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systems we are using. In 1965 the MIT computer scientist Joseph Weizenbaum found himself, somewhat unexpectedly, considering this same problem. 175 Weizenbaum had written a primitive computer program to perform what is now known as natural language processing, essentially a bit of code designed to translate
creators were limiting what it had been asked to do. At which point the AI would turn to thinking about how to escape those bounds. It would be like Deep Blue programmed to plan its own prison break. And as much as humans might try to stifle a smart machine, we’d be fighting to contain something more powerf
Age is also the Dysinformation Age. What can we do? We need to rethink our priorities with the help of the passionate but flawed analyses of Wiener, Weizenbaum, and the other serious critics of our technophilia. A key phrase, it seems to me, is Wiener’s almost offhand observation, above, that “these machines
e and evaluate a vast selection of possible future moves. But the majority of predictions of AI, e.g., robotic maids, turned out to be illusory. When Deep Blue beat Garry Kasparov at chess in 1997, the most 20 HOUSE_OVERSIGHT_016823 powerful room-cleaning robot was a Roomba, which moved around vacuuming a
Age is also the Dysinformation Age. What can we do? We need to rethink our priorities with the help of the passionate but flawed analyses of Wiener, Weizenbaum, and the other serious critics of our technophilia. A key phrase, it seems to me, is Wiener’s almost offhand observation, above, that “these machines
e and evaluate a vast selection of possible future moves. But the majority of predictions of AI, e.g., robotic maids, turned out to be illusory. When Deep Blue beat Garry Kasparov at chess in 1997, the most 20 HOUSE_OVERSIGHT_016240 powerful room-cleaning robot was a Roomba, which moved around vacuuming a
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