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

dc.contributor.authorKavanagh, Elenaen
dc.date.accessioned2026-05-06T09:23:39Z
dc.date.available2026-05-06T09:23:39Z
dc.date.issued29/04/2026en
dc.description.abstractCurrent 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.en
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid2662348en
dc.identifier.citationKavanagh, E. (2026) 'High-stakes decision-making and the future of AI governance: Indigenous self-determination and lessons from the Arctic Council', Journal of Decision Systems, 35(1), 2662348 (9pp). https://doi.org/10.1080/12460125.2026.2662348en
dc.identifier.doi10.1080/12460125.2026.2662348en
dc.identifier.endpage9en
dc.identifier.issn1246-0125en
dc.identifier.issn2116-7052en
dc.identifier.issued1en
dc.identifier.journaltitleJournal of Decision Systemsen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/18722
dc.identifier.volume35en
dc.language.isoenen
dc.publisherInforma UK Limiteden
dc.rights© 2026, The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is notaltered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by theauthor(s) or with their consent.en
dc.subjectHuman-centric AI governanceen
dc.subjectAI governanceen
dc.subjectSocio-technical decision systemsen
dc.subjectIndigenous knowledgeen
dc.subjectParticipatory governanceen
dc.subjectLegal pluralismen
dc.subjectDecolonial governanceen
dc.titleHigh-stakes decision-making and the future of AI governance: Indigenous self-determination and lessons from the Arctic Councilen
dc.typeArticle (peer-reviewed)en
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
High-stakes decision-making and the future of AI governance Indigenous self-determination and lessons from the Arctic Council.pdf
Size:
713.57 KB
Format:
Adobe Portable Document Format
Description:
Published Version
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Collections