The Artificial Intelligence Tax Treaty Assistant: Decoding the Principal Purpose Test
Posted: 29 Aug 2018 Last revised: 10 Sep 2018
Date Written: August 20, 2018
In this article, the author explores and advocates the use of an artificial intelligence tax treaty assistant with regard to resolving issues and problems in respect of the principal purpose test as proposed in relation to the OECD/G20 Base Erosion and Profit Shifting initiative. As the PPT is very complex and ambiguous, what AI learns in dealing with those cases could be put to use regarding other rules of a similar degree of complexity and ambiguity and with a largely similar purpose and nature. For instance, domestic GAARs could be addressed by an approach very similar to that as presented in this article. AI could eventually be applied to all types of anti-tax avoidance legislation. By augmenting the power of AI, a very effective means of preventing tax avoidance on a global scale should be possible. The question is only whether countries and jurisdictions across the world would welcome AI. AI could help them draft the most effective anti-tax avoidance laws and enforce them accordingly. In the author’s opinion, the application of AI in the domain of international tax avoidance is likely to be a “game changer” by not only improving the work of tax advisers and tax administrations across the world, but also the performance of tax systems globally.
Keywords: OECD, BEPS, tax avoidance, AI, machine learning, technology, disruption, international
JEL Classification: K33, K34, E62, E63, F62, H26, O23
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