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On the path to AI

Law’s prophecies and the conceptual foundations of the machine learning age

Authors: Grant, Thomas D., Wischik, Damon J.

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  • Discusses the impacts and uses of machine learning
  • Analogizes Oliver Wendell Holmes Jr's theory of prediction in law with AI
  • Explores questions of how machine learning can be used and regulated wisely
  • This is an Open Access title
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  • ISBN 978-3-030-43582-0
  • This book is an open access book, you can download it for free on link.springer.com
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  • ISBN 978-3-030-43581-3
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About this book

This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets.

On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data. 


About the authors

Thomas D. Grant is a Fellow of the Lauterpacht Centre for International Law, University of Cambridge, UK.

Damon J. Wischik is a Lecturer in the Department of Computer Science and Technology, University of Cambridge, UK.

Reviews

“Finding an analogy in the legal philosophy of Oliver Wendell Holmes Jr., the authors provide a penetrating and fine-grained examination of artificial intelligence, a rich and forward-looking approach that should restrain exaggerated claims and guide a realistic assessment of AI's prospects.” 
(Frederic R. Kellogg, author of Oliver Wendell Holmes Jr. and Legal Logic)


“There’s been a lot of discussion about how machine learning introduces or consolidates bias in AI due to its reliance on historic data. Who knew that law has been working on the social problems of the impact of precedent for over a century?”
(Joanna Bryson, Professor of Ethics and Technology, Hertie School, Germany)

Table of contents (10 chapters)

Table of contents (10 chapters)
  • Two Revolutions

    Pages 1-17

    Grant, Thomas D. (et al.)

  • Getting Past Logic

    Pages 19-31

    Grant, Thomas D. (et al.)

  • Experience and Data as Input

    Pages 33-40

    Grant, Thomas D. (et al.)

  • Finding Patterns as the Path from Input to Output

    Pages 41-48

    Grant, Thomas D. (et al.)

  • Output as Prophecy

    Pages 49-66

    Grant, Thomas D. (et al.)

Buy this book

eBook  
  • ISBN 978-3-030-43582-0
  • This book is an open access book, you can download it for free on link.springer.com
Hardcover $59.99
price for USA
  • ISBN 978-3-030-43581-3
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
On the path to AI
Book Subtitle
Law’s prophecies and the conceptual foundations of the machine learning age
Authors
Copyright
2020
Publisher
Palgrave Macmillan
Copyright Holder
The Editor(s) (if applicable) and The Author(s)
eBook ISBN
978-3-030-43582-0
DOI
10.1007/978-3-030-43582-0
Hardcover ISBN
978-3-030-43581-3
Edition Number
1
Number of Pages
XXII, 147
Number of Illustrations
4 b/w illustrations
Topics

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