Justin Li

Generalizing the Turing Test


Are people familiar with the Turing test? Named after Alan Turing, the WWII British mathematician and code-breaker, it was proposed as a way of testing whether computers are "intelligent". In addition to inventing this test and helping break the Enigma, Turing is also famous for the conception of a Turing machine, a mathematical construct that is useful for understanding computation in the abstract. Unfortunately for Turing, he was also homosexual, and was prosecuted by the state for it after the war; this eventually led to his suicide. In 2009 - 55 years after Turing's death - the British government formally apologized for its treatment of Turing, and only earlier this year, in 2013, was he officially pardoned for his crimes.

Turing is also the subject of an upcoming biopic, The Imitation Game, starring ~~Sherlock~~ Benedict Cumberbatch. The title of the film is, in fact, based on the Turing test (or rather, is famous because of the test). In the Turing Test, a computer and a person both try to convince a human judge that they are human. The judge can only communicate with both parties through text, but they can ask questions. A computer or a program is said to have passed to the Turing test if, over multiple conversations, the judge cannot reliably and correctly label which is the person and which is the computer. In some sense, the computer needs to be imitating a person, whence the name of the game.

(It can, of course, also go the other way, to have a reversed Turing test: the goal could be to convince the judge that both participants are computers. This doesn't make sense as a test of intelligence, but the idea is the same. You can also try to convince the judge that they're a computer...)

Setting the question of whether the Turing test is a good test for whether a computer is intelligent, the test is nonetheless elegant in its design. There are several crucial elements of the design, that the computer is not "the most intelligent" or "the most human like" compared to other computers, and that the judge is not simply deciding whether one conversant is a human or a computer; these features mean that the computer must match the human in performance. Further more, because the judge can ask the computer any question they want, the computer must be able to talk about any subject the judge could think of. Thus, even though no one has a good definition of "intelligence", the Turing test at least allows us to apply a "know it when I see it" criterion.

For the most part, familiarity of the Turing test has remained within the academic fields of computer science, psychology, and philosophy. I was recently surprised, however, that it came up in an economics article. In this article, it is suggested that liberal economists can successfully present conservative economic arguments, while the same cannot be said of the opposite, for a conservative economist to present liberal economic arguments. The author therefore proposes a variation of a Turing test: put him (a conservative) in a room with five liberals, and see if people can tell who's the fake; then put Paul Krugman (a liberal) in a room with five conservatives, and again see if people can tell who's the fake.

What, then, is the more general version of the Turing test? The Turing test is really a special case of a discrimination test. The key, however, is that the Turing test is being used as a criterion: if the computer cannot be distinguished from a human, then we shall consider it as intelligent. This means that, crucially, we do not need to define the exact attribute that we are judging by, only that it behaves indistinguishably from the real thing. While we do not have a perfect definition (or even a good one) of intelligence, the beauty of the Turing test is that we don't need one to decide that a computer is intelligent. This may be a very behavioral definition of intelligence - it doesn't address the Chinese room problem, for example - but it's better than endlessly debating the definition of intelligence.

Of course, the Turing test, clever as it is, is not the silver bullet for all indefinable attributes. In fact, there are strong restrictions on when the Turing test will be useful. For one, the judge must be familiar with the attribute that is being judged; for example, I would not be a good judge of liberal/conservative economists, since I myself cannot tell the difference. More generally, the more discerning the judge, the more "powerful" the Turing test becomes. Additionally, the attribute being judged must be different from how the attribute is generated. In the original Turing test, what we cared about was whether the computer is intelligent, not how it came to be that way (that is, whether it does so through neurons or silicon). This means that care must be taken to remove elements that may give the distinction away, which is why the original test uses text as the medium of communication, as opposed to a face-to-face conversation, which would detract from the task of judging intelligence.

It is curious to me that, despite spending some time on this post, I cannot think of a single application of the Turing test. The closest I've come is for driverless cars, and using the Turing test to see whether they drive safer than humans do. Such a test would involve putting human and computer in simulated drives, and having the judges simply watch a recording of the performance without knowing which is which. While such a test would show that self-driving cars are as safe - if not safer than - humans, it is also unnecessary: the metrics for safety seems sufficiently well-defined that we don't need a Turing test, and that any old comparison would suffice. This is nothing more than an argumentation from lack of imagination, it may seem that we are simply not trained to think of tests in this way. More often, when we think of an attribute we want to measure, we define the attribute such that it is measurable, or else we give up trying to get any accurate measurements. Maybe the Turing test is a good way to attack some of these measurements we've given up on.