Can Artificial Intelligence Weigh Values? Proportionality Testing under the ECHR between Doctrine and Empirical Evidence
Mahir Muharemovic
University of Tuzla , Bosnia and Herzegovinahttps://orcid.org/0000-0001-9338-7512
Abstract
This paper examines whether contemporary artificial intelligence (AI) systems are capable of performing proper proportionality tests, particularly the balancing exercise required by the European Court of Human Rights (ECtHR) in determining violations of human rights. The proportionality test sensu stricto, which requires balancing competing interests to achieve substantial justice, represents one of the most complex forms of legal reasoning, demanding deep understanding of values, cultural frameworks, and lived human experience. Through analysis of current AI limitations, including the alignment problem, value comprehension constraints, and the challenge of interpreting cultural context, this study argues that current AI systems lack the capacity for genuine value understanding and cultural sensitivity necessary for proper proportionality balancing. While AI demonstrates utility in pattern recognition and prediction of judicial outcomes, the nuanced moral reasoning, empathy, and contextual judgment required for proportionality testing, particularly considering the margin of appreciation doctrine, remain beyond current AI capabilities. The identified obstacles stem from the fundamental structural properties of the current architectural paradigm. Because these obstacles are structural rather than incidental, considerable skepticism is warranted about successor systems built upon the same principles, though this does not foreclose improvement in a different architecture. The paper concludes that human judgment remains irreplaceable in rights adjudication, though AI may serve as a valuable analytical tool when properly constrained within human-supervised frameworks.
Keywords:
artificial intelligence, proportionality test, European Court of Human Rights, AI alignment, margin of appreciationReferences
Aletras, Nikolaos, Dimitrios Tsarapatsanis, Daniel Preoţiuc-Pietro, and Vasileios Lampos. “Predicting Judicial Decisions of the European Court of Human Rights: A Natural Language Processing Perspective.” PeerJ Computer Science 2 (2016): e93. https://doi.org/10.7717/peerj-cs.93.
Alexy, Robert. A Theory of Constitutional Rights. Oxford: Oxford University Press, 2002.
Arai-Takahashi, Yutaka. The Margin of Appreciation Doctrine and the Principle of Proportionality in the Jurisprudence of the ECHR. Antwerp: Intersentia, 2002.
Barredo Arrieta, Alejandro, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García et al. “Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI.” Information Fusion 58 (2020): 82–115. https://doi.org/10.1016/j.inffus.2019.12.012.
Backgard, William. “The Calculated Law: Exploring the Limits of Transformer Models in Legal Reasoning.” MA diss., Department of Law, University of Gothenburg, 2024. https://hdl.handle.net/2077/87586.
Barak, Aharon. Proportionality: Constitutional Rights and Their Limitations. Cambridge: Cambridge University Press, 2012.
Bignotti, Camilla, and Carolina Camassa. “Legal Minds, Algorithmic Decisions: How LLMs Apply Constitutional Principles in Complex Scenarios.” Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, no. 1 (2024): 120–30. https://doi.org/10.1609/aies.v7i1.31623.
Botskina, Tatiana. “Do Language Models Understand Discrimination? Testing Alignment with Human Legal Reasoning under the ECHR.” Proceedings of the 2nd Workshop on Models of Human Feedback for AI Alignment, 2025. https://openreview.net/pdf?id=m8DOnFTLnO.
Busuioc, Madalina. “Accountable Artificial Intelligence: Holding Algorithms to Account.” Public Administration Review 81, no. 5 (2021): 825–36. https://doi.org/10.1111/puar.13293.
Coan, Andrew, and Harry Surden. “Artificial Intelligence and Constitutional Interpretation.” University of Colorado Law Review 96, no. 2 (2025): 413–501. https://scholar.law.colorado.edu/lawreview/vol96/iss2/4/.
Gabriel, Iason, and Geoff Keeling. “A Matter of Principle? AI Alignment as the Fair Treatment of Claims.” Philosophical Studies 182, no. 7 (2025): 1951–73. https://doi.org/10.1007/s11098–025–02300–4.
Guha, Neel, Julian Nyarko, Daniel E. Ho, Christopher Ré, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood et al. “LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.” Advances in Neural Information Processing Systems 36 (2023): 44123–279. https://doi.org/10.48550/arXiv.2308.11462.
Harbo, Tor-Inge. “The Function of the Proportionality Principle in EU Law.” European Law Journal 16, no. 2 (2010): 158–85. https://doi.org/10.1111/j.1468–0386.2009.00502.x.
Hildebrandt, Mireille. “Privacy as Protection of the Incomputable Self: From Agnostic to Agonistic Machine Learning.” Theoretical Inquiries in Law 20, no. 1 (2019): 83–121. https://doi.org/10.1515/til-2019–0004.
Jonker, Alexandra, and Alice Gomstyn. “What Is AI Alignment?” IBM, October 18, 2024. Accessed August 25, 2026. https://www.ibm.com/think/topics/ai-alignment.
Julienne, Marina. “AI Needs to Align with Human Values.” CNRS News, February 7, 2025. Accessed August 19, 2026. https://news.cnrs.fr/articles/ai-needs-to-align-with-human-values.
Legg, Andrew. The Margin of Appreciation in International Human Rights Law: Deference and Proportionality. Oxford: Oxford University Press, 2012.
Letsas, George. “Two Concepts of the Margin of Appreciation.” Oxford Journal of Legal Studies 26, no. 4 (2006): 705–32. https://doi.org/10.1093/ojls/gql030.
Mehrabi, Ninareh, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan. “A Survey on Bias and Fairness in Machine Learning.” ACM Computing Surveys 54, no. 6 (2021): 1–35. https://doi.org/10.1145/3457607.
Porras-Gómez, Antonio-Martín. “Law as a Design Science.” German Law Journal 26, no. 4 (2025): 547–67. https://doi.org/10.1017/glj.2025.21.
Posner, Eric A., and Shivam Saran. “Judge AI: Assessing Large Language Models in Judicial Decision-Making.” Coase-Sandor Institute for Law and Economics Research Paper No. 25–03, University of Chicago Law School, 2025.
Posner, Eric A., and Shivam Saran. “Silicon Formalism: Rules, Standards, and Judge AI.” SSRN working paper, January 29, 2026. https://ssrn.com/abstract=6155012.
Socol de la Osa, David U., and Nydia Remolina. “Artificial Intelligence at the Bench: Legal and Ethical Challenges of Informing, or Misinforming, Judicial Decision-Making Through Generative AI.” Data & Policy 6 (2024): e59. https://doi.org/10.1017/dap.2024.53.
Shojaee, Parshin, Iman Mirzadeh, Keivan Alizadeh, Maxwell Horton, Samy Bengio, and Mehrdad Farajtabar. “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity.” Apple Research, June 2025. https://doi.org/10.48550/arXiv.2506.06941.
van der Sloot, Bart. “The Origins of Proportionality and Balancing in the Jurisprudence of the European Court of Human Rights.” In Proportionality in the EU Digital Law: Balancing Conflicting Rights and Interests, edited by Jan Czarnocki and Przemysław Palka, 11–32. Oxford: Hart Publishing, 2024. https://doi.org/10.5040/9781509974542.ch-002.
Stone Sweet, Alec, and Jud Mathews. “Proportionality Balancing and Global Constitutionalism.” Columbia Journal of Transnational Law 47, no. 1 (2008): 72–164.
Trykhlib, Kristina. “The Principle of Proportionality in the Jurisprudence of the European Court of Human Rights.” EU and Comparative Law Issues and Challenges Series (ECLIC) 4 (2020): 128–54. https://doi.org/10.25234/eclic/11899.
Tsakyrakis, Stavros. “Proportionality: An Assault on Human Rights?.” International Journal of Constitutional Law 7, no. 3 (2009): 468–93. https://doi.org/10.1093/icon/mop011.
Tu, S. Sean, Amy Cyphert, and Sam J. Perl. “Artificial Intelligence: Legal Reasoning, Legal Research and Legal Writing.” Minnesota Journal of Law, Science and Technology 25, no. 2 (2024): 105–25. https://doi.org/10.24926/15529541.3898.
Vogiatzis, Nikos. “The Relationship between European Consensus, the Margin of Appreciation and the Legitimacy of the Strasbourg Court.” European Public Law 25, no. 3 (2019): 445–80. https://doi.org/10.54648/euro2019025.
Wagner, Anne. “Is Law Still Written in Stone? Rethinking Legal Semiotics.” Politics and Rights Review, May 1, 2025. Accessed August 19, 2026. https://politicsrights.com/law-interpretation-legal-semiotics/.
Zhang, Jiajie. “Artificial Intelligence vs. Human Intelligence: Which Excels Where and What Will Never Be Matched.” UTHealth Houston McWilliams School of Biomedical Informatics, October 1, 2024. Accessed August 23, 2026. https://sbmi.uth.edu/blog/2024/artificial-intelligence-versus-human-intelligence.htm
