Responsible Algorithmization in the Public Sector: A “Natural Perspective” Based on Ethnographic Research in Regulation, Policing, and Healthcare

Original

Responsible Algorithmization in the Public Sector: A “Natural Perspective” Based on Ethnographic Research in Regulation, Policing, and Healthcare

Albert Meijer, Lukas Lorenz, Isabelle Donatz‐Fest, Jan‐Luuk Hoff

Abstract

ABSTRACT Responsible algorithmization refers to the use of algorithms in the public sector while safeguarding public values. Approaches to responsible algorithmization suggested by the EU, OECD, and others depart from a rational perspective and highlight formal structures and procedures. This paper complements this perspective by adding a “natural perspective,” which emphasizes sense‐making and actual practices. This natural perspective is used for a set of ethnographic studies of algorithmization in three domains in the Netherlands: regulation, policing, and healthcare. Our findings show that algorithmization of government organizations is an emergent, political, open, and fragmented process, rather than, as assumed by rational approaches to responsible algorithmization, pre‐structured, neutral, closed, and simple. This means that rational approaches fall short of providing a comprehensive basis for establishing responsible algorithmization. We conclude that not only passive responsibility but also active responsibility for algorithmization in the public sector needs to be addressed to safeguard public values.