‘Artificial intelligence is entering African common-law courts at a moment when those courts remain structured by colonial legal inheritances: reception statutes, stare decisis, adversarial procedure, the repugnancy test, and the subordination of customary law to a facts-not-law evidentiary status. This article asks a single question: Will algorithmic tools disrupt or deepen coloniality in African judiciaries? Drawing on doctrinal analysis, decolonial legal theory, and socio-technical analysis of Legal NLP and judicial decision-support systems and focusing on common-law jurisdictions where the colonial continuum is most legible in contemporary doctrine, I defend a decisive thesis. Algorithmic tools will deepen coloniality where they are deployed as general-purpose adjudicative or predictive systems trained on colonial jurisprudence and embedded within inherited procedural hierarchies, because data, doctrine, and institutional design are co-produced within that legacy. They may disrupt coloniality only where they are narrowly designed as accountable, context-sensitive, procedurally supportive, and decolonial legal infrastructure that elevates customary, Indigenous, and plural legal orders rather than subordinating them. I map algorithmic use-cases across the judicial process, grade their colonial-reproduction risk, correct the Legal NLP literature’s mischaracterisation in earlier African scholarship, and propose seven decolonial design principles. This contribution is threefold: a jurisdiction-specific account of algorithmic accountability in a significant part of the Global South, a diagnostic framework for judicial AI governance beyond Euro-American contexts, and a constructive design agenda for technology law scholars, regulators, and judicial administrators working in the algorithmic courtroom.’
Link: https://www.sciencedirect.com/science/article/pii/S2212473X26001215
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