Dion R.J. O’Neale , Daniel Wilson , Paul T. Brown , Pascarn Dickinson , Manakore Rikus-Graham , Asia Ropeti
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Ten simple guidelines for decolonising algorithmic systems
As the scope and prevalence of algorithmic systems and artificial intelligence for decision making expand, there is a growing understanding of the need for approaches to help with anticipating adverse consequences and to support the development and deployment of algorithmic systems that are socially responsible and ethically aware. This has led to increasing interest in "decolonising" algorithmic systems as a method of managing and mitigating harms and biases from algorithms and for supporting social benefits from algorithmic decision making for Indigenous peoples.
This article presents ten simple guidelines for giving practical effect to foundational Māori (the Indigenous people of Aotearoa New Zealand) principles in the design, deployment, and operation of algorithmic systems. The guidelines are based on previously established literature regarding ethical use of Māori data. Where possible we have related these guidelines and recommendations to other development practices, for example, to open-source software.
While not intended to be exhaustive or extensive, we hope that these guidelines are able to facilitate and encourage those who work with Māori data in algorithmic systems to engage with processes and practices that support culturally appropriate and ethical approaches for algorithmic systems.