Home > Journals > WMLR > Vol. 62 (2020-2021) > Iss. 6 (2021)
William & Mary Law Review
Abstract
Airbnb’s structure, design, and algorithm create a website architecture that allows user discrimination to prevent minority hosts from realizing the same economic benefits from short-term rental platforms as White hosts, a phenomenon this Article refers to as “redliking.” For hosts with an unused home, a spare room, or an extra couch, Airbnb provides an opportunity to create new income streams and increase wealth. Airbnb encourages prospective guests to view host photographs, names, and personal information when considering potential accommodations, thereby inviting bias, both implicit and overt, to permeate transactions. This bias has financial consequences. Empirical research on host earning rates found that White hosts earn significantly more than minorities, even when controlling for location, size, and amenities. Airbnb’s algorithm augments the effects and propensity of individual user bias, creating a system wherein allegedly race-neutral variables serve as proxies for discrimination. Contemporary redliking perpetuates historic inequality related to housing wealth. In the early twentieth century, redlining maps were used to justify withholding investments from Black communities. Today, redliking continues the practice of directing wealth to White communities, reinforces systemic real property barriers by depriving minority hosts of important revenue streams, and exacerbates the racial wealth gap.
This Article examines the liability of Airbnb and similar websites for discrimination experienced by minority short-term rental hosts. The ability of the Fair Housing Act and Civil Rights Act, laws originally enacted to abolish housing discrimination and protect minority consumers, to combat redliking is complicated by the fact that sites such as Airbnb serve multiple purposes; while guests use the platform to identify and book lodging, hosts use the site to advertise available accommodations. Looking to judicial interpretation of platform liability in the context of online speech, this Article proposes two approaches—a general-function test and a fragmented-function test—to determine website liability for discrimination against short-term rental hosts. Noting the limitations of the existing antidiscrimination legal framework, this Article argues that eradicating redliking requires incorporating lessons on platform design from behavioral economics as well as eliminating opportunities for website algorithms to amplify and operationalize user discrimination.