M\=aori algorithmic sovereignty: idea, principles, and use
Paul T. Brown, Daniel Wilson, Kiri West, Kirita-Rose Escott, Kiya, Basabas, Ben Ritchie, Danielle Lucas, Ivy Taia, Natalie Kusabs, Te Taka, Keegan

TL;DR
This paper introduces M ext= aori algorithmic sovereignty principles, extending existing data sovereignty frameworks to guide culturally appropriate, responsible use of algorithms in Aotearoa New Zealand, aiming to decolonise and indigenise algorithms.
Contribution
It defines and presents new M ext= aori algorithmic sovereignty principles, adapting existing data sovereignty principles to address algorithmic responsibility from a M ext= aori perspective.
Findings
Proposes a framework for responsible algorithms aligned with M ext= aori values
Highlights how principles can decolonise current algorithms
Suggests potential for developing Indigenised algorithms
Abstract
Due to the emergence of data-driven technologies in Aotearoa New Zealand that use M\=aori data, there is a need for values-based frameworks to guide thinking around balancing the tension between the opportunities these create, and the inherent risks that these technologies can impose. Algorithms can be framed as a particular use of data, therefore data frameworks that currently exist can be extended to include algorithms. M\=aori data sovereignty principles are well-known and are used by researchers and government agencies to guide the culturally appropriate use of M\=aori 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 M\=aori perspective leads to the M\=aori algorithmic sovereignty principles. We define this idea, present the updated principles and subprinciples,…
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Taxonomy
TopicsEthics and Social Impacts of AI
