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

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.

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Publication Details

Journal
Public Administration
Published
2026-09-11
DOI
https://doi.org/10.1111/padm.70092
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Jan-Luuk Hoff, Lukas Lorenz, Albert Jacob Meijer, Isabelle Donatz-Fest
Public Administration
Ethics and Social Impacts of AI
article

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

Jan-Luuk Hoff, Lukas Lorenz, Albert Jacob Meijer, Isabelle Donatz-Fest
article en

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.

Public Administration
Utrecht University (NL), Gemeente Den Haag (NL), Bundesverband der Selbständigen Deutscher Gewerbeverband (DE), Vrije Universiteit Amsterdam (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Peace, Justice and strong institutions
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
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