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Private dispute resolution mechanisms – such as arbitration, mediation, and negotiation – are often criticised for high costs, lengthy proceedings, and inconsistent outcomes. Simultaneously, confidence in traditional courts is declining amid rising litigation expenses, delays, and concerns over impartiality, highlighting the need for more efficient and equitable resolution methods. Advances in artificial intelligence (AI) offer promising tools to address these challenges. AI enhances case preparation through natural language processing (NLP), which organises documents, extracts key insights, and supports evidence analysis. Predictive analytics help anticipate outcomes based on past decisions, aiding strategic planning. AI also enables automation in routine case management, accelerating resolution and reducing costs. Generative AI further alleviates administrative burdens, enabling legal professionals to focus on complex legal reasoning and client interactions. This chapter examines how AI is reshaping private dispute resolution, with a focus on current applications, emerging innovations, and future developments. While AI cannot replace human judgement in complex disputes, it plays a vital role in streamlining procedures, promoting fairness, and improving user satisfaction.
In governing the development and deployment of AI across the European Member States, the EU AI Act tries to bring together two very different visions of AI. The first sees AI as a powerful tool that can be made less risky to the health, safety, and fundamental rights of European consumers if it adheres to a series of technical requirements. The second sees AI as a systems technology whose governance requires a nuanced understanding of its transformative effects on the values, fundamental rights, and power relations that characterise society. This chapter uses these two perspectives on AI as a lens through which to reflect on the implications of the EU AI Act for the justice sector. It analyses the extent to which the Act’s provisions and safeguards are aligned with emerging ethical guidelines for the use of AI in the administration of justice and discusses whether it can be expected to effectively address core ethical concerns about the use of AI in the justice sector. This analysis demonstrates the limitations of the ‘tool’ perspective that dominates the AI Act and reveals the considerable discretion it gives judicial authorities to guide the integration of AI as a societally transformative systems technology into the justice sector.
This introduction offers an overview of the evolving role of artificial intelligence in civil dispute resolution, discussing current developments against the background of broader technological, regulatory and institutional contexts. It examines the dual forces of genuine innovation and persistent hype, clarifies the book’s open and technology-neutral definition of AI, and articulates an equally broad conception of civil dispute resolution encompassing adjudicative but also consensual, formal but also informal mechanisms. The introduction also outlines the book’s comparative ambition and structural organisation, ultimately framing AI as a transformative yet contested actor whose integration into justice systems demands careful, context-sensitive governance.
The rapid development of artificial intelligence (AI) presents new challenges and opportunities for the judiciary. This chapter analyses the impact of the EU’s AI Act on the use of AI systems by judicial authorities in Europe, in particular with regard to their classification as high-risk AI systems. In doing so, the chapter examines practical use cases to illustrate the obligations that judicial authorities may face as deployers and providers.
The Cambridge Handbook of Behavioural Data Science offers an essential exploration of how behavioural science and data science converge to study, predict, and explain human, algorithmic, and systemic behaviours. Bringing together scholars from psychology, economics, computer science, engineering, and philosophy, the Handbook presents interdisciplinary perspectives on emerging methods, ethical dilemmas, and real-world applications. Organised into modular parts-Human Behaviour, Algorithmic Behaviour, Systems and Culture, and Applications—it provides readers with a comprehensive, flexible map of the field. Covering topics from cognitive modelling to explainable AI, and from social network analysis to ethics of large language models, the Handbook reflects on both technical innovations and the societal impact of behavioural data, and reinforces concepts in online supplementary materials and videos. The book is an indispensable resource for researchers, students, practitioners, and policymakers who seek to engage critically and constructively with behavioural data in an increasingly digital and algorithmically mediated world.
The Cambridge Handbook of AI in Civil Dispute Resolution is the first global, in-depth exploration of how artificial intelligence is transforming civil justice. Moving past speculation, it showcases real-world applications-from predictive analytics in Brazil's courts to generative AI in the Dutch legal system and China's AI-driven Internet Courts. Leading scholars and practitioners examine the legal, ethical, and regulatory challenges, including the EU AI Act and emerging governance frameworks. With rich case studies and comparative insights, the book explores AI's impact on access to justice, procedural fairness, and the evolving public–private balance. Essential reading for legal academics, policymakers, technologists, and dispute resolution professionals, it offers a critical lens on AI's promise-and its limits-in reshaping civil dispute resolution worldwide.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
Failure to deliver a fair trial within a reasonable time is the most common violation found by the European Court of Human Rights (ECtHR) as almost half of all its judgments include a violation of Article 6. If the ECtHR were subject to its own jurisdiction, however, it, too, would be in violation of Article 6 in a sizable portion of its judgments. Therefore, both reports by the Court itself and academic literature have urged the Court to increase digitalisation and employ new technologies, including AI, in its procedures. Historically, the Court has employed an ambivalent approach to new technology, incorporating it in its caseload management, but insisting on the use of fax and physical mail in its communications with applicants. There are indicators, such as allowing electronic applications from Ukraine due to the suspension of physical mail during the war with Russia, that the Court may be abandoning this ambivalence. This chapter accounts for the current and potential use of AI at the ECtHR in each of the steps in its adjudication, evaluating the potential of existing AI technologies and the risks involved, considering the procedures and divisions of labour at the ECtHR.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
By 2024, collaboration between Japan’s government and the private sector had deepened to promote IT integration into the judiciary. In civil litigation, legal reforms have driven progress, and AI-supported legal tech is streamlining time-consuming tasks. Academia is also developing AI-based legal reasoning tools. However, criminal trials remain largely untouched by AI, due to Japan’s conservative legal culture and the judges’ reliance on precedent. Public expectations for fairness coexist with concerns over AI’s lack of empathy. The issue is especially sensitive in the context of Japan’s death penalty system. Japan now faces a critical juncture in balancing innovation and tradition in its judicial use of AI.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
The challenges courts face in dealing with the demand for justice in the digital age have increased considerably in the last thirty years. These actors have always been under the spotlight as the traditional institutional mechanism to protect rights and ensure the rule of law, but have been increasingly confronted with limited resources and expertise, and an overwhelming amount of judicial workload. Digitalisation and automation have been seen as a possibility for political decision-makers to sort out new strategies and tools that ease judicial activity. This chapter argues that the increasing digitalisation of justice has resulted in two constitutional trends, respectively towards an increasing internalisation of AI and digital technologies into the judicial field, and externalisation of judicial functions to private actors and administrative authorities which also implement AI technologies. Both internalisation and externalisation raise constitutional challenges for judicial activities, touching the core of digital constitutionalism, primarily the protection of rights and the limits of power in the digital age.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
This chapter analyses a decision of the Constitutional Court of Colombia, which devises a regulatory framework for judicial use of AI. I claim that as long as AI tools are responsive to legal queries, judges will continue to use them. This has significant consequences for the legal profession. Using AI for judicial decision-making prevents important discussions within the profession, which provide cohesiveness, certainty, and legitimacy to legal outcomes. Reliance on AI may undermine the role of professional socialisation in fostering convergent, predictable, and legitimate legal outcomes. Instead, it can facilitate the ‘colonisation’ of the legal field by a disembodied and unaccountable universe of programmers and training dataset authors from outside the (national) legal field. To fully illustrate the magnitude of AI’s effect on the profession, this chapter outlines the Constitutional Court’s decision and its limitations in effectively regulating AI. I then discuss the role of professional socialisation and how AI can displace it. The chapter concludes by suggesting that built-in restrictions in the algorithm itself should be the focus of any regulation of the judicial use of AI.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
Accountability is a foundational judicial value and a tenet of the rule of law. Drawing on contemporary examples from the UK, EU, USA, Latin America, Taiwan, and China, this chapter examines how artificial intelligence (AI) is being used to assist judicial decision-making at varying stages – ranging from case-sorting tools and legal research aids to fully automated ‘smart courts’. By categorising these judicial uses by level of AI intervention, the chapter interrogates two common claims: (1) that greater AI involvement increases threats to judicial accountability, and (2) that judicial oversight ensures such accountability is preserved. Contrary to these common claims, we argue that accountability is compromised at all levels of AI integration. This occurs because AI systems: (1) obscure transparency and open justice; (2) erode judicial independence and reasoning by amplifying cognitive biases; and (3) hinder appellate review, thus limiting opportunities to contest decisions. While governments often assert that judicial supervision and discretion are sufficient safeguards, the chapter argues that such protections are increasingly ineffective amid pervasive and elusive AI systems.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
AI applications are increasingly deployed in the judiciary for a wide array of tasks, denoted as ‘judicial AI’. The implications for the legal system are vast. In this chapter, I focus on the effects of judicial AI on the rule of law, given the judiciary’s essential role in safeguarding this value. After examining what is meant by the rule of law, three sets of questions guide my analysis. First, how does the turn from text-driven to code- and data-driven legal interpretation affect the nature of law? Is there a risk that instead of fostering the rule of law, this leads to algorithmic rule by law? Second, since AI applications are designed by human beings, delegating judicial tasks to AI implies a delegation to the coders developing it. To what extent can this result in a rule of coders? And last, what impact does judicial AI have on the separation of powers, given that the executive and legislative branch of power control the judiciary’s resources? Can it undermine the judiciary’s ability to check and balance the other branches of power? The answers to these questions force me to conclude that many concerns must be addressed prior to judicial AI’s wide-scale adoption.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
The criminal justice system is becoming automated. At every stage, from policing to evidence to parole, AI tools and other technologies guide outcomes. Debates over the pros and cons of these technologies have overlooked a crucial issue: ownership. Developers often claim that details about how their tools work are trade secrets and refuse to disclose that information to criminal defendants or their attorneys. The introduction of intellectual property claims into the criminal justice system raises under-theorised tensions between life, liberty, and property interests. This chapter argues that trade secrets should not be privileged in criminal proceedings. A criminal trade secret privilege is ahistorical, harmful to defendants, and unnecessary to protect the interests of the secret holder. Meanwhile, compared to substantive trade secret law, the privilege overprotects intellectual property. Further, privileging trade secrets in criminal proceedings fails to serve the theoretical purpose of either trade secret law or privilege law. The trade secret inquiry sheds new light on how evidence rules do, and should, function differently in civil and criminal cases.
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences
Edited by
Monika Zalnieriute, Law Institute of the Lithuanian Centre for Social Sciences,Agne Limante, Law Institute of the Lithuanian Centre for Social Sciences