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Alan Turing, in his 1950 paper Computing Machinery and Intelligence, proposed a test for intelligence which has since become known as the Turing test. [1] While there are a number of different versions, the original test, described by Turing as being based on the "imitation game", involved a "machine intelligence" (a computer running an AI program), a female participant, and an interrogator.
An artificial superintelligence (ASI) is a hypothetical type of AGI that is much more generally intelligent than humans, [23] while the notion of transformative AI relates to AI having a large impact on society, for example, similar to the agricultural or industrial revolution.
A real-world example of HITL simulation as an evaluation tool is its usage by the Federal Aviation Administration (FAA) to allow air traffic controllers to test new automation procedures by directing the activities of simulated air traffic while monitoring the effect of the newly implemented procedures.
It was billed as ‘Man vs Machine’: ... During the AI vs AI race on the morning before the AI vs human contest, the cars were reaching speeds of 200kph. And if it weren’t for the lack of ...
Turing thus once again demonstrates his interest in empathy and aesthetic sensitivity as components of an artificial intelligence; and in light of an increasing awareness of the threat from an AI run amok, [83] it has been suggested [84] that this focus perhaps represents a critical intuition on Turing's part, i.e., that emotional and aesthetic ...
Human Compatible: Artificial Intelligence and the Problem of Control is a 2019 non-fiction book by computer scientist Stuart J. Russell. It asserts that the risk to humanity from advanced artificial intelligence (AI) is a serious concern despite the uncertainty surrounding future progress in AI.
Book cover of the 1979 paperback edition. Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI, What Computers Can't Do (1972; 1979; 1992) and Mind over Machine, he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.
AI and AI ethics researchers Timnit Gebru, Emily M. Bender, Margaret Mitchell, and Angelina McMillan-Major have argued that discussion of existential risk distracts from the immediate, ongoing harms from AI taking place today, such as data theft, worker exploitation, bias, and concentration of power. [137]