ALGORITHMIC SUBSIDIARITY: DESIGNING AI JUSTICE TOOLS FOR INDIGENOUS LEGAL ORDERS

Samenvatting

his paper advances the concept of algorithmic subsidiarity as a guiding principle for the design of artificial intelligence (AI) and legal technology (LegalTech) tools in Indigenous and community-based legal systems. Building on the traditions of critical legal pluralism (CLP), it argues that AI must not replace, but rather support and remain accountable to, Indigenous legal orders. At the center of this inquiry is the tension between universalist, technocratic logics embedded in mainstream LegalTech design and the moral embeddedness, relationality, and participatory governance that characterize Indigenous jurisprudence. The research asks three central questions: How might machine learning models be trained on datasets informed by Indigenous legal principles such as Māori tikanga or Navajo hozho? What participatory design methodologies are most effective in ensuring that these technologies reflect communal well-being and values rather than impose external frameworks? And what governance models—such as data sovereignty agreements and community oversight boards—are necessary to ensure AI systems remain subordinate to the living, evolving character of Indigenous law? Methodologically, the study draws on case studies of emerging initiatives, including Māori-led AI projects for tribal land management and blockchain systems for encoding customary precedents, alongside a participatory action research approach involving co-design of a prototype tool with an Indigenous community partner. Theoretically, the paper situates these findings at the intersection of CLP and critical technology studies, proposing a framework for communitarian AI. This framework resists one-size-fits-all approaches to legal automation and instead affirms cultural specificity, narrative-based epistemologies, and subsidiarity in algorithmic governance. By articulating concrete design principles rooted in moral and cultural embeddedness, the paper contributes to broader debates on responsible AI, Indigenous data sovereignty, and the future of pluralistic legal orders in an increasingly digital world.