Playing the Imitation Game
The Imitation Game is a 2015 movie based on the biography of Alan Turing, a Cambridge and Princeton graduate. In 1939, Turing was recruited by the newly created British intelligence agency MI6 to decipher Nazi codes, including Enigma. The Polish had broken the Enigma code before the war, but the Nazis increased the complexity of their Enigma machines, so there were approximately 10114 permutations to the code. At the time, the British code-breaking operation involved 12,000 people who covered three shifts that operated 24/7. Turing and his team built an electromechanical machine called the Bombe that searched through the permutations of the Enigma code to find the one that was used for each message. Using the Bombe, the British were able to read all of the German navy's encrypted messages.
While working toward his Ph.D. at Princeton, Turing published a paper entitled "On Computable Numbers with an application to the Entscheidungsproblem," in which he envisioned a single, universal machine that could solve any problem by following instructions that could be encoded on a paper tape. For example, given one set of instructions, the machine might be able to calculate square roots. Given another set of instructions, it could solve crossword puzzles. Although others have been credited with inventing the first computer, Turing's ideas gave birth to the field of computer science, specifically computer programming.
Testing a Machine to Determine Whether It Is Intelligent
In a 1951 paper, Turing proposed a test for intelligence called the “imitation game,” which is based on a Victorian parlor game. The game involves three players—Player A is a man, Player B is a woman, and Player C is a man or woman who acts as the interrogator. Player C cannot see Players A or B and can communicate with them only through written messages. Player C writes down questions that are passed to Player A or B and receives written answers back from them. Based on the answers, Player C must determine which player (A or B) is the man and which is the woman. Player A's job is to trick Player C into making the wrong choice, while player B attempts to assist Player C in making the right choice.
Turing imagined an updated version of the imitation game in which Player A is replaced by a machine. If the machine were just as effective as a human player in fooling Player C, Turing deemed this proof of (artificial) intelligence. The imitation game later came to be referred to as the "Turing test."
This test sparked a lot of curiosity in the possibility of an "intelligent machine"—one that could accomplish a specific task in the presence of uncertainty and variations in its environment. For a machine to be considered intelligent, it must be able to monitor its environment and make adjustments based on its observations. In the case of the Turing test, the machine would need to be able to "understand" its role in the game (to fool Player C) and its gender (male) and be able to choose responses to unanticipated questions in a way that would confuse Player C.
Even after nearly 70 years, this test is still intriguing and a considerable challenge for computer developers. You can witness a version of this today by interacting with smartphones and artificially intelligent virtual assistants, like Siri and Alexa, whose answers to questions and responses to directives are often comical at best.
Turing Test Limitations
Most experts agree that the Turing test is not necessarily the best way to gauge intelligence. For one it depends a lot on the interrogator—some people are easily fooled. It also assumes that artificial intelligence is like human intelligence and that computers have mastered verbal communication, when that is far from the truth; computers often misinterpret words and phrases. If a computer cannot carry on an intelligent conversation, then how can we expect it to perform higher level tasks that require the ability to accurately interpret verbal and non-verbal communication, such as accurately diagnosing an illness?
A Test That Continues to Drive Innovation
The Turing test still inspires a lot of innovation. Companies continue to try to create intelligent chatbots, for example, and there are still natural language processing (NLP) competitions that attempt to pass the test. Indeed, it seems as though modern machines are only a few years away from passing the Turing test. Many modern NLP applications are able to accurately understand many of your requests. Now they just have to improve their ability to respond.
Yet even if a machine is able to pass the Turing test, it still seems unlikely that that same machine would qualify as intelligent. Even if your smartphone is able to trick you into thinking you’re talking to a human, that doesn’t mean that it will offer meaningful conversation or care about what you think or feel.