Studies: Corporate Criminal Law and AI Liability. – 8. Conclusions and Recommendations.

Summary: 1. Introduction. – 2. Methodology. – 3. Bias in the Judiciary: Human, Algorithmic, and Institutional Dimensions. – 3.1. A Human Bias. – 3.2. Judicial Bias: Sources and Safeguards. – 3.3. Automation Bias. – 4. AI and LLMs in courts. – 4.1. Deployment Models and Practices in the Judiciary. – 4.2. Problem Cases: Bias, Opacity, and Due-Process Risks. – 5. Bias Controls in Judicial AI: Hard- and Soft-Law Approaches. – 6. Conclusions.

Summary: 1. Introduction. – 2. Defining Product Liability. – 3. Scope of Application. – 4. Elements of Liability. – 5. Exemptions from Liability. – 6. Procedural Matters. – 7. Conclusions.

Summary: 1. Introduction. – 2. Methodology. – 3. Concept Framework. – 3.1. The Definition of “Artificial Intelligence in Criminal Justice”. – 3.2. The Definition of “Technological Innovation in Criminal Justice”. – 3.3. The Definition of “Right to Personal Data Protection in Criminal Justice”. – 4. Key Principles Ensuring a Balance between Technological Innovation and the Right to Personal Data Protection. – 4.1. The Principles of Lawfulness, Necessity, and Proportionality. – 4.2. The Principle of Accountability and Impact Assessment. – 4.3. The Principle of Transparency and Human Supervision. – 4.4. The Principle of a Balanced Approach in Applying AI to Criminal Justice. – 5. The EU’s Experience in Ensuring the Balance between Technological Innovation and Personal Data Protection in Criminal Justice. – 5.1. The EU’s Legal Framework for Ensuring the Balance between Technological Innovation and Personal Data Protection. – 5.2. Balancing Mechanisms through Impact Assessment and Risk Control. – 5.3. Enforcement Mechanism and the Role of Independent Monitoring Bodies. – 6. Legal Status and Challenges in Vietnam in Ensuring a Balance between Technological Innovation and Personal Data Protection in Criminal Justice. – 6.1. Current Status of Vietnamese Laws. – 6.2. Challenges of Vietnam in Ensuring the Balance between Technological Innovation and the Right to Personal Data Protection in Criminal Justice. – 7. Recommendations to Improve Vietnam’s Legal System from the European Union’s Experience. – 8. Conclusions.

Summary: 1. Introduction. – 2. Methodology. – 3. Results and Discussion. – 3.1. European Standards and Regulatory Architecture of the Digital Justice in the European Union. – 3.2. National Practices of Digital Justice in the Countries of Central and Eastern Europe. – 3.3. National Practices of Digital Justice in the Countries of the Baltic Region. – 3.4. Ukraine’s Digital Justice Landscape: Challenges, Gaps and Alignment with EU standards. – 4. Conclusions.

Summary: 1. Introduction. – 2. European Approach to AI in Adjudication. – 3. AI as Judicial Assistants: Supporting Human Decision-Making. – 4. AI as Autonomous Adjudicators: The Prospect of Replacing Judges. – 5. Conclusions.