Indigenous peoples and artificial intelligence: A systematic review and future directions - Maneesha Perera; Rajith Vidanaarachchi; Sangeetha Chandrashekeran; Melissa Kennedy; Brendan Kennedy; Saman Halgamuge (Big Data & Society)
This systematic literature review addresses the intersection of two rapidly evolving areas of knowledge and practice: Indigenous Knowledge Systems (IKS) and artificial intelligence (AI). There is growing scholarly recognition of the rich and diverse nature of IKS, which are unique intergenerational understandings of worldly relations from an Indigenous standpoint. There is now a vast literature on the promise and pitfalls of AI. However, there is a lack of systematic reviews showing how these two dynamic literatures are intersecting, and what the major themes are. AI has the potential to assist the promotion of IKS; however, there are also potential risks arising from AI for Indigenous peoples, such as the erosion of cultural knowledge, and data-grabbing that fails to respect the principles of Indigenous Data Sovereignty. These risks can exacerbate existing knowledge hierarchies and socio-economic inequalities. In this paper, we conducted a systematic review of articles published between 2012 and 2023 (January) on Indigenous peoples and AI. We shed light upon four unique overlapping categories into which existing literature can be classified and comprehensively discuss literature under each category. The first two categories discuss AI’s role in assisting the promotion of IKS and the third focuses on the pitfalls of using AI for Indigenous peoples. The final category discusses how IKS itself can enrich the development of AI. We further identify several gaps in the literature and highlight avenues requiring attention on AI’s role with Indigenous peoples and their knowledge systems.