Explaining Why the Computer Says No: Algorithmic Transparency Affects the Perceived Trustworthiness of Automated Decision-Making

Stephan Grimmelikhuijsen

doi:10.1111/puar.13483

Explaining Why the Computer Says No: Algorithmic Transparency Affects the Perceived Trustworthiness of Automated Decision-Making

Stephan Grimmelikhuijsen^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Algorithms based on Artificial Intelligence technologies are slowly transforming street-level bureaucracies, yet a lack of algorithmic transparency may jeopardize citizen trust. Based on procedural fairness theory, this article hypothesizes that two core elements of algorithmic transparency (accessibility and explainability) are crucial to strengthening the perceived trustworthiness of street-level decision-making. This is tested in one experimental scenario with low discretion (a denied visa application) and one scenario with high discretion (a suspicion of welfare fraud). The results show that: (1) explainability has a more pronounced effect on trust than the accessibility of the algorithm; (2) the effect of algorithmic transparency not only pertains to trust in the algorithm itself but also—partially—to trust in the human decision-maker; (3) the effects of algorithmic transparency are not robust across decision context. These findings imply that transparency-as-accessibility is insufficient to foster citizen trust. Algorithmic explainability must be addressed to maintain and foster trustworthiness algorithmic decision-making.

Original language	English
Pages (from-to)	241-262
Number of pages	22
Journal	Public Administration Review
Volume	83
Issue number	2
DOIs	https://doi.org/10.1111/puar.13483
Publication status	Published - 1 Mar 2023

Bibliographical note

Funding Information:
Netherlands Organization for Scientific Research (NWO), Grant/Award Number: VENI‐451‐15‐024 Funding information

Funding Information:
I thank the following people for their comments on a previous version of paper and/or feedback on the experimental design: Mark Bovens, Albert Meijer, Floris Bex, Lars Tummers, Robin Bouwman and Marij Swinkels. I also thank three anonymous reviewers for their constructive feedback on the manuscript. Data collection was funded by a research grant from the Netherlands Organization for Scientific Research (NWO) under grant number: VENI‐451‐15‐024.

Publisher Copyright:
© 2022 The Author. Public Administration Review published by Wiley Periodicals LLC on behalf of American Society for Public Administration.

Funding

Netherlands Organization for Scientific Research (NWO), Grant/Award Number: VENI‐451‐15‐024 Funding information I thank the following people for their comments on a previous version of paper and/or feedback on the experimental design: Mark Bovens, Albert Meijer, Floris Bex, Lars Tummers, Robin Bouwman and Marij Swinkels. I also thank three anonymous reviewers for their constructive feedback on the manuscript. Data collection was funded by a research grant from the Netherlands Organization for Scientific Research (NWO) under grant number: VENI‐451‐15‐024.

Keywords

Artificial-intelligence
Procedural justice
Black-box
Government
Discretion
Big

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10.1111/puar.13483Licence: CC BY

Public Administration Review - 2022 - Grimmelikhuijsen - Explaining Why the Computer Says No Algorithmic TransparencyFinal published version, 1.05 MBLicence: CC BY

Cite this

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title = "Explaining Why the Computer Says No: Algorithmic Transparency Affects the Perceived Trustworthiness of Automated Decision-Making",

abstract = "Algorithms based on Artificial Intelligence technologies are slowly transforming street-level bureaucracies, yet a lack of algorithmic transparency may jeopardize citizen trust. Based on procedural fairness theory, this article hypothesizes that two core elements of algorithmic transparency (accessibility and explainability) are crucial to strengthening the perceived trustworthiness of street-level decision-making. This is tested in one experimental scenario with low discretion (a denied visa application) and one scenario with high discretion (a suspicion of welfare fraud). The results show that: (1) explainability has a more pronounced effect on trust than the accessibility of the algorithm; (2) the effect of algorithmic transparency not only pertains to trust in the algorithm itself but also—partially—to trust in the human decision-maker; (3) the effects of algorithmic transparency are not robust across decision context. These findings imply that transparency-as-accessibility is insufficient to foster citizen trust. Algorithmic explainability must be addressed to maintain and foster trustworthiness algorithmic decision-making.",

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Explaining Why the Computer Says No: Algorithmic Transparency Affects the Perceived Trustworthiness of Automated Decision-Making

Abstract

Bibliographical note

Funding

Keywords

Access to Document

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