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Animorphs: The Re...
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by TK17
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“In a paper published in the philosophy journal Mind, Alan Turing described what's called the Turing Test. This asks whether someone could distinguish, 30% of the time, whether they were interacting (for up to five minutes) with a computer or a person. If not, he implied, there'd be no reason to deny that a computer could really think.

That was tongue in cheek. Although it featured in the opening pages, the Turing Test was an adjunct within a paper primarily intended as a manifesto for a future Al. Indeed, Turing described it to his friend Robin Gandy as light-hearted "propaganda," inviting giggles rather than serious critique.”
Margaret A. Boden, AI: Its Nature and Future

Arvind Narayanan
“While generative Al is modestly but meaningfully useful for a large number of people, it is more profoundly significant for some. An app called Be My Eyes connects blind people to volunteers who assist them in moments of need. The app records the user's surroundings through the phone camera, and the volunteer describes it to them. Be My Eyes has added a virtual assistant option that uses a version of ChatGPT that can describe images. Of course, ChatGPT isn't as helpful as a person, but it is always available, unlike human volunteers.”
Arvind Narayanan, AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference

Sayash Kapoor
“... for the longest time, we have used the form of a piece of content to determine whether it is legitimate and credible, but that proxy is no longer available to us.”
Sayash Kapoor, AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference

Arvind Narayanan
“The surprising thing is not that chatbots sometimes generate nonsense but that they answer correctly so often.”
Arvind Narayanan, AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference

Arvind Narayanan
“In one extreme case, U.S. health insurance company UnitedHealth forced employees to agree with Al decisions even when the decisions were incorrect, under the threat of being fired if they disagreed with the Al too many times. It was later found that over 90 percent of the decisions made by Al were incorrect.

Even without such organizational failure, overreliance on automated decisions (also known as "automation bias") is pervasive. It affects people across industries, from airplane pilots to doctors. In a simulation, when airline pilots received an incorrect engine failure warning from an automated system, 75 percent of them followed the advice and shut down the wrong engine. In contrast, only 25 percent of pilots using a paper checklist made the same mistake. If pilots can do this when their own lives are at stake, so can bureaucrats.

No matter the cause, the end result is the same: consequential decisions about people's lives are made using Al, and there is little or no recourse for flawed decisions.”
Arvind Narayanan, AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference

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