Simplification of Administrative Procedures through Fully Automated Decision-Making: The Case of Norway

Weitzenboeck, Emily M. (2021) Simplification of Administrative Procedures through Fully Automated Decision-Making: The Case of Norway. Administrative Sciences, 11 (4). p. 149. ISSN 2076-3387

[thumbnail of admsci-11-00149-v2.pdf] Text
admsci-11-00149-v2.pdf - Published Version

Download (327kB)

Abstract

Norway has a high degree of digitalisation. In the public sector, there is a long tradition of automation of parts of case management. This includes automation of cases where a public sector body makes a so-called individual administrative decision, that is, a decision made in the exercise of public authority through which the rights or duties of one or more specified private persons are determined. In the last five years, various amendments to public sector legislation were proposed by a number of government departments and agencies in Norway to ensure that the relative administrative agency has a legal basis to carry out fully automated individual decisions. This is challenging both from an administrative law and from a data protection law standpoint. Among the main reasons for the move towards fully automated legal decision-making that are mentioned in the preparatory works to the proposed amendments are greater efficiency in decision-making, equal treatment of citizens and a claim that such decisions will be less prone to error than human decisions. This paper examines this trend in Norway and identifies the statutes and regulations that have been amended or are in the process of being amended. It analyses the measures specified in these amendments to safeguard the individual party’s rights, freedoms and legitimate interests. Finally, it discusses the tightrope that must be walked to safeguard important administrative law principles and rules such as protection from arbitrary decisions, the audi alternam partem rule and the right under the European Union’s General Data Protection Regulation not to be subject to fully automated decisions.

Item Type: Article
Subjects: Librbary Digital > Multidisciplinary
Depositing User: Unnamed user with email support@librbarydigit.com
Date Deposited: 04 Sep 2024 04:34
Last Modified: 04 Sep 2024 04:34
URI: http://info.openarchivelibrary.com/id/eprint/1182

Actions (login required)

View Item
View Item