Watson, Technology, Trade and what kind of job will you have after college?
You may have heard or watched on TV how "Watson," the artificial intelligence system developed by IBM, soundly defeated the reigning human Jeopardy TV show champions in recent contests. In the game of Jeopardy contestants are read an 'answer' and the first to guess the corresponding 'question' wins. For example, in the 'Olympic Oddities' category Watson was the first to correctly say "What is a leg" given the 'answer' "it was the anatomical oddity of U.S. gymnast George Eyser, who won a gold medal on the parallel bars in 1904."
Watson's impressive trouncing of humans that everyone considered highly educated experts has led many people to ponder whether we might not in fact be living through the eve of an impressive new technological revolution that may foist a radical new world upon us. It seems only a matter of time before this kind of technology replaces all kinds of humans.
Until recently many economists were of the view that the segment of the population most likely to be adversely affected by both technological change and/or by offshoring were relatively low-skilled workers in jobs were tasks could be routinized. For instance, factory assembly line jobs in the USA, would be likely replaced by robots and/or by offshoring those tasks to low-wage overseas markets. This interpretation has frequently been held up as one explanation for the observed widening of the income distribution in the United States over the past 3-4 decades because, it was said, more educated white-collar workers with college degrees would earn a premium over blue collar workers as the more educated would be needed to manage and work with these new more sophisticated machines.
But as Princeton trade economist Paul Krugman recently wrote in a New York Times column (free access after signup) the emergence of artificial intelligence machines like Watson supports the contention of other research economiststhat "the crucial difference in terms of possible replacement of humans by machines [is] one of routine versus non-routine, rather than white-collar versus blue-collar, and that computerization was if anything likely to increase demand for some “low-skill” occupations and reduce demand for some traditionally well-paying white-collar jobs." For instance to several types of medical diagnosis (e.g. interpreting X-rays) and legal work (sifting through reams of legal documents in search of a clue or incriminating evidence). Until recently many people that only well paid and highly educated humans could do these tasks well (and would be paid well for their work), but now it seems we might already be in a world where computers can do these things at least as well, and in many instances, better and much much faster than humans. Many middle-class occupations held by educated workers, suddenly seem under threat.
Others (see here and follow the links he points to) have weighed in on this debate (e.g. , some claiming this is our moment of technological singularity -- interesting podcast on the topic of singularity here)
It's useful to think about these issues using the specific factors and HOS models. Think of the role of technology and how it is changing. What must happen to the income distribution? Who gains in this new world? Who loses?
Watson's impressive trouncing of humans that everyone considered highly educated experts has led many people to ponder whether we might not in fact be living through the eve of an impressive new technological revolution that may foist a radical new world upon us. It seems only a matter of time before this kind of technology replaces all kinds of humans.
Until recently many economists were of the view that the segment of the population most likely to be adversely affected by both technological change and/or by offshoring were relatively low-skilled workers in jobs were tasks could be routinized. For instance, factory assembly line jobs in the USA, would be likely replaced by robots and/or by offshoring those tasks to low-wage overseas markets. This interpretation has frequently been held up as one explanation for the observed widening of the income distribution in the United States over the past 3-4 decades because, it was said, more educated white-collar workers with college degrees would earn a premium over blue collar workers as the more educated would be needed to manage and work with these new more sophisticated machines.
But as Princeton trade economist Paul Krugman recently wrote in a New York Times column (free access after signup) the emergence of artificial intelligence machines like Watson supports the contention of other research economiststhat "the crucial difference in terms of possible replacement of humans by machines [is] one of routine versus non-routine, rather than white-collar versus blue-collar, and that computerization was if anything likely to increase demand for some “low-skill” occupations and reduce demand for some traditionally well-paying white-collar jobs." For instance to several types of medical diagnosis (e.g. interpreting X-rays) and legal work (sifting through reams of legal documents in search of a clue or incriminating evidence). Until recently many people that only well paid and highly educated humans could do these tasks well (and would be paid well for their work), but now it seems we might already be in a world where computers can do these things at least as well, and in many instances, better and much much faster than humans. Many middle-class occupations held by educated workers, suddenly seem under threat.
Others (see here and follow the links he points to) have weighed in on this debate (e.g. , some claiming this is our moment of technological singularity -- interesting podcast on the topic of singularity here)
It's useful to think about these issues using the specific factors and HOS models. Think of the role of technology and how it is changing. What must happen to the income distribution? Who gains in this new world? Who loses?
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