Although algorithms are increasingly used to support professional tasks and routine decision-making, their opaque nature invites resistance and results in suboptimal use of their advice. Scholars argue for transparency to enhance the acceptability of algorithmic advice. However, current research is limited in understanding how improved transparency enhances the use of algorithmic advice, such as the differences among various aspects of transparency and the underlying mechanism. In this paper, we investigate whether and how different aspects of algorithmic transparency (performance, process, and purpose) enhance the use of algorithmic advice. Drawing on the knowledge-based trust perspective, we examine the mediating roles of trusting beliefs in the relationships between transparency and the use of algorithmic advice. Using the “judge-advisor system” paradigm, we conduct a 2 × 2 × 2 experiment to manipulate the three aspects of transparency and examine their effects on the use of algorithmic advice. We find that performance and process transparency promote the use of algorithmic advice. However, the effect of process transparency gets attenuated when purpose transparency is high. Purpose transparency is only useful when process transparency is low. We also find that while all three aspects of transparency facilitate different trusting beliefs, only competence belief significantly promotes the use of algorithmic advice. It also fully mediates the facilitating effects of performance and process transparency. This study contributes to the emerging research on algorithmic decision support by empirically investigating the effects of transparency on the use of algorithmic advice and identifying the underlying mechanism. The findings also provide practical guidance on how to promote the acceptance of algorithmic advice that is valuable to both individual users and practitioners.

中文翻译：

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透明度如何影响算法建议的利用：信任信念的中介作用


尽管算法越来越多地用于支持专业任务和日常决策，但其不透明的性质会招致阻力，并导致其建议的使用不理想。学者们主张透明度可以提高算法建议的可接受性。然而，目前的研究仅限于理解提高透明度如何增强算法建议的使用，例如透明度各个方面和底层机制之间的差异。在本文中，我们研究了算法透明度的不同方面（性能、过程和目的）是否以及如何增强算法建议的使用。利用基于知识的信任视角，我们研究了信任信念在透明度与算法建议的使用之间关系中的中介作用。使用“法官-顾问系统”范式，我们进行了 2 × 2 × 2 实验来操纵透明度的三个方面，并检查它们对算法建议的使用的影响。我们发现性能和流程透明度促进了算法建议的使用。然而，当目的透明度较高时，流程透明度的效果就会减弱。仅当流程透明度较低时，目的透明度才有用。我们还发现，虽然透明度的所有三个方面都会促进不同的信任信念，但只有能力信念才能显着促进算法建议的使用。它还充分调解了绩效和流程透明度的促进效应。本研究通过实证研究透明度对算法建议使用的影响并确定潜在机制，为算法决策支持的新兴研究做出了贡献。 研究结果还为如何促进对个人用户和从业者都有价值的算法建议的接受提供了实用指导。