Research Handbook in Data Science and Law
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Research Handbook in Data Science and Law

Edited by Vanessa Mak, Eric Tjong Tjin Tai and Anna Berlee

The use of data in society has seen an exponential growth in recent years. Data science, the field of research concerned with understanding and analyzing data, aims to find ways to operationalize data so that it can be beneficially used in society, for example in health applications, urban governance or smart household devices. The legal questions that accompany the rise of new, data-driven technologies however are underexplored. This book is the first volume that seeks to map the legal implications of the emergence of data science. It discusses the possibilities and limitations imposed by the current legal framework, considers whether regulation is needed to respond to problems raised by data science, and which ethical problems occur in relation to the use of data. It also considers the emergence of Data Science and Law as a new legal discipline.
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Chapter 13: Data science and taxation

Ronald Russo

Abstract

This chapter looks at data science in the field of taxation, with an emphasis on the taxation of companies. The focus is on the point of view of companies as well as tax authorities. The former are affected by data science in relation to their financial accounts; and the quality thereof by the functioning of their internal auditing system. This then provides the input for financial accounts and tax accounts. The tax accounts a company maitains are discussed in this chapter as well as how data science – in particular in managing data – may relate to these tax accounts. Secondly, this chapter looks at the role of tax authorities and how the emerging field of data science impacts their work. Here too the wealth of information that reaches these authorities requires managing. The legal boundaries in which the authorities may make use of this data are discussed in this chapter as well. Finally, the contribution looks at, and provides comments on, the Intra-European Organization of Tax Administration’s 2017 report on data science and taxation, which discusses, among others, data management, predictive modelling, social network analysis and data visualization.

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