Strategic and Competitive Uses of Information & Digital Technologies (SCUIDT)
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Paper Type
Complete
Paper Number
1533
Description
Digital products and services make it possible to use data profitably. Particularly in highly complex applications, e.g., as those found in modern industry, such digital services in the form of intelligent decision support systems (DSS) can be a great support for human decision-making. On the other hand, these systems are subject to criticism because the underlying calculations are often not transparent and contain a residual error. This may be reflected in user rejection of the system’s advice. To better understand the impact of such systems, the paper addresses the problem with an empirical investigation towards user confidence and performance. An industrial quality inspection scenario is used as an applied application case. The results highlight that intelligent DSSs affect and even improve user confidence and corresponding to their related performance. However, a significant difference in the influence of different transparency levels between black-box-, grey-box-, and white-box-based DSS tool support was rejected.
Recommended Citation
Wanner, Jonas, "Do you really want to know why? Effects of AI-based DSS Advice on Human Decisions" (2021). AMCIS 2021 Proceedings. 13.
https://aisel.aisnet.org/amcis2021/strategic_is/strategic_is/13
Do you really want to know why? Effects of AI-based DSS Advice on Human Decisions
Digital products and services make it possible to use data profitably. Particularly in highly complex applications, e.g., as those found in modern industry, such digital services in the form of intelligent decision support systems (DSS) can be a great support for human decision-making. On the other hand, these systems are subject to criticism because the underlying calculations are often not transparent and contain a residual error. This may be reflected in user rejection of the system’s advice. To better understand the impact of such systems, the paper addresses the problem with an empirical investigation towards user confidence and performance. An industrial quality inspection scenario is used as an applied application case. The results highlight that intelligent DSSs affect and even improve user confidence and corresponding to their related performance. However, a significant difference in the influence of different transparency levels between black-box-, grey-box-, and white-box-based DSS tool support was rejected.
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