How Alan Turing and His Test Became AI Legend

Alan Turing was the eccentric British mathematician who came up with the idea of modern computing and whose code breaking played a major role in the Allied victory over the Nazis in World War II. He was prosecuted in 1952 for having a homosexual affair (homosexual acts being illegal in Britain until 1967) and accepted a form of chemical castration as a condition of probation in order to avoid jail time. His security clearance was revoked, ending his work for the British government. He was found dead of cyanide poisoning in 1954 and was posthumously pardoned of his conviction in 2013 by Queen Elizabeth II.

Turing was writing about computers well before any such thing existed. Back in 1936, he introduced the concept of the "universal computing machine" in a dense mathematical paper called "On Computable Numbers, With an Application to the Entscheidungsproblem."

"According to my definition, a number is computable if its decimal can be written down by a machine," wrote Turing, a decade before the first electronic computer was built. "It is possible to invent a single machine which can be used to compute any computable sequence."

Turing's definition of "computability" — something that a computer can do — is what's known today as an algorithm. Turing was the first to lay out the design framework of a machine that could be programmed to run a series of discrete algorithms in order to achieve a desired task. Other mathematicians and engineers had toyed with calculating machines — most famously Charles Babbage's 19th-century analytical engine — but Turing envisioned a device that wasn't limited to solving one kind of problem.

"Anything you can describe as an algorithm can be done by one machine," says Andrew Hodges, a mathematics professor at Oxford University and author of "Alan Turing: The Enigma," the inspiration for the Oscar-winning 2014 film "The Imitation Game."

"The universal machine is essentially what we mean by a computer now, something on which you can store the instructions and it carries them out," says Hodges. "No one else had formalized that idea."

From the start, Turing's universal machine was conceived as a very simplified form of artificial intelligence, even though that term wouldn't be coined until 1956. Hodges says that the design of the universal machine was meant to imitate the inner workings of the human mind, a subject that fascinated Turing almost as much as mathematics.

In fact, when describing how his universal machine would work, Turing used the term "state of mind" to label the different "read" and "write" functions of the machine. In Turing's conceptual machine, a length of tape is run through a read/write scanner. The tape is inscribed with bits of information represented by symbols. The scanner head can either read the symbols or write new ones according to its "state of mind."

"The operation actually performed is determined... by the state of mind of the computer and the observed symbols," wrote Turing in his 1936 paper. "In particular, they determine the state of mind of the computer after the operation is carried out."

A decade later, when Turing was leading the stalled British effort to build one of the first electronic computers in 1946, he also studied neurology and human physiology on the side. The result was an internal paper published for the National Physical Laboratory that modeled how a computer could be programmed to "learn" on its own. Hodges sees it as one of the earliest proposals of what are now called "neural networks," a type of deep machine learning that's at the bleeding edge of artificial intelligence.

Turing wasn't the only person intrigued by the similarities between human and machine intelligence. A surge of new technologies developed during World War II, including early computers, space satellites and nuclear power, had captured the intellectual and public imagination.

"As soon as computers are mentioned at all, people are talking about electronic brains and the possibility of the computer rivaling the brain," says Hodges.

The 1948 book "Cybernetics" coined the prefix "cyber" and wondered whether it would be possible to "construct a chess-playing machine, and whether this sort of ability represents an essential difference between the potentialities of the machine and the mind." The author, Norbert Wiener, concluded that such a machine "might very well be as good a player as the vast majority of the human race."

It was during this era of excitement and nervous speculation about super-intelligent machines that Turing wrote "Computing Machinery and Intelligence," what Hodges calls one of the most cited papers in philosophical literature.

"I propose to consider the question, 'Can machines think?'" begins Turing. Since the definitions of "machine" and "think" are ambiguous, Turing narrows the scope of the question. For his purposes, the machine must be a "digital computer" and the test of whether or not it can "think" would be answered by the imitation game. It went something like this: There would be three terminals physically separated. Two would have humans as operators (one to be a questioner); the other would have a computer. One human would ask questions to the other human and to the computer via text and, from the answers received from both, determine who was "real" and who was computer. A computer was determined to have artificial intelligence (i.e. passed the test) if the questioner could not tell the difference between "man" and "machine."

The game, now known as the Turing Test, is only mentioned briefly in the paper and Hodges says that Turing didn't take the details of the test too seriously, publishing different versions in other papers. But Turing did like the playful simplicity of it.

"In a way, he was making a drama out of it," says Hodges. It presented this idea [of the possibility of advanced artificial intelligence] in a way that engages people and that ordinary people would make the decision, like a jury in a trial."

When the Turing Test was first published in 1950, Turing himself was confident that "intelligent machinery" (as he called it) would be able to win the imitation game within 50 to 100 years.

In 2025, researchers at UC San Diego published a study claiming that OpenAI’s GPT-4.5 had effectively passed the Turing Test — a major milestone in AI development.

In the study, participants had conversations with both a human and an AI, then had to guess which was which. Surprisingly, GPT-4.5 was mistaken for a human 73 percent of the time, outperforming actual humans, who were correctly identified only 67 percent of the time.

This marked the first time an AI convincingly fooled people more often than real people did in the same setup.

The researchers designed the test to be closer to what Alan Turing originally envisioned, using natural conversations without tipping off participants that an AI might be involved. GPT-4.5 was also given a specific personality or “persona prompt,” which made its responses sound more human-like.

However, not everyone agrees this means the Turing Test has truly been “beaten.” Some experts argue that this kind of test only proves that an AI can mimic human speech well — not that it actually understands anything.

Others believe the Turing Test is no longer a useful benchmark, since it rewards surface-level imitation rather than real reasoning, emotion or intelligence.

Editor's Note: The Loebner Prize has been defunct since 2020.

We updated this article in conjunction with AI technology, then made sure it was fact-checked and edited by a HowStuffWorks editor.