Facing Discrimination: Choosing Equality over Technology

51 Pages Posted: 9 Feb 2021

See all articles by Patric Reinbold

Patric Reinbold

University of Wisconsin - Madison, Law School

Multiple version iconThere are 2 versions of this paper

Date Written: December 21, 2020


On its face, facial recognition technology poses advantages in the form of efficiency and cost-savings in sectors of society such as law enforcement, education, employment, and healthcare. However, these advantages perpetuate indirect forms of discrimination through unequal access to the technology’s benefits and—more significantly—direct forms of discrimination such as falsely identifying Black, Indigenous, and People of Color as suspects of crimes disproportionately. Facial recognition technology offers several opportunities to inject bias into its performance: through biased algorithm design, recycling racial bias in the form of past law enforcement data, and through biased user applications.

The precautionary principle warns against regulating a technology before it is fully developed and implemented, but the consequences of allowing this technology to go unregulated are overcome by the startling implications on racial discrimination in the United States. Therefore, this technology should be regulated before any further harm is done. This Comment analyzes the legislation proposed to regulate facial recognition technology by considering the longevity and breadth of the proposed regulations.

Keywords: equality, machine learning, facial recognition, technology, racial bias, BIPOC

Suggested Citation

Reinbold, Patric, Facing Discrimination: Choosing Equality over Technology (December 21, 2020). Available at SSRN: https://ssrn.com/abstract=3766259 or http://dx.doi.org/10.2139/ssrn.3766259

Patric Reinbold (Contact Author)

University of Wisconsin - Madison, Law School ( email )

Madison, WI
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics