Brown, Paul T.Wilson, DanielWest, KiriEscott, Kirita-RoseBasabas, KiyaRitchie, BenLucas, DanielleTaia, IvyKusabs, NatalieKeegan, Te Taka Adrian Gregory2026-11-132026-11-132024-04-02Brown, P. T., Wilson, D., West, K., Escott, K. -R., Basabas, K., Ritchie, B., Lucas, D., Taia, I., Kusabs, N., & Keegan, T. T. (2024). Māori algorithmic sovereignty: idea, principles, and use. Data Science Journal, 23. https://doi.org/10.5334/dsj-2024-0151683-1470https://hdl.handle.net/10289/18778With the emergence of data technologies and algorithms in Aotearoa New Zealand that are used for decision-making and support, there is a need for frameworks to guide how we maximise the opportunities these technologies create and minimise the risks they may impose. For algorithms that use Māori data, these require extra considerations due to the heightened risks Māori endure due to systemic biases inherent within data and the processes that underlie algorithm development. Algorithms can be framed as a particular use of data, therefore data frameworks that currently exist can be extended to include algorithms. Māori data sovereignty principles are well-known and are used by researchers and government agencies to guide the culturally appropriate use of Māori data. Extending these principles to fit the context of algorithms, and re-working the underlying sub-principles to address issues related to responsible algorithms from a Māori perspective leads to the Māori algorithmic sovereignty principles. We define this idea, present the updated principles and sub-principles, and highlight a strategy for the detection and minimisation of bias within the algorithm development process.enAttribution 4.0 Internationalcomputer sciencedata sovereigntydata useindigenousMāoriresonsible algorithmscs.CYcs.CYJournal Article10.5334/dsj-2024-0151683-147046 Information and Computing Sciences39 Education3904 Specialist Studies In Education46 Information and Computing Sciences4603 Computer Vision and Multimedia Computation4605 Data management and data science