It is essential that users understand how algorithmic decisions are made, as we increasingly delegate important decisions to intelligent systems. Prior work has often taken a techno-centric approach, focusing on new computational techniques to support transparency. In contrast, this article employs empirical methods to better understand user reactions to transparent systems to motivate user-centric designs for transparent systems. We assess user reactions to transparency feedback in four studies of an emotional analytics system. In Study 1, users anticipated that a transparent system would perform better but unexpectedly retracted this evaluation after experience with the system. Study 2 offers an explanation for this paradox by showing that the benefits of transparency are context dependent. On the one hand, transparency can help users form a model of the underlying algorithm's operation. On the other hand, positive accuracy perceptions may be undermined when transparency reveals algorithmic errors. Study 3 explored real-time reactions to transparency. Results confirmed Study 2, in showing that users are both more likely to consult transparency information and to experience greater system insights when formulating a model of system operation. Study 4 used qualitative methods to explore real-time user reactions to motivate transparency design principles. Results again suggest that users may benefit from initially simplified feedback that hides potential system errors and assists users in building working heuristics about system operation. We use these findings to motivate new progressive disclosure principles for transparency in intelligent systems and discuss theoretical implications.

Aaron Springer

Steve Whittaker

ACM Transactions on Interactive Intelligent Systems

ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS (TIIS) 发表有关包含某种形式的机器智能的交互式系统的设计、实现或评估的研究论文。 TIIS 文章来自广泛的研究领域和社区。一篇文章可以采用交互式智能系统的几种互补观点中的任何一种，重点关注：智能技术、用户与系统的交互，或同时关注这两个方面。

ACM Transactions on Interactive Intelligent Systems (TIIS) publishes research papers on the design, implementation, or evaluation of interactive intelligent systems that incorporate some form of machine intelligence. Articles in TIIS come from a wide range of research fields and communities. Each paper may adopt any of several complementary perspectives on interactive intelligent systems, focusing on intelligent technologies, user-system interaction, or both aspects simultaneously.

《ACM Transactions on Interactive Intelligent Systems》 (TIIS) 发表关于交互式智能系统的设计、实现或评估的研究论文，这些系统包含某种形式的机器智能。TIIS 的文章涵盖广泛的研究领域和社区。每篇文章可以从多个互补的视角探讨交互式智能系统，重点关注智能技术、用户与系统的交互，或同时关注这两个方面。

ACM Trans. Interact. Intell. Syst.

Progressive Disclosure

Empirical methods are employed to better understand user reactions to transparent systems to motivate user-centric designs for transparent systems and to motivate new progressive disclosure principles for transparency in intelligent systems.

Category	Quartile
计算机科学	4
计算机科学, 计算机人工智能	4

Progressive Disclosure

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Journal Info

Category	Quartile
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	2