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Eric Tjong Tjin Tai

In the discussion between formal and informal contract law it is suggested that networks would benefit from informal contract law. This hypothesis is tested with the example of Dutch contract law, which is relatively informal. Three case studies are explored, which suggest that an informal contract law does remove certain barriers, but introduces other problems. Further doctrinal research is required in order to adequately facilitate networks. Solutions should not solely be looked for in additional rules, but rather in proportionate remedies and procedure-oriented communication structures. Keywords: networks, linked contracts, contract law, informal contract law

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Eric Tjong Tjin Tai

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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Vanessa Mak, Eric Tjong Tjin Tai and Anna Berlee

This book deals with one of the most important scientific developments of recent years, namely the exponential growth of data science. More than a savvy term that rings of robotics, artificial intelligence and other terms that for long were regarded as part of science-fiction, data science has started to become structurally embedded in scientific research. Data, meaning personal data as well as information in the form of digital files, has become available at such a large scale that it can lead to an expansion of knowledge through smart combinations and use of data facilitated by new technologies. This book examines the legal implications of this development. Do data-driven technologies require regulation, and vice versa, how does data science advance legal scholarship? Defining the relatively new field of data science requires a working definition of the term. By data science we mean the use of data (including data processing) for scientific research. The availability of massive amounts of data as well the relatively cheap availability of storage and processing power has provided scientists with new tools that allow research projects that until recently were extremely cumbersome if not downright impossible. These factors are also often described with the term ‘big data’, which is characterized by three Vs: volume, velocity and variety.The term data science is nonetheless broader, because it can also refer to the use of data sets that are large but still limited—and therefore, unlike big data, of a manageable size for processing.

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Vanessa Mak, Eric Tjong Tjin Tai and Anna Berlee

At the outset of this book the question was put forth: do data-driven technologies require regulation, and vice versa, how does data science advance legal scholarship? While there is no resounding answer one way or the other to the first question, we can deduce from the analyses put forward by our authors that the rise of the so-called data economy does pose challenges to regulators. The challenges are diverse and the answers to the – many – questions put forward in the previous chapters will likely be manifold. We nevertheless perceive some common issues that regulators are likely to encounter in each of the areas of law that were examined. We summarize them in section 2 of this conclusion, and elaborate some thoughts on the direction in which future research on the regulatory aspects of data-driven technologies may be headed. The second part of the book considered the increasing use of data science in legal scholarship and legal practice. Here also, challenging questions for future research have been identified by our authors. While the replacement of lawyers and judges by robots may still be a science-fiction dream (or nightmare), the use of data analysis in law is changing the way in which we approach legal (research) questions. We summarize the tentative findings in this field in section 3 of this conclusion. We round off the book with a final question: with data science and law, are we witnessing the emergence of a new discipline?

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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.