Taxation of Automation and Artificial Intelligence as a Tool of Labour Policy

29 Pages Posted: 2 Feb 2019

See all articles by Vincent Ooi

Vincent Ooi

Singapore Management University - School of Law; Singapore Management University - Centre for AI & Data Governance

Glendon Goh

University of Oxford, Students

Date Written: November 1, 2018

Abstract

Rapid developments in automation technology pose a risk of mass displacement of human labour, resulting in the need to support and retrain displaced workers (a negative externality). We propose an “automation tax” that would slow the adoption of automation technology in appropriate circumstances, giving workers and social support systems time to adapt. This could be easily implemented through changes to the existing schedular system of depreciation/ capital allowances, reducing the uncertainty of its application and implementation costs. Such a system would be flexible enough to keep up with rapid technological developments. Two main dimensions may be adjusted to produce intended distortionary effects: 1) accelerated depreciation, and 2) bonus depreciation. While the benefits of efficiency gains mean that the automation tax is unlikely to have widespread application, it does provide a useful tool for specific situations where the rate of automation needs to be slowed due to its resultant social costs.

Keywords: Tax Law, Taxation, Automation Taxation, Robot Tax, Regulation, Tax and Regulation, Labour Law

Suggested Citation

Ooi, Vincent and Goh, Glendon, Taxation of Automation and Artificial Intelligence as a Tool of Labour Policy (November 1, 2018). SMU Centre for AI & Data Governance Research Paper No. 2019/01. Available at SSRN: https://ssrn.com/abstract=3322306 or http://dx.doi.org/10.2139/ssrn.3322306

Vincent Ooi (Contact Author)

Singapore Management University - School of Law ( email )

55 Armenian Street
Singapore, 179943
Singapore

HOME PAGE: http://law.smu.edu.sg/faculty/profile/156436/Vincent-OOI

Singapore Management University - Centre for AI & Data Governance ( email )

55 Armenian Street
Singapore
Singapore

Glendon Goh

University of Oxford, Students ( email )

Oxford
United Kingdom

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