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 15: Methods of data research for law

Bart Custers

Abstract

Methods of data research are becoming increasingly important in the legal domain. After explaining the concept of legal big data, to show that law is an area in which a lot of big data is available, this chapter discusses and illustrates several existing and potential applications of data research methods for lawyers and legal researchers. Particular opportunities exist with regard to: (1) predictions; (2) searching, structuring and selecting; and (3) decision-making and empirical legal research. These methods constitute an important contribution to legal practice and legal scholarship as they may provide novel and unexpected insights and considerably increase efficiency (less resources, more results) and effectiveness (more accurate and reliable results) of legal research, both in legal practice and legal scholarship. This may, among other things, result in improved legal services, new business models, new knowledge and a more solid basis for evidence-based policies and legislation. However, there are also several limits to, and drawbacks of, the use of these data research methods for law. From a methodological perspective, these include the lack of human intuition, an abundance of results that are not always relevant, limited insights in underlying causality, issues with repurposing, self-confirmation, self-fulfilling prophecies and reliability issues. It is concluded that, given the opportunities these developments provide for new business models for legal services and for legal research (both in legal practice and in legal scholarship), it is likely that these methods will be used on a larger scale in the near future and that new and additional methods will be developed. This will change to some extent the way legal work looks like and the job market for lawyers.

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