<body> Excerpts: Long Bets

Saturday, July 31, 2004

Long Bets

Stumbled across an interesting website, Long Bets, where people place bets on long term societal and technological possibilities. . For $50 anyone can put lay out a prediction and then others can place a bet against them. One of those bets was placed between Mitchell Kapor and Ray Kurzweil who have each plonked down $10,000 on opposite sides of whether a machine will pass the Turing test by 2029. The Predictors and Bettors must provide an argument explaining why the subject of their prediction is important and why they think they will be proved right.

The following excerpt gives a brief understanding of the turing test.

From The Imitation Game To The Turing Test


The Turing Test was introduced by Alan M. Turing (1912-1954) as "the imitation game" in his 1950 article (now available online) Computing Machinery and Intelligence (Mind, Vol. 59, No. 236, pp. 433-460) which he so boldly began by the following sentence:


I propose to consider the question "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think."


Turing Test is meant to determine if a computer program has intelligence. Quoting Turing, the original imitation game can be described as follows:


The new form of the problem can be described in terms of a game which we call the "imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B.


When talking about the Turing Test today what is generally understood is the following: The interrogator is connected to one person and one machine via a terminal, therefore can't see his/her counterparts. His/Her task is to find out which of the two candidates is the machine, and which is the human only by asking them questions. If the machine can "fool" the interrogator, it is intelligent.

This test has been subject to different kinds of criticism and has been at the heart of many discussions in AI, philosophy and cognitive science for the past 50 years.




The toughest test of Artificial Intelligence is going to be its understanding of Irony. How is a perfectly logical machine to understand it? It is impossible to spot irony without understanding irony, and yet how could it (the A.I.) understand irony without spotting it? If you don’t recognize irony, you can’t see it, and you can’t see it if you don’t recognize it. Fowler in his classic volume Modern English Usage says, “Irony is a form of utterance that postulates a double audience, consisting of one party that, hearing, shall hear and shall not understand, and another party that, when more is meant than meets the ear, is aware both of that more and of the outsider’ incomprehension.”

The more one reads the sentence, the more one identifies with the outsider’s incomprehension. Is it possible that the very definition is ironic?!



(To read the bet placed by Mitchell Kapor and Ray Kurzweil click here.)



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