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The Limits of Global Inclusion in AI Development

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arxiv 2102.01265 v1 pith:KEOBQMQT submitted 2021-02-02 cs.CY

Alan Chan , Chinasa T. Okolo , Zachary Terner , Angelina Wang This is my paper · ORCID
classification cs.CY
keywords developmentsystemsapplicationglobalgroupsincludinginequalitypower
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Those best-positioned to profit from the proliferation of artificial intelligence (AI) systems are those with the most economic power. Extant global inequality has motivated Western institutions to involve more diverse groups in the development and application of AI systems, including hiring foreign labour and establishing extra-national data centers and laboratories. However, given both the propensity of wealth to abet its own accumulation and the lack of contextual knowledge in top-down AI solutions, we argue that more focus should be placed on the redistribution of power, rather than just on including underrepresented groups. Unless more is done to ensure that opportunities to lead AI development are distributed justly, the future may hold only AI systems which are unsuited to their conditions of application, and exacerbate inequality.

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Cited by 3 Pith papers

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