De La Feria, R and Amparo Grau Ruiz, M (2022) Taxing Robots. 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. 93-99. ISBN 978-3-031-04304-8
Abstract
In recent years, the idea of taxing robots has been progressively gaining momentum. The potential impact of automation on employment, and consequently on income tax revenues, has led many to defend the introduction of a tax on robots, or on the use of robots, to either compensate for the potential revenue loss, or to slow down the process of automation. This paper argues that whilst automation presents significant challenges to tax systems, the introduction of a new tax on robots –or on their use– are not effective mechanisms through which to address these challenges. In order to explain the growing popularity of taxing robots, the paper draws insights from behavioral science. It concludes that the growing support for such a tax is more a reflection of unconscious and institutional biases, than it is of sound taxation principles.
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_16. |
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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 15:57 |
Last Modified: | 01 Sep 2023 19:06 |
Status: | Published |
Publisher: | Springer Nature |
Series Name: | Biosystems & Biorobotics |
Identification Number: | 10.1007/978-3-031-04305-5_16 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184463 |