||September 28, 2017, 2:00 PM
||Cone University Center, Room 113
||Margaret Hu, associate professor of law, Washington and Lee University
|Registration Details & Deadlines
|Who is Invited
||Validated parking tickets available for off campus attendees.
This presentation by Margaret Hu, associate professor of law at Washington and Lee University, contends that 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 first required mandatory separation and discrimination on the front end, and then supposedly established equality on the back end. In contrast, an algorithmic Jim Crow regime allows for “equal but separate” discrimination. In this system, newly developed big data vetting tools fuse biometric data with biographic data and Internet/Social Media profiling to assess risk algorithmically.
Because everyone will be assessed this way, the screening appears to be equal. However, those individuals and groups negatively and disparately impacted by mandatory vetting and screening protocols will largely be the same as groups traditionally discriminated against on the basis of classifications like race, color, ethnicity, national origin, gender, and religion. Thus, under Algorithmic Jim Crow, equal vetting and database screening of all citizens and non-citizens will make it appear that the principles of fairness and equality are preserved. However, this apparent equality 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.
The presentation is hosted by the Center for Professional & Applied Ethics at UNC Charlotte.