A01=Alexander E. Silverman
Ai Approach
Ai Researcher
Ai System
Art Network
artificial intelligence
artificial intelligence legal reasoning
Author_Alexander E. Silverman
Backpropagation Networks
Biological Neural Networks
Category=JHB
Classical Ai
Classical Expert Systems
cognitive modeling law
Collision Avoidance Behavior
computational law
Connectionist Ai
Connectionist Approaches
Connectionist Systems
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Essential Vagueness
fuzzy logic applications
Fuzzy Systems
HAL
human legal reasoning
indeterminacy concept
indeterminacy theory
jurisprudence
Kuhn's Theory
Kuhnian paradigm shifts
Kuhn’s Theory
legal expert system
legal expert systems
Legal Process School
Quasi-static Approximation
RELATIVES Slot
Rule Based Expert Systems
Subsumption Architecture
Vice Versa
World War Ii Veteran
Product details
- ISBN 9780367008215
- Weight: 450g
- Dimensions: 152 x 222mm
- Publication Date: 07 Jun 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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In this provocative essay, Alexander E. Silverman explores the relationship between artificial intelligence (AI) and the law from the point of view of the legal theorist. Beginning with an overview of AI technology, he provides the necessary background review of classical, connectionist, fuzzy, and interactionist approaches to AI, as well as of legal expert systems. He then applies the lessons from this research to a number of jurisprudential topics, including the concepts of indeterminacy, open texture, and essential vagueness; Kuhnian paradigm shifts and the nature of theory; and the production of new metaphors of law. He concludes with a discussion of the lessons of AI research for our understanding of human legal reasoning. Mind, Machine, and Metaphor is a rich, original, and wide-ranging view of legal theory in the context of AI research. It is essential reading for legal theorists and for legal scholars and students of AI with an interest in each other’s fields.
