Learning from successful urgent automation of case processing of public services during COVID-19

While promising faster, less expensive, more consistent, and more innovative public services, automating public case processing requires considering many values related to equity, effectiveness, compliance, and others. Examples of approaches that resolve these trade-offs can lead the way to fulfilling these promises responsibly. Under significant pressure to process large volumes of public service cases during the COVID-19 pandemic, several Norwegian government institutions successfully and independently of each other designed, developed, and implemented automated solutions that met their goals without violating public policy values. In-depth interviews and a confirmation workshop with leaders of these development efforts reveal shared value drivers, technical features, and successful design approaches relevant to realizing automation opportunities in the public sector. By learning from these success stories, our findings guide research and practice of automating public services in keeping with the public policies that drive them.

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Publication Details

Published
2025-05-03
DOI
https://doi.org/10.1109/iwsib66663.2025.00011
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Learning from successful urgent automation of case processing of public services during COVID-19

Karl Kristian Larsson, Jo Erskine Hannay, Leif Z. Knutsen
Data Mining and Machine Learning Applications
article

Learning from successful urgent automation of case processing of public services during COVID-19

Karl Kristian Larsson, Jo Erskine Hannay, Leif Z. Knutsen
article en

Abstract

While promising faster, less expensive, more consistent, and more innovative public services, automating public case processing requires considering many values related to equity, effectiveness, compliance, and others. Examples of approaches that resolve these trade-offs can lead the way to fulfilling these promises responsibly. Under significant pressure to process large volumes of public service cases during the COVID-19 pandemic, several Norwegian government institutions successfully and independently of each other designed, developed, and implemented automated solutions that met their goals without violating public policy values. In-depth interviews and a confirmation workshop with leaders of these development efforts reveal shared value drivers, technical features, and successful design approaches relevant to realizing automation opportunities in the public sector. By learning from these success stories, our findings guide research and practice of automating public services in keeping with the public policies that drive them.

Simula Metropolitan Center for Digital Engineering (NO)
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Data Mining and Machine Learning Applications
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Learning from successful urgent automation of case processing of public services during COVID-19 — Karl Kristian Larsson, Jo Erskine Hannay, et al. · (2025) | TGRS Research Map | TGRS