Supporting detection of hostile intentions: automated assistance in a dynamic decision-making context

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Date

2023-11

Journal Title

Journal ISSN

Volume Title

Publisher

Springer Science and Business Media LLC

Abstract

In a dynamic decision-making task simulating basic ship movements, participants attempted, through a series of actions, to elicit and identify which one of six other ships was exhibiting either of two hostile behaviors. A high-performing, although imperfect, automated attention aid was introduced. It visually highlighted the ship categorized by an algorithm as the most likely to be hostile. Half of participants also received automation transparency in the form of a statement about why the hostile ship was highlighted. Results indicated that while the aid’s advice was often complied with and hence led to higher accuracy with a shorter response time, detection was still suboptimal. Additionally, transparency had limited impacts on all aspects of performance. Implications for detection of hostile intentions and the challenges of supporting dynamic decision making are discussed.

Description

Keywords

Dynamic decision making, Automation, Trust, Transparency

Citation

Patton, C.E., Wickens, C.D., Smith, C.A.P. et al. Supporting detection of hostile intentions: automated assistance in a dynamic decision-making context. Cogn. Research 8, 69 (2023). https://doi.org/10.1186/s41235-023-00519-5
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