When Nixon opened China to American business, U.S. manufacturing was still a viable source of employment for a large swath of the middle class. When robots began replacing workers on assembly lines, it was an early sign of myopia. When corporations (which, as late as the 1990s, offered mentoring programs for high school and college students and often provided internships as a first step toward employment) stopped nurturing a domestic workforce, U.S. industry made it clear that profitability was number one. There was no consistent number two.
Now the problem is severe. The American middle class is the subject of countless political speeches by candidates and elected officials. Yet nothing’s ever done that offers real hope of restoring domestic employment. Meanwhile, in parallel, there is the rise of smart machines, the export of white collar jobs, and the elimination of job training/retraining programs for lack of funding (and the easy availability of Asian workers who can be brought into the States on H-1B visas, be hired as students, or be employed in situ in their home countries). This is, in a very real sense, a tax issue, as I’ll explain.
Smarter than a Rocket Scientist
Taken to a logical end, artificial intelligence has the potential to replace millions of workers in the U.S. and around the world, whether A.I. is employed to solve problems, run machinery, or create new machines that can program themselves. For all the good that IBM’s Watson can do in fields like medical research (to find effective treatments and cures for disease), national security (to detect threat patterns), and fraud detection (in financial services industries), it also implies that humans aren’t fast enough or objective enough to do that work. And a November 2015 story in the Harvard Business Review, while crowing about a new generation of robots that are safe enough to interact with people, points out with no sense of irony that the robots can learn from their human co-workers. That is not a source of comfort to the labor force.
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