Living in Algorithmic Governance: A Study in the Digital Governance of Social Assistance in Ontario

The aim of this dissertation is to examine the impact of the digital governance of social assistance in Ontario via a new software program, Social Assistance Management System (SAMS). SAMS represents a hybrid of traditional methods of regimenting welfare assistance and a newer high-tech version. I reveal a critical shift in governance practice with SAMS, as the system governs welfare recipients into a particular mode of productive subjectivity. Despite the wealth and depth of research in surveillance studies about the potential impact of data mining, creation of data doubles, loss of privacy, and concerns about algorithms that replicate some of the worst biases about people in poverty, there is an absence of clear empirical research into or evidence of actual programs and how they work. We need a better understanding of the impact of delegated governance and algorithmic culture in the delivery of social services. Scholars posit that algorithms now govern and dictate the flow of information in many important ways, yet this is often not supported by empirical research and rarely involves interviews or focus groups with people from marginalized communities. This dissertation reveals what it feels like to be governed at a distance through a welfare algorithm. To explore this, I interviewed welfare recipients and caseworkers dealing with a software program that has removed much of their professional autonomy and discretion. Drawing from these in-depth interviews, including interviews with two software programmers who offered insight into algorithmic control of software systems, I reveal how a software program works to construct the 'ideal' welfare recipient. As this dissertation demonstrates, welfare recipients have developed techniques to resist this digitalized system through networks of support. Additionally, caseworkers have created 'unofficial' methods to bypass SAMS rigid regulations when they believe it is not flexible enough and often informally share these methods with each other. Welfare policy is being shaped and informed by the widespread belief that welfare recipients must often be forced into the workforce. As a result, SAMS software creates the 'ideal' welfare recipient, leading to an overall effect of the consolidation of the shift to employability being the ideal subjectivity.