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How long does it take you to add 3,456,732 and 2,245,678? Ten seconds? Not bad--for a human. The average new PC can perform the calculation in 0.000000018 second. How about your memory? Can you remember a shopping list of 10 items? Maybe 20? Compare that with 125 million items for the PC.
On the other hand, computers are stumped by faces, which people recognize instantly. Machines lack the creativity for novel ideas and have no feelings and no fond memories of their youth. But recent technological advances are narrowing the gap between human brains and circuitry. At Stanford University, bioengineers are replicating the complicated parallel processing of neural networks on microchips. Another development--a robot named Darwin VII--has a camera and a set of metal jaws so that it can interact with its environment and learn, the way juvenile animals do. Researchers at the Neurosciences Institute in La Jolla, Calif., modeled Darwin's brain on rat and ape brains.
The developments raise a natural question: If computer processing eventually apes nature's neural networks, will cold silicon ever be truly able to think? And how will we judge whether it does? More than 50 years ago British mathematician and philosopher Alan Turing invented an ingenious strategy to address this question, and the pursuit of this strategy has taught science a great deal about designing artificial intelligence, a field now known as AI. At the same time, it has shed some light on human cognition.
Beginnings: Testing Smarts
So what, exactly, is this elusive capacity we call "thinking"? People often use the word to describe processes that involve consciousness, understanding and creativity. In contrast, current computers merely follow the instructions provided by their programming.
In 1950, an era when silicon microchips did not yet exist, Turing realized that as computers got smarter, this question about artificial intelligence would eventually arise. [For more on Turing's life and work, see box on opposite page.] In what is arguably the most famous philosophy paper ever written, "Computing Machinery and Intelligence," Turing simply replaced the question "Can machines think?" with "Can a machine--a computer--pass the imitation game?" That is, can a computer converse so naturally that it could fool a person into thinking that it was a human being?
Turing took his idea from a simple parlor game in which a person, called the interrogator, must determine, by asking a series of questions, whether or not an unseen person in another room is a man or a woman. In his thought experiment he replaced the person in the other room with a computer. To pass what is now called the Turing Test, the computer must answer any question from an interrogator with the linguistic competency and sophistication of a human being.
Turing ended his seminal paper with the prediction that in 50 years' time--which is right about now--we would be able to build computers that are so good at playing the imitation game that an average interrogator will have only a 70 percent chance of correctly identifying whether he or she is speaking to a person or a machine.
Why does something that comes so easily for people pose such hurdles for machines?
So far Turing's prediction has not come true [see box on page 80]. No computer can actually pass the Turing Test. Why does something that comes so easily for people pose such hurdles for machines? To pass the test, computers would have to demonstrate not just one competency (in mathematics, say, or knowledge of fishing) but many of them--as many competencies as the average human being possesses. Yet computers have what is called a restricted design. Their programming enables them to accomplish a specific job, and they have a knowledge base that is relevant to that task alone. A good example is Anna, IKEA's online assistant. You can ask Anna about IKEA's products and services, but she will not be able to tell you about the weather. PAGE 1 | 2 | 3 | Next»
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