Algorithmic decision making in public administration: A CSCW-perspective

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Algorithmic decision making in public administration : A CSCW-perspective. / Flügge, Asbjørn Ammitzbøll.

GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work. Association for Computing Machinery, 2020. p. 15-24.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Flügge, AA 2020, Algorithmic decision making in public administration: A CSCW-perspective. in GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work. Association for Computing Machinery, pp. 15-24, 21st ACM International Conference on Supporting Group Work, GROUP 2020, Sanibel Island, United States, 06/01/2020. https://doi.org/10.1145/3323994.3371016

APA

Flügge, A. A. (2020). Algorithmic decision making in public administration: A CSCW-perspective. In GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work (pp. 15-24). Association for Computing Machinery. https://doi.org/10.1145/3323994.3371016

Vancouver

Flügge AA. Algorithmic decision making in public administration: A CSCW-perspective. In GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work. Association for Computing Machinery. 2020. p. 15-24 https://doi.org/10.1145/3323994.3371016

Author

Flügge, Asbjørn Ammitzbøll. / Algorithmic decision making in public administration : A CSCW-perspective. GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work. Association for Computing Machinery, 2020. pp. 15-24

Bibtex

@inproceedings{ea49f3c3523748b4a2b449c3a623a838,
title = "Algorithmic decision making in public administration: A CSCW-perspective",
abstract = "In 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.",
keywords = "Algorithmic decision making, Casework, Civic participation, Collaborative work, Public administration, Transparency, Trust",
author = "Fl{\"u}gge, {Asbj{\o}rn Ammitzb{\o}ll}",
year = "2020",
doi = "10.1145/3323994.3371016",
language = "English",
pages = "15--24",
booktitle = "GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work",
publisher = "Association for Computing Machinery",
note = "21st ACM International Conference on Supporting Group Work, GROUP 2020 ; Conference date: 06-01-2020 Through 08-01-2020",

}

RIS

TY - GEN

T1 - Algorithmic decision making in public administration

T2 - 21st ACM International Conference on Supporting Group Work, GROUP 2020

AU - Flügge, Asbjørn Ammitzbøll

PY - 2020

Y1 - 2020

N2 - In 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.

AB - In 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.

KW - Algorithmic decision making

KW - Casework

KW - Civic participation

KW - Collaborative work

KW - Public administration

KW - Transparency

KW - Trust

UR - http://www.scopus.com/inward/record.url?scp=85078335723&partnerID=8YFLogxK

U2 - 10.1145/3323994.3371016

DO - 10.1145/3323994.3371016

M3 - Article in proceedings

AN - SCOPUS:85078335723

SP - 15

EP - 24

BT - GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work

PB - Association for Computing Machinery

Y2 - 6 January 2020 through 8 January 2020

ER -

ID: 240685549