Why computers can’t really ‘think’

Stanley Fish sparked off a lively debate with his NYT piece about IBM’s Watson machine. This is an excerpt from an interesting response by Sean Dorrance Kelly and Hubert Dreyfus.

The fact is, things are relevant for human beings because at root we are beings for whom things matter. Relevance and mattering are two sides of the same coin. As Haugeland said, “The problem with computers is that they just don’t give a damn.” It is easy to pretend that computers can care about something if we focus on relatively narrow domains — like trivia games or chess — where by definition winning the game is the only thing that could matter, and the computer is programmed to win. But precisely because the criteria for success are so narrowly defined in these cases, they have nothing to do with what human beings are when they are at their best.

Far from being the paradigm of intelligence, therefore, mere matching with no sense of mattering or relevance is barely any kind of intelligence at all. As beings for whom the world already matters, our central human ability is to be able to see what matters when. But, as we show in our recent book, this is an existential achievement orders of magnitude more amazing and wonderful than any statistical treatment of bare facts could ever be. The greatest danger of Watson’s victory is not that it proves machines could be better versions of us, but that it tempts us to misunderstand ourselves as poorer versions of them.

This comforting line of argument doesn’t square with Peter Wilby’s scepticism about the prevailing assurances of Western governments that “If enough people buckle down to acquiring higher-level skills and qualifications, Europeans and Americans will continue to enjoy rising living standards. If they work hard enough, each generation can still do better than its parents. All that is required is to bring schools up to scratch and persuade universities to teach ‘marketable” skills.'”

“Knowledge work”, supposedly the west’s salvation, is now being exported like manual work. A global mass market in unskilled labour is being quickly succeeded by a market in middle-class work, particularly for industries, such as electronics, in which so much hope of employment opportunities and high wages was invested. As supply increases, employers inevitably go to the cheapest source. A chip designer in India costs 10 times less than a US one. The neoliberals forgot to read (or re-read) Marx. “As capital accumulates the situation of the worker, be his payment high or low, must grow worse.”

We are familiar with the outsourcing of routine white-collar “back office” jobs such as data inputting. But now the middle office is going too. Analysing X-rays, drawing up legal contracts, processing tax returns, researching bank clients, and even designing industrial systems are examples of skilled jobs going offshore. Even teaching is not immune: last year a north London primary school hired mathematicians in India to provide one-to-one tutoring over the internet. Microsoft, Siemens, General Motors and Philips are among big firms that now do at least some of their research in China. The pace will quicken. The export of “knowledge work” requires only the transmission of electronic information, not factories and machinery. Alan Blinder, a former vice-chairman of the US Federal Reserve, has estimated that a quarter of all American service sector jobs could go overseas.

And John Markoff, in another essay reports the intentions of IBM executives

to commercialize Watson to provide a new class of question-answering systems in business, education and medicine. The repercussions of such technology are unknown, but it is possible, for example, to envision systems that replace not only human experts, but hundreds of thousands of well-paying jobs throughout the economy and around the globe. Virtually any job that now involves answering questions and conducting commercial transactions by telephone will soon be at risk. It is only necessary to consider how quickly A.T.M.’s displaced human bank tellers to have an idea of what could happen.

To be sure, anyone who has spent time waiting on hold for technical support, or trying to change an airline reservation, may welcome that day. However, there is also a growing unease about the advances in natural language understanding that are being heralded in systems like Watson. As rapidly as A.I.-based systems are proliferating, there are equally compelling examples of the power of I.A. — systems that extend the capability of the human mind.