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Has the age of computer overlords begun?
An IBM computer has thrashed two human champions in the quiz show Jeopardy! Is it game over for humanity?
"I for one welcome our new computer overlords," quipped Ken Jennings as he and Brad Rutter, up to that point the world's leading contestants on the quiz show "Jeopardy!", went down to defeat by Watson, a robotic system developed by IBM.
Has it really come to this? Is humanity now doomed to subservient status, while robots increasingly displace us from jobs that were once considered the exclusive domain of thinking beings?
Can a machine think?
This question was posed already more than 60 years ago, at the dawn of the age of electronic computers. Alan Turing, a pioneering computer scientist, proposed a test by which it could be judged whether a machine was intelligent. The test, which he called the Imitation Game but which is now universally referred to as the Turing Test, basically requires that the machine be able to carry on a conversation (using a text interface similar to a chat system to remove cues such as physical appearance from consideration) that would fool a human judge into believing it was human.
Although the test has its critics on philosophical as well as practical grounds, it has stood as a grand challenge for workers in the field of artificial intelligence (AI). Turing believed that a computer would pass the test by the year 2000, but clearly the task has turned out to be harder than it looked to him.
Despite decades of efforts by many very smart people, the goal remains seemingly as far out of reach as ever. This fact has only been made more apparent by an actual attempt to carry out the Turing Test in practice. The Loebner Prize contest, sponsored by a businessman with no background in computer science, annually pits the best conversationalist computer programs, called chatbots, against each other and against a selection of humans to compete for the prize of Most Human.
AI researchers generally regard the competition as a farce and a distraction. Even the best chatbots are hollow when you look inside them, using various gimmicks and rules of thumb to produce plausible but essentially meaningless dialog. Meanwhile, efforts to produce computer programs that can genuinely understand language and display common sense have made only slow progress.
Now suddenly a new contender has burst onto the scene, which actually looks like a possible candidate for the status of a thinking machine. Has IBM finally done it? Have its scientists produced true artificial intelligence?
Watson could not pass or even enter the Turing Test, since it is not a conversationalist. It only answers questions, one after another and cannot carry on a dialog. So we would have to set aside Turing's standard for judging intelligence. But if we look at Watson's performance simply on its own merits, was the machine thinking?
Despite all the hype that appeared in the wake of Watson's victory on "Jeopardy!" in the match televised February 14, 15, and 16, the answer is: definitely not.
Watson unquestionably represents a new level of ability in responding to questions given in natural language, a notoriously difficult problem for AI. Human language is full of ambiguity, words have multiple meanings, and context makes a great deal of difference to what sort of answer is expected. Compounding these difficulties, "Jeopardy!" clues often involve puns or other types of witty word play that are very difficult for computers to deal with.
The IBM researchers who built and programmed Watson are to be commended for a real tour de force, combining sophisticated processing of vast quantities of unstructured textual data harvested from the Internet with powerful statistical-association methods that allow various facts and concepts to be related to one another. They have built on the results of years of AI research to achieve an impressively capable question-answering system.
But Watson does not think, at least in the usual meaning of the word, and as Turing intended it to be understood. Watson does not "understand" the content of either the questions or its own answers. It works by generating hypotheses by applying search-engine techniques to the clues and then deciding which hypothesis has the highest likelihood of being correct. Watson's lack of true understanding is revealed occasionally when it makes an elementary mistake such as giving "Toronto" as an answer when a US city was clearly required.
Watson is a remarkable achievement. More importantly, the methods that were used in programming it are not tied specifically to the task of answering trivia questions. It would be straightforward to re-program it to answer questions about medical diagnosis, for example. In fact IBM has already announced plans to work with a hospital to develop a physician's assistant based on Watson technology. Other possible application areas, such as sales assistance or computer troubleshooting, come readily to mind.
But Watson is too expensive for widespread adoption in the near term. The system that was used to play "Jeopardy!" packs a cluster of 90 high-end servers into a rack the size of ten refrigerators, and must have cost well over $10 million. However, if computer hardware continues its historical trend of steadily increasing performance per unit cost, we can expect similarly capable systems to become affordable for moderate-sized businesses in a decade or so.
When that happens, we can expect to see many companies attempt to use this type of technology as a complete replacement for human workers such as sales clerks or help-desk staff. However, I believe that they, and more importantly their customers, will find the results less than satisfactory. Susan Feldman, an analyst for the consulting firm IDC, has written insightfully,
It is also important to note that Watson is not creative. It cannot come up with any new ideas of its own. If asked for a solution to a problem, it can search for and locate a solution, if someone somewhere has already come up with one. But it is not equipped to be original.
This means that a better role for Watson is as a quick, knowledgeable aide to human specialists, helping them to manage large volumes of facts that would be too overwhelming for any one person to assimilate. This is a development to look forward to, not to dread.
After all, we need to keep clearly in focus that we build computers and other tools to help humans achieve their goals, not the other way around. Efficiency and lowering costs are means, not ends.
In "R.U.R.," the classic science-fiction play about a world run by robots, the general manager of the robot factory is asked what makes the best kind of worker: is it honesty, dedication? "No," he answers, "it's the one that's the cheapest."
But ultimately labour and production are not about economics and doing things the cheapest way. They are about fulfilling human needs, one of which is to be useful, to be creative, to participate in the great task of being stewards of creation and making the earth a better place. Computers are not yet our overlords or even our peers in this enterprise, and not likely to be so soon.
Associate Professor Bob Moniot teaches computer science at Fordham University in New York.
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