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The promise of artificial intelligence : reckoning and judgment / Brian Cantwell Smith.

By: Smith, Brian Cantwell [author.].
Contributor(s): IEEE Xplore (Online Service) [distributor.] | MIT Press [publisher.].
Material type: materialTypeLabelBookPublisher: Cambridge : MIT Press, 2019Distributor: [Piscataqay, New Jersey] : IEEE Xplore, [2019]Description: 1 PDF (xx, 157 pages) : illustrations.Content type: text Media type: electronic Carrier type: online resourceISBN: 9780262355209.Subject(s): Artificial intelligence -- Philosophy | Artificial intelligence -- Social aspectsGenre/Form: Electronic books.Additional physical formats: Print version:: Promise of artificial intelligenceDDC classification: 006.3 Online resources: Abstract with links to resource Also available in print.
Contents:
Intro; Contents; Preface; Introduction; 1 -- Background; 2 -- History; 3 -- Failure; 4 -- Transition; 5 -- Machine Learning; 6 -- Assessment; 7 -- Epistemological Challenges; 8 -- Objects; 9 -- World; 10 -- Reckoning and Judgment; 11 -- Discussion; 12 -- Application; 13 -- Conclusion; References; Index
Summary: An argument that--despite dramatic advances in the field--artificial intelligence is nowhere near developing systems that are genuinely intelligent.In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability reckoning, and argues that it does not lead to full human judgment--dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (good old-fashioned AI, or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself--what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.
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Includes bibliographical references and index.

Intro; Contents; Preface; Introduction; 1 -- Background; 2 -- History; 3 -- Failure; 4 -- Transition; 5 -- Machine Learning; 6 -- Assessment; 7 -- Epistemological Challenges; 8 -- Objects; 9 -- World; 10 -- Reckoning and Judgment; 11 -- Discussion; 12 -- Application; 13 -- Conclusion; References; Index

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An argument that--despite dramatic advances in the field--artificial intelligence is nowhere near developing systems that are genuinely intelligent.In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability reckoning, and argues that it does not lead to full human judgment--dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (good old-fashioned AI, or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself--what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.

Also available in print.

Mode of access: World Wide Web

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