Author ORCID Identifier
Tsai - https://orcid.org/0000-0001-9188-0362 Chen - https://orcid.org/0000-0003-2830-5589
Document Type
Conference Proceeding
Publication Date
5-21-2025
Publication Title
Conference on Digital Government Research
Volume
26
Issue
2025
DOI
https://doi.org/10.59490/dgo.2025.980
Abstract
This paper addresses a gap in the AI governance literature in understanding collaboration between national governments and tribal nations in governing AI systems for emergency management. This conceptual work develops and presents a governance design framework for accountable AI systems to fill the knowledge gap by drawing from the fields of public administration, information systems, indigenous studies, and emergency management. This framework situates the governance framework in a cross-sovereignty historical, legal, and policy contexts. It captures the multi-level features and embeddedness of governance structures, including the levels of collaborative governance structure, software system governance rules, and technical software system design. The focal governance dynamics involve the collaborative process in the bi-directional relationship between governance rules and technical design for accountability and the feedback loop. The framework highlights the importance of multi-level and process considerations in designing accountable AI systems. Productive future research avenues include empirical investigation and resulting refinement of the framework and analytical rigor employing institutional grammar.
Recommended Citation
Chen, Y.-C., Tsai, C.-H., & Zendejas, E. (2025). Multi-level Collaborative Governance Framework for Designing Accountable AI Systems for Emergency Management. Conference on Digital Government Research, 26. https://doi.org/10.59490/dgo.2025.980
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
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