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 4: Liability for (semi)autonomous systems: robots and algorithms

Eric Tjong Tjin Tai

Abstract

Liability for robots and algorithms is at present unclear. A comparative overview shows that while several grounds for liability may apply, depending on the jurisdiction, there are still significant gaps, in particular regarding liability for algorithms. Several changes would be required to provide effective protection of interests that may be harmed by defective autonomous systems. By careful regulation a proper balance may be obtained between allowing innovation without undue harm for society.

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