Inside algorithmic bureaucracy: Disentangling automated decision-making and good administration

Abstract

Public administrative bodies around the world are increasingly applying automated, administrative decision-making as underlying technologies such as machine learning mature. Such decision-making is a central element of emerging forms of algorithmic bureaucracies. With its direct exercise of public authority over individual citizens and firms, automated, administrative decision-making makes it particularly important to consider relations to values of good administration. Based on a multiple case-study, the article focuses on how empirical use of automated decision-making influences and transforms issues of good administration in four policy areas in Denmark: Business and social policy; labour market policy; agricultural policy; and tax policy. Supplementing emerging literature, the article exemplifies how public authorities struggle to apply automated decision-making in ways that support rather than undermine good administration. We identify six empirical relations of usage of automated, administrative decision-making and good administration: (I) Giving accurate and comprehensible reasons; (II) Informing addressees’ expectations; (III) Combining material and algorithmic expertise; (IV) Achieving effective oversight; (V) Continuously ensuring quality; and (VI) Managing high complexity. Additionally, we pinpoint related key capabilities for administrative bodies in order to support good administration.