Publication Type
Blog Post
Version
publishedVersion
Publication Date
6-2022
Abstract
The post highlights three main issues that may result from the rapid and widespread automation of jobs: 1) declining tax revenues; 2) inequitable distribution of gains and losses from automation; and 3) social costs of job displacement, such as social support and retraining programmes for displaced workers.An automation tax may be imposed on a temporary basis to manage (slow) the rate of displacement of workers due to the adoption of automation technologies, but should not be a permanent feature. Otherwise, there will be a risk of loss of competitiveness in the long-term, possibly resulting in even greater economic harm.One main problem with an automation tax is figuring out what to base the tax on. Attempts to tax "robots" have faced difficulties in defining what a robot is.A potential solution proposed in the paper is to build on the existing capital allowance/depreciation mechanisms. Such frameworks in many tax systems are schedular, allowing governments the flexibility of attaching a particular tax benefit to each item in the schedule. An automation tax could be determined based on the type of technology adopted and the field it is applied in, correlating with the social costs associated with its adoption (which can be conceptualised as “negative depreciation”).This mechanism could also allow for a distinction to be drawn between employment-substituting technologies, which render human workers redundant and should be disincentived, and employment-complementing technologies, which can be used by human workers to enhance their productivity, and which should be incentivised.
Keywords
Tax Law, Taxation, Automation Taxation, Robot Tax, Regulation, Tax and Regulation, Labour Law
Discipline
Business Organizations Law | Corporate Finance | Tax Law
Research Areas
Innovation, Technology and the Law; Corporate, Finance and Securities Law
Publisher
Association for Computing Machinery (ACM)
Citation
OOI, Vincent.
An automation tax- adopt with caution. (2022).
Available at: https://ink.library.smu.edu.sg/sol_research/3966
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.