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A descriptive, practical, hybrid argumentation model to assist with the formulation of defensible assessments in uncertain sense-making environments: an initial evaluation

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Abstract

This paper presents the preliminary results of our initial, descriptive, practical, hybrid argumentation model, designed for the use by criminal intelligence analysts (from now on referred to as analysts) working with sophisticated visual analytical software in uncertain sense-making environments. Analysts are required to create exhibits (as evidence) for a court of law or as input for decision-making in intelligence-led policing. These exhibits are required to be accurate, relevant and unbiased. Eight experienced criminal intelligence analysts from West Midlands police and the Belgium police evaluated a low-fidelity prototype resembling the first-order argumentation concepts of our initial argumentation model. The evaluation was to assess the applicability and practicality of the first-order argumentation concepts within our model. The preliminary results presented in this paper indicate that most of the first-order argumentation concepts are both applicable and practical and that the participants would use such concepts to construct their rationale from the onset of an analytical activity, if it were included as part of a software application.

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Acknowledgements

The research results reported here have received funding from the European Union Seventh Framework Programme (FP7/2007–2013) through Project VALCRI, European Commission Grant Agreement N° FP7-IP-608142, awarded to B.L. William Wong, Middlesex University and partners. We are also very grateful for the enthusiasm of the police analysts in sharing with us their experiences that made this report possible. A special thanks to Nadeem Qazi for his time and effort to get the evaluation data into a usable format.

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Authors and Affiliations

  1. Middlesex University, NW4 4BT, London, UK

    Celeste Groenewald, Simon Attfield, Peter Passmore, B. L. William Wong, Nadeem Qazi & Neesha Kodagoda

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  1. Celeste Groenewald
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  2. Simon Attfield
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  3. Peter Passmore
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  4. B. L. William Wong
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  5. Nadeem Qazi
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  6. Neesha Kodagoda
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Correspondence to Celeste Groenewald.

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Groenewald, C., Attfield, S., Passmore, P. et al. A descriptive, practical, hybrid argumentation model to assist with the formulation of defensible assessments in uncertain sense-making environments: an initial evaluation. Cogn Tech Work 20, 529–542 (2018). https://doi.org/10.1007/s10111-018-0495-x

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