Administration by Algorithm? Public Management meets Public Sector Machine Learning

This chapter first explains the types of machine learning systems used in the public sector, detailing the processes and tasks that they aim to support. It then looks at three levels of government—the macro, meso, and the street-level—to map out, analyse, and evaluate how machine learning in the public sector more broadly is framed and standardized across government. It concludes that, while the use of machine learning in the public sector is mostly discussed with regard to its ‘transformative effect’ versus ‘the dynamic conservatism’ characteristic of public bureaucracies that embrace new technological developments, it also raises several concerns about the skills, capacities, processes, and practices that governments currently employ, the forms of which can have value-laden, political consequences