Automating International Human Rights Adjudication

47 Pages Posted: 12 Apr 2024

See all articles by Veronika Fikfak

Veronika Fikfak

University College London - School of Public Policy; University of Copenhagen - iCourts - Centre of Excellence for International Courts

Laurence R. Helfer

Duke University School of Law; University of Copenhagen - iCourts - Centre of Excellence for International Courts

Date Written: February 29, 2024


International human rights courts and treaty bodies are increasingly turning to automated decision-making (ADM) technologies to expedite and enhance their review of individual complaints. Algorithms, machine learning, and AI offer numerous potential benefits to achieve these goals, such as improving the processing and sorting of complaints, identifying patterns in case law, enhancing the consistency of decisions, and predicting outcomes. However, these courts and quasi-judicial bodies have yet to consider the many legal, normative, and practical issues raised by the use of different types of automation technologies for these purposes.

This article offers a comprehensive and balanced assessment of the benefits and challenges of introducing ADM into international human rights adjudication. We reject the use of fully automated decision-making tools on legal, normative, and practical grounds. In contrast, we conclude that semi-automated systems—in which ADM makes recommendations that judges, treaty body members, and secretariat or registry lawyers can accept, reject or modify—is justified provided that judicial discretion is preserved and cognitive biases are minimised.

Applying this framework, we find a strong case for using ADM to digitize documents and for internal case management purposes, such as assigning complaints according to expertise. We also endorse the use of facilitated ADM to make straightforward recommendations regarding registration, inadmissibility, and the calculation of damages. Conversely, we reject the use of algorithms or AI to predict whether a state has violated a human rights treaty. In between these polar categories we discuss semi-automated programs that cluster similar cases together, summarize and translate key texts, and recommend relevant precedents. The benefits of introducing these tools to improve international human rights adjudication need to be weighed against the challenges posed by two types of cognitive biases—biases inherent in the datasets on which ADM is trained, and biases arising from interactions between humans and machines.

We also introduce a framework for enhancing the accountability of ADM in international human rights adjudication. This includes public review, consultations, and external oversight before automation tools are adopted, as well as systemic and case-specific explanations about how the tools have been deployed in individual cases. Concerns about the ability of humans to meaningfully supervise machine learning and AI programs also raise questions about revisiting the finality of international decisions made with the assistance of ADM.

Keywords: human rights, human rights adjudication, automation, machine learning, AI and human rights, bias in automation

JEL Classification: K33

Suggested Citation

Fikfak, Veronika and Helfer, Laurence R., Automating International Human Rights Adjudication (February 29, 2024). Michigan Journal of International Law, Vol. 45, No. 1, 2024, Duke Law School Public Law & Legal Theory Series No. 2024-28, Available at SSRN:

Veronika Fikfak (Contact Author)

University College London - School of Public Policy ( email )

29/30 Tavistock Square
London, WC1H 9QU
United Kingdom

University of Copenhagen - iCourts - Centre of Excellence for International Courts ( email )

Studiestraede 6
Copenhagen, DK-1455

Laurence R. Helfer

Duke University School of Law ( email )

210 Science Dr.
Box 90360
Durham, NC 27708
United States
+1-919-613-8573 (Phone)


University of Copenhagen - iCourts - Centre of Excellence for International Courts ( email )

University of Copenhagen Faculty of Law
Karen Blixens Plads 16
Copenhagen S, DK-2300


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