20 10.1163/22131035-14020001 | enigbokan is mandatory that public officials are transparent in the processes, criteria, and the bases upon which decisions are made.105 Mashaw asserts that ‘authority without reason is literally dehumanising’.106 Therefore, human dignity is at the centre of the rationale for a duty to give reasons for decisions.107 This administrative duty extends to algorithmic decision. To succeed in meeting this duty, there is a need for ai algorithmic systems to provide the legal basis upon which a particular legal decision has been made.108 ai scholars use the term explainability for this idea.109 Explainability implies the duty to provide reasons (justifying decision) and the ability to understand how the algorithm decision was reached and why, making it comprehensible to the public.110 Some deep neural network (‘black box’) algorithms suffer from opacity, meaning they are unable to provide reasons or suitable explanations for the decisions they make.111 Experts in the field (computer scientists or programmers) cannot understand how these black box models process data, and the outcomes arrived at – if so, they will even be more incomprehensible to the public.112 Although we do not fully understand how these forms of ai generate decisions, this is similar to our limited understanding of how 105 106 107 108 109 110 111 112 Child on State obligations regarding the human rights of children in the Context of International Migration in Countries of Origin, Transit, Destination and Return; Art. 41 Charter of Fundamental Rights of the European Union (oj 2012/c 326/02). Khaled Khalaf Abed Rabbo Aldrou, ‘The principle of Transparency in Administrative Decisions in Light of Artificial Intelligence for Sustainable Development Goals: A Legal Study’ 2025 5 (2) Journal of Lifestyle and sdg s Review 1–25; Charter of Fundamental Rights of the European Union (oj 2012/c 326/02), Art. 41. Jerry Mashaw, ‘Public Reason and Administrative Legitimacy’ in John Bell and others (Eds.), Public Law Adjudication in Common Law Systems: Process and Substance (Hart Publishing, 2016) 17. Palairet (n 103). 97. David Restrepo Amariles, ‘Promises and Limits of Law for a Human-Centric Artificial Intelligence’ (2023) 48 Computer Law & Security Review 8. Riccardo Guidotti and others, ‘A Survey of Methods for Explaining Black Box Models’ (2018) 51(5) acm Computing Surveys 1–42; Tim Miller, ‘Explanation in Artificial Intelligence: Insights from the Social Science’(2019) 267 Artificial Intelligence 1–38. The Royal Society ‘Explainable ai: The Basics’ Policy briefing November 2019, 8, <https://www.techtarget.com/searchcio/tip/AI-transparency-What-is-it-and-why-do -we-need-it> accessed 30 September 2025. Hassija and others, (n 10) at 46. Ibid; Stéphanie Laulhé Shaelou and Yulia Razmetaeva, ‘Challenges to Fundamental Human Rights in the Age of Artificial Intelligence Systems: Shaping the Digital Legal Order while Upholding Rule of Law Principles and European Values’ (2024) 24 Journal of the Academy of European Law 580; Johan Wolswinkel, ‘Artificial Intelligence and Administrative Law’ December 2022 para. 19; See The cases of c-203/22 ck v Dun & Bradstreet Austria; ibm ‘What is Black Box ai?’ 29 October 2024 <https://www.ibm.com /think/topics/black-box-ai> accessed 30 September 2025. International Human Rights Law Review (2025) 1–31