Artificial Intelligence and Race: a Systematic Review

Channarong Intahchomphoo · Odd Erik Gundersen

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Ethics and Social Impacts of AI Digitalization, Law, and Regulation Artificial Intelligence in Law

Abstract

This paper examines peer-reviewed publications to learn about the relationships between artificial intelligence (AI) and the human race. For this systematic review, papers were collected from three academic databases: Scopus, Web of Science, and Academic Search Complete. From 1,222 papers reviewed, 36 papers were included. The findings indicate that there are four relationships between AI and race (i). AI causes unequal opportunities for people from certain racial groups, (ii). AI helps to detect racial discrimination, (iii). AI is applied to study health conditions of specific racial population groups, and (iv). AI is used to study demographics and facial images of people from different racial backgrounds. To widen the knowledge related to AI and race, all four finding categories in this review included supplementary studies as lessons learned for legal information management research. The authors, Channarong Intahchomphoo and Odd Erik Gundersen, use these findings to discuss how AI could impact libraries and how legal information management professionals might have to cope with the problem of biased AI.

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References

2017Semantics derived automatically from language corpora contain human-like biases 2017Counterfactual Fairness 2021Social Media Participation in an Activist Movement for Racial Equality 2021Deciphering the 2016 U.S. Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists 2017Recycling Privileged Learning and Distribution Matching for Fairness 2017Preventing discrimination in the automated targeting of job advertisements 2015Characterizing the Demographics Behind the #BlackLivesMatter Movement

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