Automating Inequality

Since the dawn of the digital age, decision-making in finance, employment, politics, health, and human services has undergone revolutionary change. Today, automated systems—rather than humans—increasingly control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud.

While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, 2016 New America Fellow Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America.

In Indiana, one million applications for healthcare, food stamps, and cash benefits are denied in three years for simple mistakes a computer interprets as "failure to cooperate," and in Los Angeles, an algorithm sorts of the comparative vulnerability of tens of thousands of homeless people to decide who gets access to an inadequate pool of housing resources. Like the county poorhouse of the nineteenth century, automated decision-making makes possible an ethical distance needed to make inhumane choices: who gets food and who starves, who has housing and how remains homeless, and which families are broken up by the state. In the process, it weakens democracy and betrays our most cherished national values.

Join New America NYC at the New York Public Library for a conversation with Virginia Eubanks and DJ Spooky on data-based discrimination—and the ways we can collectively begin to dismantle it.

PARTICIPANTS

Follow the conversation online using #AutomatingInequality and by following @NewAmericaNYC.

This event is presented in partnership with the New York Public Library.