The myth of artificial intelligence : why computers can't think the way we do
2021
006.3 LAR
Available at Arbeids- og velferdsbiblioteket
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Details
Title
The myth of artificial intelligence : why computers can't think the way we do
Author
ISBN
9780674278660 heftet
Date
2021
Publisher
Belknap Press of Harvard University Press, Cambridge, Massachusetts
Language
English
Pages
viii, 312
Dewey
006.3
Subjects
Keywords
Abstract
"Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren’t really on the path to developing intelligent machines. In fact, we don’t even know where that path might be.A tech entrepreneur and pioneering research scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence, and what it would take to get there. Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. This is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don’t correlate data sets: we make conjectures informed by context and experience. Human intelligence is a web of best guesses, given what we know about the world. We haven’t a clue how to program this kind of intuitive reasoning, known as abduction. Yet it is the heart of common sense. That’s why Alexa can’t understand what you are asking, and why AI can only take us so far.Larson argues that AI hype is both 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 want to make real progress, we will need to start by more fully appreciating the only true intelligence we know—our own." Forleggeromtale
Bibliography, etc. Note
Har referanser og indeks
Formatted Contents Note
Part One. The simplified world: The intelligence errors
Turing at Bletchley
The superintelligence error
The singularity, then and now
Natural language understanding
AI as technological kitsch
Simplifications and mysteries
Part Two. The problem of inference: Don't calculate, analyze
The puzzle of Peirce (and Peirce's Puzzle)
Problems with deduction and induction
Machine learning and big data
Abductive inference
Inference and language I
Inference and language II
Part Three. The future of the myth: Myths and heroes
AI mythology invades neuroscience
Neocortical theories of human intelligence
The end of science?
Turing at Bletchley
The superintelligence error
The singularity, then and now
Natural language understanding
AI as technological kitsch
Simplifications and mysteries
Part Two. The problem of inference: Don't calculate, analyze
The puzzle of Peirce (and Peirce's Puzzle)
Problems with deduction and induction
Machine learning and big data
Abductive inference
Inference and language I
Inference and language II
Part Three. The future of the myth: Myths and heroes
AI mythology invades neuroscience
Neocortical theories of human intelligence
The end of science?