Designing a system to mimic expert cognition: An initial prototype

Journal article

Hepenstal, Sam, Zhang, Leishi and William Wong, B. L. 2022. Designing a system to mimic expert cognition: An initial prototype. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66 (1), pp. 2057-2061. https://doi.org/10.1177/1071181322661092
AuthorsHepenstal, Sam, Zhang, Leishi and William Wong, B. L.
AbstractIn this paper, we present a proof-of-concept system to highlight the potential benefits of mimicking higher-order cognitive processes involved in ‘insight seeking’ to create the necessary context for expert sensemaking. We draw upon data from a realistic investigation exercise undertaken by 14 experienced intelligence analysts and use this to develop our prototype to mimic behaviours demonstrated by expert analysts. Our prototype system evaluates different strategies and provides recommendations for an analyst to explore, through a prototype user interface. The recommended strategies, and associated information retrieved, aligns with the actual investigations. We propose that our system presents a novel and promising approach to design AI support systems for tasks that typically require human expert cognitive processes.
KeywordsAI; Artificial intelligence ; Expert cognition
Year2022
JournalProceedings of the Human Factors and Ergonomics Society Annual Meeting
Journal citation66 (1), pp. 2057-2061
PublisherSAGE
ISSN2169-5067
1071-1813
Digital Object Identifier (DOI)https://doi.org/10.1177/1071181322661092
Official URLhttps://doi.org/10.1177/1071181322661092
Publication dates
Print27 Nov 2022
Online27 Oct 2022
Publication process dates
Deposited02 Nov 2022
Accepted23 May 2022
Accepted author manuscript
License
Output statusPublished
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https://repository.canterbury.ac.uk/item/92zqw/designing-a-system-to-mimic-expert-cognition-an-initial-prototype

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Accepted author manuscript
InsightSeekingpaper-HFES2022.pdf
License: CC BY-NC 4.0

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