Algorithmic transparency of conversational agents

Hepenstal, Sam, Kodagoda, Neesha, Zhang, Leishi ORCID logoORCID:, Paudyal, Pragya and Wong, B. L. William ORCID logoORCID: (2019) Algorithmic transparency of conversational agents. Trattner, Christoph, Parra, Denis and Riche, Nathalie, eds. Joint Proceedings of the ACM IUI 2019 Workshops (ACMIUI-WS 2019). In: IUI 2019 Workshop on Intelligent User Interfaces for Algorithmic Transparency in Emerging Technologies, 17-20 Mar 2019, Los Angeles, CA, USA. . ISSN 1613-0073 [Conference or Workshop Item]

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A lack of algorithmic transparency is a major barrier to the adoption of artificial intelligence technologies within contexts which require high risk and high consequence decision making. In this paper we present a framework for providing transparency of algorithmic processes. We include important considerations not identified in research to date for the high risk and high consequence context of defence intelligence analysis. To demonstrate the core concepts of our framework we explore an example application (a conversational agent for knowledge exploration) which demonstrates shared human-machine reasoning in a critical decision making scenario. We include new findings from interviews with a small number of analysts and recommendations for future

Item Type: Conference or Workshop Item (Paper)
Additional Information: Vol-2327
Research Areas: A. > School of Science and Technology
Item ID: 27914
Notes on copyright: Copyright © 2019 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.
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Depositing User: Leishi Zhang
Date Deposited: 21 Oct 2019 08:04
Last Modified: 21 Apr 2020 10:58

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