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Data quality and analysts’ role in AI enhanced C2
Mälardalen University (SWE).ORCID iD: 0000-0003-4572-9623
University West, Department of Social and Behavioural Studies, Division of Psychology, Pedagogy and Sociology.ORCID iD: 0000-0003-0394-9724
Mälardalen University (SWE).ORCID iD: 0000-0002-5792-7240
Swedish Defence Research Agency (SWE).
2023 (English)In: International Command and Control Research and Technology Symposium (ICCRTS) proceedings, 2023Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Artificial Intelligence (AI) in Command and Control (C2) raises questions about the interaction between operators on different levels on the one hand and AI-supported information systems on the other. For some purposes, the aggregation and analysis of large “big data”-sets creates potential for prediction and calculations of probabilities, while for other purposes human heuristics may be as promising depending on the situation. What has been more rarely discussed, is the very quality of data underpinning such calculations, and thus also operators’ awareness of the validity of predictions in relation to any specific situation. This is an urgent debate, considering the fact that full transparency may be impossible and underpinning data may be based on exercises, simulations, real-time data, or a mix thereof. Based on a fundamental classification of different kinds of uncertainties, this article discusses how data of different origins and quality can be managed and communicated to allow for operators to assess on what basis predictions are made. The article further suggests that looking at other fields of research may be useful for exploring unconventional ways of highlighting the existence and quality of different kinds of data of different origins in order to assess its predictive power. Finally, the article discusses how AI may change the role of analysts with regard to such issues.

Place, publisher, year, edition, pages
2023.
Series
International Command and Control Research and Technology Symposium (ICCRTS) proceedings, ISSN 2577-1604
Keywords [en]
Artificial Intelligence (AI), Command and Control (C2)
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hv:diva-21138OAI: oai:DiVA.org:hv-21138DiVA, id: diva2:1822636
Conference
28th International Command And Control Research & Technology Symposium 28-30 November 2023 - Laurel, Maryland, USA
Available from: 2023-12-27 Created: 2023-12-27 Last updated: 2023-12-27

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Schüler, Martin

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