On the path to AI : Law's prophecies and the conceptual foundations of the machine learning age /

On the path to AI : Law's prophecies and the conceptual foundations of the machine learning age /

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Bibliographic Details
Author / Creator:	Grant, Thomas D.
Imprint:	Cham : Palgrave Macmillan, 2020.
Description:	1 online resource (163 pages)
Language:	English
Subject:	Artificial intelligence. Machine learning. Artificial Intelligence Artificial intelligence. Machine learning.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12355058

Hidden Bibliographic Details
Other authors / contributors:	Wischik, Damon J.
ISBN:	9783030435820 3030435822 9783030435813
Notes:	Open access. Print version record.
Summary:	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.
Other form:	Print version: Grant, Thomas D. On the Path to AI : Law's Prophecies and the Conceptual Foundations of the Machine Learning Age. Cham : Springer International Publishing AG, ©2020 9783030435813

Table of Contents:

Two revolutions
Getting past logic
Experience and data as input
Finding patterns as the path from input to output
Output as prophecy
Explanations of machine learning
Juries and other reliable predictors
Poisonous datasets, poisonous trees
From Holmes to AlphaGo
Conclusion.