Technological Redlining

The financial value of segregation was one of the justifications for redlining policies in the early to mid-twentieth century in which banks, with the support of the federal government, mapped cities into color-coded zones, investing in White neighborhoods and depriving Black ones. In my grandmother’s neighborhood, Leimert Park Los Angeles, marketing campaigns from the 1940s lured White home buyers by touting “beneficial restrictions that absolutely SECURES the security of your investment.”19 These racially restrictive covenants were the main tool that individual homeowners, neighborhood associations, and developers used in order to prevent Black people from purchasing property.

Whereas laws and practices of a previous era blatantly encouraged segregation to reinforce racial hierarchy, today companies are more interested in curating a range of markets to bolster their profit margin. And, whereas the purpose of identifying an individual’s race during the Jim Crow era was to discriminate effectively, now the stated aim is to “better serve” or “include” different groups.20 By fixing group identities as stable features of the social landscape, these technical fixes offer a kind of remedy for the shortcomings of a mass-marketing approach to consumer life. Difference is monetized and, through software techniques, now codified beyond the law, in the digital structures of everyday life, through what Safiya Noble incisively calls “technological redlining.”

This is not simply a story of “then” versus “now.” It is about how historical processes make the present possible; it is about the continuity between Jim Crow and the New Jim Code. Those who wanted to maintain White supremacy by controlling wealth and property used redlining and restrictive covenants to create neighborhoods separated by race. These same geographic divisions are

now a source of profit for those who want to gear their products and services to different racial–ethnic groups. But whether or not we consider this latter process “racist” depends in part on how well we think a group is being targeted – accurately seen, unfairly ignored, or falsely distorted.