Kim on AI and Inequality

Pauline Kim (Washington University in St. Louis – School of Law) has posted “AI and Inequality” (Forthcoming in The Cambridge Handbook on Artificial Intelligence & the Law, Kristin Johnson & Carla Reyes, eds. (2022)) on SSRN. Here is the abstract:

This Chapter examines the social consequences of artificial intelligence (AI) when it is used to make predictions about people in contexts like employment, housing and criminal law enforcement. Observers have noted the potential for erroneous or arbitrary decisions about individuals; however, the growing use of predictive AI also threatens broader social harms. In particular, these technologies risk increasing inequality by reproducing or exacerbating the marginalization of historically disadvantaged groups, and by reinforcing power hierarchies that contribute to economic inequality. Using the employment context as the primary example, this Chapter explains how AI-powered tools that are used to recruit, hire and promote workers can reflect race and gender biases, reproducing past patterns of discrimination and exclusion. It then explores how these tools also threaten to worsen class inequality because the choices made in building the models tend to reinforce the existing power hierarchy. This dynamic is visible in two distinct trends. First, firms are severing the employment relationship altogether, relying on AI to maintain control over workers and the value created by their labor without incurring the legal obligations owed to employees. And second, employers are using AI tools to increase scrutiny of and control over employees within the firm. Well-established law prohibiting discrimination provides some leverage for addressing biased algorithms, although uncertainty remains over precisely how these doctrines will be applied. At the same time, U.S. law is far less concerned with power imbalances, and thus, more limited in responding to the risk that predictive AI will contribute to economic inequality. Workers currently have little voice in how algorithmic management tools are used and firms face few constraints on further increasing their control. Addressing concerns about growing inequality will require broad legal reforms that clarify how anti-discrimination norms apply to predictive AI and strengthen employee voice in the workplace.