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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorSahadžić, Maja
dc.contributor.authorBalakrishnan, Abhijith
dc.date.accessioned2024-12-13T00:01:20Z
dc.date.available2024-12-13T00:01:20Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/48242
dc.description.abstractThis thesis explores the ethical and legal implications of deploying AI judges in judicial systems, focusing on balancing efficiency with the fundamental right to a fair trial. While AI promises enhanced efficiency and consistency in judicial decision-making, it raises critical concerns about transparency, accountability, bias, and adherence to the rule of law. These challenges highlight the need for a comprehensive evaluation of the legal and ethical dimensions of AI integration in the judiciary. The study examines key case studies, including the Dutch SyRI case and the US Loomis case. The SyRI case emphasizes the importance of transparency and proportional safeguards to protect privacy rights under Article 8 of the European Convention on Human Rights (ECHR). The Loomis case highlights the risks associated with proprietary AI algorithms in risk assessments, including biases and the lack of explainability. Both cases underscore the need for robust regulatory measures to ensure fairness and maintain public trust in AI-assisted judicial systems. The thesis evaluates existing legal frameworks, including the General Data Protection Regulation (GDPR), the European Union’s AI Act, the ECHR, and the European Ethical Charter on AI in Judicial Systems. The GDPR’s provisions, particularly Article 22, emphasize the importance of human oversight in automated decision-making. The AI Act’s risk-based classification system for high-risk AI applications provides additional safeguards, but gaps remain, such as insufficient guidance on the specific application of AI in judicial contexts. Key regulatory principles discussed include non-discrimination, transparency, accountability, quality, and user control. The thesis advocates for the integration of explainable AI (xAI) systems to ensure decisions are understandable and justifiable. It also stresses the importance of maintaining judicial independence, where AI systems serve as tools to assist judges rather than replace their decision-making authority. Continuous monitoring, regular audits, and ethical-by-design principles are proposed to address risks such as bias and data misuse. In conclusion, while AI offers opportunities to improve judicial efficiency and consistency, its deployment must prioritize ethical and legal safeguards to uphold the principles of justice, fairness, and the rule of law. The thesis calls for the development of enforceable and comprehensive regulatory frameworks to address these challenges, ensuring that AI is used responsibly in judicial decision-making processes while safeguarding public trust and fundamental rights.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThe thesis examines the ethical and legal implications of integrating AI judges into judicial systems, focusing on balancing efficiency with the right to a fair trial. It explores challenges like transparency, accountability, bias, and the rule of law, analyzing cases such as SyRI and Loomis. It evaluates the adequacy of existing regulations (e.g., GDPR, AI Act, ECHR) and proposes strategies for ethical AI use in judicial decision-making while upholding justice and public trust.
dc.titleETHICAL AND LEGAL IMPLICATIONS OF AI JUDGES: BALANCING EFFICIENCY AND THE RIGHT TO FAIR TRIAL
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsAI judges; ethical implications; legal implications; fair trial; transparency; accountability; bias; rule of law; SyRI case; Loomis case; GDPR; AI Act; ECHR; judicial decision-making; algorithmic bias; explainable AI; human rights; data protection; judicial independence; legal frameworks; public trust; AI regulation; ethical AI; artificial intelligence in law.
dc.subject.courseuuLaw and Technology in Europe
dc.thesis.id41705


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