Welfare Fraud 2.0? Using Big Data to Surveil, Stigmatize, and Criminalize the Poor

Abstract

Background This article examines the discourse around the digital surveillance of those living on social assistance by analyzing two digital “anti-fraud” tracking tools: Ontario’s Social Assistance Management System and Australia’s BasicsCard system. Analysis Digital surveillance and big data analytical processes embedded in the utilization of digital “anti-fraud” tracking tools tend to operate outside of democratic processes, outpace ethical considerations, and even create and reinforce social divisions and inequality. Conclusion and implications Despite the claim that these software programs make about saving taxpayers’ money and assisting those in need more effectively, these digital tools adversely affect the people they are supposed to help and, worse, stigmatize and criminalize those who live in poverty.