The myth of artificial intelligence : why computers can't think the way we do / Erik J. Larson.

Format:

Book

Author/Creator:

Larson, Erik J. (Erik John), author.

Language:

English

Subjects (All):

Artificial intelligence.

Neurosciences.

Natural language processing (Computer science).

Logic.

Intellect.

Inference.

Physical Description:

1 online resource (288 p.)

Place of Publication:

Cambridge, Massachusetts : Harvard University Press, [2021]

Language Note:

In English.

Summary:

“Artificial intelligence has always inspired outlandish visions—that AI is going to destroy us, save us, or at the very least radically transform us. Erik Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. This is a timely, important, and even essential book.” —John Horgan, author of The End of Science Many futurists insist that AI will soon achieve human levels of intelligence. From there, it will quickly eclipse the most gifted human mind. The Myth of Artificial Intelligence argues that such claims are just that: myths. We are not on the path to developing truly intelligent machines. We don’t even know where that path might be. Erik Larson charts a journey through the landscape of AI, from Alan Turing’s early work to today’s dominant models of machine learning. Since the beginning, AI researchers and enthusiasts have equated the reasoning approaches of AI with those of human intelligence. But this is a profound mistake. Even cutting-edge AI looks nothing like human intelligence. Modern AI is based on inductive reasoning: computers make statistical correlations to determine which answer is likely to be right, allowing software to, say, detect a particular face in an image. But human reasoning is entirely different. Humans do not correlate data sets; we make conjectures sensitive to context—the best guess, given our observations and what we already know about the world. We haven’t a clue how to program this kind of reasoning, known as abduction. Yet it is the heart of common sense. Larson argues that all this AI hype is bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we are to make real progress, we must abandon futuristic talk and learn to better appreciate the only true intelligence we know—our own.

Contents:

Frontmatter

CONTENTS

Introduction

Part I: THE SIMPLIFIED WORLD

1 The Intelligence Error

2 Turing at Bletchley

3 The Superintelligence Error

4 The Singularity, Then and Now

5 Natural Language Understanding

6 AI as Technological Kitsch

7 Simplifications and Mysteries

Part II: THE PROBLEM OF INFERENCE

8 Don’t Calculate, Analyze

9 The Puzzle of Peirce (and Peirce’s Puzzle)

10 Problems with Deduction and Induction

11 Machine Learning and Big Data

12 Abductive Inference

13 Inference and Language I

14 Inference and Language II

Part III: THE FUTURE OF THE MYTH

15 Myths and Heroes

16 AI Mythology Invades Neuroscience

17 Neocortical Theories of Human Intelligence

18 The End of Science?

Notes

Acknowledgments

Index

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9780674259928

0674259920

9780674259935

0674259939

OCLC:

1240729240