Automating Inequality

Automating Inequality examines how algorithmic decision-making systems have become embedded in welfare administration, child protective services, and criminal justice, often with devastating consequences for vulnerable populations. Eubanks traces the history of automated systems in social services from the 1970s onward, showing how these technologies were designed with assumptions that criminalize poverty and reinforce existing inequalities.

Through detailed case studies—including Indiana's welfare system, Los Angeles child services, and predictive policing—the book demonstrates how automation amplifies bias, reduces human discretion, and creates barriers to essential services. Eubanks argues that these systems are not neutral tools but reflect and entrench the values of those who design them, disproportionately harming low-income people and communities of color.

The work has become influential in technology ethics, policy debates, and academic discussions of algorithmic justice. It challenges the assumption that automation improves efficiency and fairness, instead showing how it can systematize discrimination at scale.