Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes – On the Potential of XAI in Tax Audit Processes

Nijat Mehdiyev (), Constantin Houy (), Oliver Gutermuth (), Lea Mayer () and Peter Fettke ()
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Nijat Mehdiyev: Saarland University
Constantin Houy: Saarland University
Oliver Gutermuth: Saarland University
Lea Mayer: Saarland University
Peter Fettke: Saarland University

A chapter in Innovation Through Information Systems, 2021, pp 413-428 from Springer

Abstract: Abstract Artificial Intelligence (AI) can offer significant potential for public administrations which – in Germany – are likely to face considerable skills shortages in the next few years. AI systems can especially support the automation of processes and thus disburden administrative staff. As transparency and fairness play a major role in administrative processes, explainable AI (XAI) approaches are expected to enable a proper usage of AI in public administration. In this article, we investigate the potential of XAI for the support of tax authority processes, especially the selection of tax audit target organizations. We illustrate relevant tax audit scenarios and present the potential of different XAI techniques which we currently develop in these scenarios. It shows that XAI can significantly support tax audit preparations resulting in more efficient processes and a better performance of tax authorities concerning their main responsibilities. A further contribution of this article lies in the exemplary application of XAI usage guidelines in the public administration context.

Keywords: Explainable Artificial Intelligence; XAI; Public administration; Tax audit (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-86790-4_28

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DOI: 10.1007/978-3-030-86790-4_28

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