Algorithmic Decision Making in Public Administration: A CSCW-Perspective

dc.contributor.authorFlügge, Asbjörn Ammitzböll
dc.description.abstractIn this paper, I propose a study of algorithmic decision making in public administration from a computer supported cooperative work (CSCW) perspective. Each day the public administration makes thousands of decisions with consequences for the welfare of its citizens. An increasing number of such decisions are supported or made by algorithmic decision making (ADM) systems, yet in the scientific and public sphere there is a growing concern that these algorithms become a 'black box' possibly containing hidden bias (Olsen et al., 2019), obstacles for human discretion (Rason, 2017), low transparency (Alkhatib and Bernstein, 2019) or trust (Mittelstadt et al. 2016). For example, ADM is currently tested in public administration in job placement for the prediction of a citizen's risk of long-term unemployment. Following prior research questioning the usefulness of the black box metaphor, my interest is to understand how caseworkers' and citizens understand ADM, as a basis for design of CSCW technologies employing ADM.en
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofCompanion Proceedings of the 2020 ACM International Conference on Supporting Group Work
dc.subjectcivic participation
dc.subjectpublic administration
dc.subjectalgorithmic decision making
dc.subjectcollaborative work
dc.titleAlgorithmic Decision Making in Public Administration: A CSCW-Perspectiveen
dc.typeText/Conference Paper
gi.conference.locationSanibel Island, Florida, USA