Changing the Activation of At-Risk Jobseekers: Algorithmically Redefining Categories of Vulnerability

Abstract

This study investigates how the use of algorithms to analyse and support jobseekers by public employment services (PESs) redefines categories of vulnerability through the technology’s quantitative lens. We investigate the case of VDAB, the Flemish PES, which has introduced an algorithmic dashboard to visualise jobseekers’ efforts in finding work. Originally introduced to make decision-making processes more fair, less biased, and more efficient, algorithmic analyses, we show, have contributed to the reorientation of the organisation’s counsellors towards specific data points that render their historically determined differences (race, class, etc.) invisible but reformulate a new category of vulnerability. This category, digital illiteracy, is the new determinant of jobseekers’ support trajectories and becomes the main criteria for their estimated success in finding work. This study builds on qualitative interviews, meetings with management and document analysis to add to our understanding of how PESs utilise algorithmic technology to recontextualise and interpret jobseekers’ efforts in finding work.