The Elgar Encyclopedia of Law and Data Science represents a
comprehensive mapping of the field. Comprising over 60 entries, it
features contributions from eminent global scholars, drawing on
expertise from multiple disciplines, including law and data
science, economics, computer engineering, physics, biomedical
engineering and history, philosophy, neuro-engineering, political
science, and geo-informatics. This Encyclopedia brings together
jurists, computer scientists, and data analysts to uncover the
challenges, opportunities, and fault lines that arise as these
groups are increasingly thrown together by expanding attempts to
regulate and adapt to a data-driven world. It explains the concepts
and tools at the crossroads of the many disciplines involved in
data science and law, bridging scientific and applied domains.
Entries span algorithmic fairness, consent, data protection,
ethics, healthcare, machine learning, patents, surveillance,
transparency and vulnerability. Comprehensive yet accessible, this
Encyclopedia will be an indispensable resource for scholars of law,
data science, artificial intelligence and law and technology. It
also contains practical implications for a manifold of users: from
domain experts to policy makers, from businesses to practitioners.
Key Features: The first Encyclopedic coverage of the field of Law
and Data Science Over 60 entries Entries organized alphabetically
for ease of reference Full analytical index Interrelated
multidisciplinary perspectives Unique accessibility for
non-experts.
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