Algorithmic responsibility without accountability
Understanding data‐intensive algorithms and decisions in organisations
Publication date
2024-06-04
Document type
Forschungsartikel
Author
Organisational unit
Publisher
Wiley
Series or journal
Systems Research and Behavioral Science
ISSN
Periodical volume
42
Periodical issue
3
First page
739
Last page
755
Part of the university bibliography
✅
Language
English
Keyword
dtec.bw
Abstract
Social science research has been concerned for several years with the issue of shifting responsibilities in organisations due to the increased use of data‐intensive algorithms. Much of the research to date has focused on the question of who should be held accountable when ‘algorithmic decisions’ turn out to be discriminatory, erroneous or unfair. From a sociological perspective, it is striking that these debates do not make a clear distinction between responsibility and accountability. In our paper, we draw on this distinction as proposed by the German social systems theorist Niklas Luhmann. We use it to analyse the changes and continuities in organisations related to the use of data‐intensive algorithms. We argue that algorithms absorb uncertainty in organisational decision‐making and thus can indeed take responsibility but cannot be made accountable for errors. By using algorithms, responsibility is fragmented across people and technology, while assigning accountability becomes highly controversial. This creates new discrepancies between responsibility and accountability, which can be especially consequential for organisations' internal trust and innovation capacities.
Description
This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Version
Published version
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