High-stakes decision-making and the future of AI governance: Indigenous self-determination and lessons from the Arctic Council

Current AI governance risks remaining dominated by state-centric models that marginalise Indigenous peoples and historically excluded communities. This paper proposes a human-centric AI governance framework that reconceptualises AI governance institutions as socio-technical decision systems responsible for structuring ethical, political, and regulatory choices about AI deployment. It argues that Indigenous self-determination and participatory rights should be embedded as design principles of AI governance architecture rather than treated as consultative add-ons. By integrating relational knowledge systems and collective responsibility models, pluralistic governance structures can enhance the legitimacy, resilience, and ethical robustness of AI-related decision processes. The analysis uses the Arctic Council’s model as an institutional reference to show how co-governance arrangements can inform the design of inclusive AI governance. The paper contributes to decision systems research by extending the concept of the socio-technical decision system to high-stakes AI governance and by formulating institutional principles for pluralistic AI governance, organised around decision-systems logic.