The impact of system transparency on analytical reasoning

Conference paper

Hepenstal, S., Zhang, L. and Wong, B.L.W. 2023. The impact of system transparency on analytical reasoning.
AuthorsHepenstal, S., Zhang, L. and Wong, B.L.W.
TypeConference paper
Description

In this paper, we present the hypothesis that system transparency is critical for tasks that involve expert sensemaking. Artificial Intelligence (AI) systems can aid criminal intelligence analysts, however, they are typically opaque, obscuring the underlying processes that inform outputs, and this has implications for sensemaking. We report on an initial study with 10 intelligence analysts who performed a realistic investigation exercise using the Pan natural language system [10, 11], in which only half were provided with system transparency. Differences between conditions are analysed and the results demonstrate that transparency improved the ability of analysts to reason about the data and form hypotheses.

KeywordsArtificial intelligence; Decision support; Intelligence analysis; Expert decision making
Year2023
ConferenceCHI23
Official URLhttps://chi2023.acm.org/
Related URLhttps://dl.acm.org/conference/chi
Book titleCHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
Web address (URL) of conference proceedingshttps://doi.org/10.1145/3544549.3585786
Publisher's version
File Access Level
Controlled
Publication process dates
Deposited25 Apr 2023
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