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

2022/02/10 by Stephan Grimmelikhuijsen · 211 citations
Computer Science · Social Sciences · #Blockchain Technology Applications and Security #Bureaucracy #Computer science #Computer security #Context (archaeology) #Decision maker #Discretion #Economics #Ethics and Social Impacts of AI #Internet privacy #Law #Management science #Political science #Privacy-Preserving Technologies in Data #Transparency (behavior) #Trustworthiness

paper · pdf · doi:10.1111/puar.13483

published in Public Administration Review 83(2), 241-262 (Wiley)

openalex publication_date 2022/02/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

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.

Citations

• Policy Area as a Potential Moderator of Transparency Effects: An Experiment
• From Street‐Level to System‐Level Bureaucracies: How Information and Communication Technology is Transforming Administrative Discretion and Constitutional Control
• 25 Years of Transparency Research: Evidence and Future Directions
• Accountable Artificial Intelligence: Holding Algorithms to Account

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