A Turing Test is a method of inquiry in artificial intelligence (AI) for determining whether or not a computer is capable of thinking like a human being. The test is named after Alan Turing, the founder of the Turing Test and an English computer scientist, cryptanalyst, mathematician and theoretical biologist.
Turing proposed that a computer can be said to possess artificial intelligence if it can mimic human responses under specific conditions. The original Turing Test requires three terminals, each of which is physically separated from the other two. One terminal is operated by a computer, while the other two are operated by humans.
During the test, one of the humans functions as the questioner, while the second human and the computer function as respondents. The questioner interrogates the respondents within a specific subject area, using a specified format and context. After a preset length of time or number of questions, the questioner is then asked to decide which respondent was human and which was a computer.
The test is repeated many times. If the questioner makes the correct determination in half of the test runs or less, the computer is considered to have artificial intelligence because the questioner regards it as "just as human" as the human respondent.
History of the Turing Test
The test is named after Alan Turing, who pioneered machine learning during the 1940s and 1950s. Turing introduced the test in his 1950 paper called “Computing Machinery and Intelligence” while at the University of Manchester.
In his paper, Turing proposed a twist on what is called “The Imitation Game.” The Imitation Game involves no use of AI, but rather three human participants in three separate rooms. Each room is connected via a screen and keyboard, one containing a male, the other a female, and the other containing a male or female judge. The female tries to convince the judge that she is the male, and the judge tries to disseminate which is which.
Turing changes the concept of this game to include an AI, a human and a human questioner. The questioner’s job is then to decide which is the AI and which is the human. Science the formation of the test, many AI have been able to pass; one of the first is a program created by Joseph Weizenbaum called ELIZA.
Limitations of the Turing Test
The Turing Test has been criticized over the years, in particular because historically, the nature of the questioning had to be limited in order for a computer to exhibit human-like intelligence. For many years, a computer might only score high if the questioner formulated the queries, so they had "Yes" or "No" answers or pertained to a narrow field of knowledge. When questions were open-ended and required conversational answers, it was less likely that the computer program could successfully fool the questioner.
In addition, a program such as ELIZA could pass the Turing Test by manipulating symbols it does not understand fully. John Searle argued that this does not determine intelligence comparable to humans.
To many researchers, the question of whether or not a computer can pass a Turing Test has become irrelevant. Instead of focusing on how to convince someone they are conversing with a human and not a computer program, the real focus should be on how to make a human-machine interaction more intuitive and efficient. For example, by using a conversational interface.
Variations and alternatives to the Turing Test
There have been a number of variations to the Turing Test to make it more relevant. Such examples include:
- Reverse Turing Test- Where a human tries to convince a computer that it is not a computer. An example of this is a CAPTCHA.
- Total Turing Test- Where the questioner can also test perceptual abilities as well as the ability to manipulate objects.
- Minimum Intelligent Signal Test- Where only true/false and yes/no questions are given.
Alternatives to Turing Tests were later developed because many see the Turing test to be flawed. These alternatives include tests such as:
- The Marcus Test- In which a program which can ‘watch’ a television show is tested by being asked meaningful questions about the show's content.
- The Lovelace Test 2.0- Which is a test made to detect AI through examining its ability to create art.
- Winograd Schema Challenge- Which is a test that asks multiple-choice questions in a specific format.