Summary Of Erik J Larson S The Myth Of Artificial Intelligence
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Summary of Erik J. Larson's The Myth of Artificial Intelligence
Author: Everest Media,
language: en
Publisher: Everest Media LLC
Release Date: 2022-06-09T22:59:00Z
Please note: This is a companion version & not the original book. Sample Book Insights: #1 The story of artificial intelligence begins with the ideas of computer pioneer Alan Turing. In 1950, he published a paper titled Computing Machinery and Intelligence, which argued that any computer that could hold a conversation with a human would be doing something that requires thinking. #2 Turing had made his reputation as a mathematician long before he began writing about artificial intelligence. In 1936, he published a paper on the precise meaning of computer, which at the time referred to a person working through a sequence of steps to get a definite result. #3 The idea that the mind’s intuition, its ability to grasp truth and meaning, is reducible to a machine was raised by Gödel in 1931. He proved that there must exist some statements in any formal system that are True, with capital-T standing, yet not provable in the system itself using any of its rules. #4 The formalist movement in mathematics was a sign of a broader turn by intellectuals toward scientific materialism. They believed that all of mathematics could be converted into rule-based operations, and that the world was turning to the idea of precision machines.
The Myth of Artificial Intelligence
“Exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it.” —John Horgan “If you want to know about AI, read this book...It shows how a supposedly futuristic reverence for Artificial Intelligence retards progress when it denigrates our most irreplaceable resource for any future progress: our own human intelligence.” —Peter Thiel Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. A computer scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to reveal why 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. And we haven’t a clue how to program that kind of intuitive reasoning, which lies at the heart of common sense. Futurists insist AI will soon eclipse the capacities of the most gifted mind, but Larson shows how far we are from superintelligence—and what it would take to get there. “Larson worries that we’re making two mistakes at once, defining human intelligence down while overestimating what AI is likely to achieve...Another concern is learned passivity: our tendency to assume that AI will solve problems and our failure, as a result, to cultivate human ingenuity.” —David A. Shaywitz, Wall Street Journal “A convincing case that artificial general intelligence—machine-based intelligence that matches our own—is beyond the capacity of algorithmic machine learning because there is a mismatch between how humans and machines know what they know.” —Sue Halpern, New York Review of Books
The Descent of Artificial Intelligence
Author: Kevin Padraic Donnelly
language: en
Publisher: University of Pittsburgh Press
Release Date: 2024-07-15
The idea that a new technology could challenge human intelligence is as old as the warning from Socrates and Plato that written language eroded memory. With the emergence of generative artificial intelligence programs, we find ourselves once again debating how a new technology might influence human thought and behavior. Researchers, software developers, and “visionary” tech writers even imagine an AI that will equal or surpass human intelligence, adding to a sense of technological determinism where humanity is inexorably shaped by powerful new machines. But among the hundreds of essays, books, and movies that approach the question of AI, few have asked how exactly scientists and philosophers have codified human thought and behavior. Rather than focusing on technical contributions in machine building, The Descent of Artificial Intelligence explores a more diverse cast of thinkers who helped to imagine the very kind of human being that might be challenged by a machine. Kevin Padraic Donnelly argues that what we often think of as the “goal” of AI has in fact been shaped by forgotten and discredited theories about people and human nature as much as it has been by scientific discoveries, mathematical advances, and novel technologies. By looking at the development of artificial intelligence through the lens of social thought, Donnelly deflates the image of artificial intelligence as a technological monolith and reminds readers that we can control the narratives about ourselves.