De La Feria, R and Amparo Grau Ruiz, M (2022) The Robotization of Tax Administration. In: Amparo Grau Ruiz, M, (ed.) Interactive Robotics: Legal, Ethical, Social and Economic Aspects: Selected Contributions to the INBOTS Conference 2021, 18-20 May, 2021. INBOTS Conference 2021, 18-20 May 2021 Biosystems & Biorobotics, 30 . Springer Nature , pp. 115-123. ISBN 978-3-031-04304-8
Abstract
Developments over the last decade in the use of AI in tax administration have been nothing short of outstanding. Not only are taxpayers increasingly making use of automated systems in tax compliance, but perhaps more importantly, tax enforcement is increasingly reliant on new technologies as compliance-enhancing and fraud-prevention tools. However, whilst the use of AI brings very significant advantages to both the efficiency and the equity of tax systems, it also carries important risks. This paper identifies the development of a new AI fallacy within the tax policy sphere, namely that of unconstrained success: that the use of AI in tax compliance and enforcement can compensate for the deficiencies of the tax law. This paper considers the rationale behind the development of this fallacy, in particular the political and institutional dynamics involved in the approval of new tax legislation. It concludes that, maximising the benefits of the use of AI in tax compliance and enforcement requires departure from this fallacy, and the recognition of the wider dynamics of the tax policy-administration symbiosis.
Metadata
Item Type: | Proceedings Paper |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/978-3-031-04305-5_19. |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) |
Funding Information: | Funder Grant number EU - European Union 780073 |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Mar 2022 16:06 |
Last Modified: | 05 Aug 2023 01:18 |
Status: | Published |
Publisher: | Springer Nature |
Series Name: | Biosystems & Biorobotics |
Identification Number: | 10.1007/978-3-031-04305-5_19 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184465 |