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Books > Computing & IT
Drawing on the theoretical debates, practical applications, and
sectoral approaches in the field, this ground-breaking Handbook
unpacks the political and regulatory developments in AI and big
data governance. Covering the political implications of big data
and AI on international relations, as well as emerging initiatives
for legal regulation, it provides an accessible overview of ongoing
data science discourses in politics, law and governance. With novel
insights into existing and emerging debates, this cutting-edge
Handbook highlights the mutual effects of big data and AI on
society. Amongst other theoretical and sectoral issues, chapters
analyse the liability of AI use in autonomous weapons, the role of
big data in healthcare and education, the intersections between AI
and gender in human rights law, and the ethics of public
facial-recognition technology. Addressing the many open questions
and future regulatory problems, it uses data science to investigate
the dynamics between the technical aspects, societal dynamics and
governance implications of big data and AI. Transdisciplinary in
scope, this Handbook will be invaluable to students and researchers
across the fields of politics, law, governance and data science,
alongside policymakers concerned with the regulation and governance
of AI and big data in public and private institutions.
This pocket guide is perfect as a quick reference for PCI
professionals, or as a handy introduction for new staff. It
explains the fundamental concepts of the latest iteration of the
PCI DSS, v3.2.1, making it an ideal training resource. It will
teach you how to protect your customers' cardholder data with best
practice from the Standard.
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Heart
(Paperback)
Martin Farquhar Tupper
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R444
Discovery Miles 4 440
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Ships in 12 - 19 working days
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Gathering insightful and stimulating contributions from leading
global experts in Artificial Intelligence in Education (AIED), this
comprehensive Handbook traces the development of AIED from its
early foundations in the 1970s to the present day. The Handbook
evaluates the use of AI techniques such as modelling in closed and
open domains, machine learning, analytics, language understanding
and production to create systems aimed at helping learners,
teachers, and educational administrators. Chapters examine theories
of affect, metacognition and pedagogy applied in AIED systems;
foundational aspects of AIED architecture, design, authoring and
evaluation; and collaborative learning, the use of games and
psychomotor learning. It concludes with a critical discussion of
the wider context of Artificial Intelligence in Education,
examining its commercialisation, social and political role, and the
ethics of its systems, as well as reviewing the possible challenges
and opportunities for AIED in the next 20 years. Providing a broad
yet detailed account of the current field of Artificial
Intelligence in Education, researchers and advanced students of
education technology, innovation policy, and university management
will benefit from this thought-provoking Handbook. Chapters will
also be useful to support undergraduate courses in AI, computer
science, and education.
Is competition law able to deal with algorithmic collusion? This
evaluative book provides an insight into tackling this important
question for competition law, with contrasting critical
perspectives, including theoretical, empirical, and doctrinal –
the latter frequently from a comparative perspective. Bringing
together scholarly discussion on algorithmic collusion, the book
questions whether competition law is adeptly equipped to deal with
its various facets. With a comprehensive overview of the recent
literature on algorithmic collusion, chapters offer a critical
appraisal of the effectiveness of competition law to deal with
algorithmic collusion. Covering a unique collection of legal,
theoretical, and experimental case studies, it initiates debate
among legal scholars for a better understanding of the data upon
which algorithms decide prices. With a comparative identification
of both the potentialities and limitations of competition law in
relation to algorithmic collusion, this book will be of key value
to students and scholars of competition law, economics and finance.
It will also be an invaluable resource for legal practitioners and
policy makers in the field.
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