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Hans-W. Micklitz, Anne-Lise Sibony and Fabrizio Esposito

For decades, consumer law has been the stepchild of the legal discipline, neither public nor private law, not classic but postmodern, not ‘legal enough’, ‘too political’, in short, a discipline at the margins, suffering from the haut goût and striving to change society through law for the ‘better’. Just like Atreyu, Frodo Baggins, Luke Skywalker, the Ghostbusters, Naruto Uzumaki, Dreamworks’ dragon trainer, and many others, consumer law is the underdog carrying the burden of saving the day. Times are changing. We are perhaps reaching the point at which the world comes to understand the real value of consumer law in a society that is dominated by and dependent on private consumption. Publishing houses and ever more numerous researchers from public and private law perspectives, working on national, European and international law are getting into what is no longer a new legal field. Now the time is ripe for a whole Handbook on Consumer Law Research which brings methodology to the fore. This first chapter pursues three aims: first, to embed consumer law research into the overall development of legal research since the rise of consumer law in the 1960s; secondly, to explain our choice to focus on the behavioural turn in consumer law research and present the range of contributions in this volume that engage with the upcoming strand of research; and thirdly, to explore how the recent attention to behavioural insights can be combined with a pre-existing body of doctrinal research and social legal research in consumer law, and outline avenues for further research.

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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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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.