Shifting Concepts of Value: Designing Algorithmic Decision-Support Systems for Public Services
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Shifting Concepts of Value: Designing Algorithmic Decision-Support Systems for Public Services. / Møller, Naja L. Holten; Shklovski, Irina; Hildebrandt, Thomas Troels.
NordiCHI '20: Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society. Association for Computing Machinery, 2020. p. 1-12 70.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Shifting Concepts of Value: Designing Algorithmic Decision-Support Systems for Public Services
AU - Møller, Naja L. Holten
AU - Shklovski, Irina
AU - Hildebrandt, Thomas Troels
PY - 2020
Y1 - 2020
N2 - Calls for responsible design in algorithmic decision-support systems, especially those used in public services, are increasingly common. While an algorithmic system might promise greater precision and efficiency in domains such as critical care, the same efficiency is difficult to replicate in the public service domain, where caseworkers must exercise discretion in applying complex legal frameworks that directly affect individual lives. In this paper we examine the challenges in responsibly designing such an algorithmic decision-support system. We report findings from a large cross-disciplinary research project, aiming to develop an algorithmic component for municipal decision-support systems for job placement in Denmark. Our data showcases insights from how a team of data scientists, caseworkers, and system developers negotiated notions of value metrics and usefulness in a participatory design set-up. Whereas data scientists expected to focus on profiling individuals, the caseworkers instead pushed for systems that could help mitigate organizational contradictions and obscured processes in casework. We close with a discussion of challenges and future directions for participatory algorithmic systems design in municipal contexts.
AB - Calls for responsible design in algorithmic decision-support systems, especially those used in public services, are increasingly common. While an algorithmic system might promise greater precision and efficiency in domains such as critical care, the same efficiency is difficult to replicate in the public service domain, where caseworkers must exercise discretion in applying complex legal frameworks that directly affect individual lives. In this paper we examine the challenges in responsibly designing such an algorithmic decision-support system. We report findings from a large cross-disciplinary research project, aiming to develop an algorithmic component for municipal decision-support systems for job placement in Denmark. Our data showcases insights from how a team of data scientists, caseworkers, and system developers negotiated notions of value metrics and usefulness in a participatory design set-up. Whereas data scientists expected to focus on profiling individuals, the caseworkers instead pushed for systems that could help mitigate organizational contradictions and obscured processes in casework. We close with a discussion of challenges and future directions for participatory algorithmic systems design in municipal contexts.
U2 - 10.1145/3419249.3420149
DO - 10.1145/3419249.3420149
M3 - Article in proceedings
SP - 1
EP - 12
BT - NordiCHI '20: Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society
PB - Association for Computing Machinery
T2 - 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society
Y2 - 25 October 2020 through 29 October 2020
ER -
ID: 251255257