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Computer Science > Computers and Society

arXiv:2102.01265 (cs)
[Submitted on 2 Feb 2021]

Title:The Limits of Global Inclusion in AI Development

Authors:Alan Chan, Chinasa T. Okolo, Zachary Terner, Angelina Wang
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Abstract: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.
Comments: AAAI 2021 Workshop on Reframing Diversity in AI
Subjects: Computers and Society (cs.CY)
Cite as: arXiv:2102.01265 [cs.CY]
  (or arXiv:2102.01265v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2102.01265

Submission history

From: Angelina Wang [view email]
[v1] Tue, 2 Feb 2021 02:53:40 UTC (56 KB)
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