Original article was published on Deep Learning on Medium
The chasm between the ordinary and extraordinary uses of computers started almost 70 years ago, when Alan Turing proposed a gimmick that accidentally helped found the field of artificial intelligence. Turing guessed that machines would become most compelling when they became convincing companions, which is essentially what today’s smartphones (and smart toasters) do. But computer scientists missed the point by contorting Turing’s thought experiment into a challenge to simulate or replace the human mind.
In his 1950 paper, Turing described a party game, which he called the imitation game. Two people, a man and a woman, would go behind closed doors, and another person outside would ask questions in an attempt to guess which one was which. Turing then imagined a version in which one of the players behind the door is a human and the other a machine, like a computer. The computer passes the test if the human interlocutor can’t tell which is which. As it institutionalized, the Turing test, as it is known, has come to focus on computer characters — the precursors of the chatbots now popular on Twitter and Facebook Messenger. There’s even an annual competition for them. Some still cite the test as a legitimate way to validate machine intelligence.
But Turing never claimed that machines could think, let alone that they might equal the human mind. Rather, he surmised that machines might be able to exhibit convincing behavior. For Turing, that involves a machine’s ability to pass as something else. As computer science progressed, “passing” the Turing test came to imply success as if on a licensure exam, rather than accurately portraying a role.
That misinterpretation might have marked the end of Turing’s vision of computers as convincing machines. But he also baked persuasion into the design of computer hardware itself. In 1936, Turing proposed a conceptual machine that manipulates symbols on a strip of tape according to a finite series of rules. The machine positions a head that can read and write symbols on discrete cells of the tape. Each symbol corresponds with an instruction, like writing or erasing, which the machine executes before moving to another cell on the tape.
The design, known as the universal Turing machine, became an influential model for computer processing. After a series of revisions by John von Neumann and others, it evolved into the stored-programming technique — a computer that keeps its program instructions as well as its data in memory.
In the history of computing, the Turing machine is usually considered an innovation independent from the Turing test. But they’re connected. General computation entails a machine’s ability to simulate any Turing machine (computer scientists call this feat Turing completeness). A Turing machine, and therefore a computer, is a machine that pretends to be another machine.
Think about the computing systems you use every day. All of them represent attempts to simulate something else. Like how Turing’s original thinking machine strived to pass as a man or woman, a computer tries to pass, in a way, as another thing. As a calculator, for example, or a ledger, or a typewriter, or a telephone, or a camera, or a storefront, or a café.
After a while, successful simulated machines displace and overtake the machines they originally imitated. The word processor is no longer just a simulated typewriter or secretary, but a first-order tool for producing written materials of all kinds. Eventually, if they thrive, simulated machines become just machines.
Today, computation overall is doing this. There’s not much work and play left that computers don’t handle. And so, the computer is splitting from its origins as a means of symbol manipulation for productive and creative ends, and becoming an activity in its own right. Today, people don’t seek out computers in order to get things done; they do the things that let them use computers.