fficient and trustworthy decision making through human-in-the-loopvisual analytics: A case study on tax risk assessment
- Autores: Walter Didimo, Luca Grilli, Giuseppe Liotta, Fabrizio Montecchiani
- Localización: Rivista italiana di Informatica e Diritto (RIID): Periodico Internazionale del CNR-IGSG, ISSN-e 2704-7318, Nº. 2, 2022, págs. 15-21
- Idioma: varios idiomas
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Resumen
Data mining and AI techniques are increasingly being used to automate data analysis. Ideally, one may wishto completely automate the data analysis process, but in many real-world applications a full automationmay pose significant risks. In these cases, human analysts must be directly involved to refine the analysis orto make the final decisions. A challenging problem, therefore, is how to perform efficient and trustworthydecision-making when humans are an integral part of the analysis pipeline. We propose a “human-in-the-loop” methodology that leverages data mining, machine learning, and visual analytics to improve and speedup the analysis. A key feature is the use of a dashboard that integrates intuitive visual tools, which aidanalysts to efficiently discover hidden data patterns or to get helpful insights. We describe in particular howthis methodology has been successfully applied to support Revenue Agency officers in tax risk assessment.
