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Associate Professor of Law, Washington & Lee University School of Law
Citation: Margaret Hu, Algorithmic Jim Crow, 86 Fordham L. Rev. 633 (2017).
This Article contends that current immigration- and security-related vetting protocols risk promulgating an algorithmically driven form of Jim Crow. Under the “separate but equal” discrimination of a historic Jim Crow regime, state laws required mandatory separation and discrimination on the front end, while purportedly establishing equality on the back end. In contrast, an Algorithmic Jim Crow regime allows for “equal but separate” discrimination. Under Algorithmic Jim Crow, equal vetting and database screening of all citizens and noncitizens will make it appear that fairness and equality principles are preserved on the front end. Algorithmic Jim Crow, however, will enable discrimination on the back end in the form of designing, interpreting, and acting upon vetting and screening systems in ways that result in a disparate impact.
Lunch will be provided.
This event is pending approval of Minimum Continuing Legal Education Credit by the State Bar of California. UCI Law is a State Bar-approved provider.
About the Colloquium
Machine learning and automated decision-making technologies (colloquially dubbed "artificial intelligence" or "AI") are an increasingly integral feature of social systems. These technologies raise novel legal questions regarding oversight, individual rights, liability and justice. The UCI Law Spring 2020 Colloquium on AI & Law brings to campus leading thinkers engaged with these issues.