When Robots Run the Show
Posted on Aug 21, 2015
By Peter Richardson
“Rise of the Robots: Technology and the Threat of a Jobless Future”
A book by Martin Ford
There’s good reason to believe that robots will replace more and more workers, especially those who perform routine tasks, in the coming years. According to one analysis, up to 47 percent of jobs in the United States now performed by humans will be performed by machines within two decades. In the past, this sort of job loss was attributed to “creative destruction” — the destruction of something old by something new, which economist Joseph Schumpeter considered “the essential fact about capitalism.” Continuous innovation sustained economic growth even as it destroyed older modes of production. Predictions of long-term joblessness went awry because innovation also transformed our wants and needs. When I was running Fortran programs using punched cards, I didn’t realize I would eventually need a handheld computer that also doubled as my telephone, camera and navigational guide.
In “Rise of the Robots: Technology and the Threat of a Jobless Future,” author Martin Ford, software developer and computer designer, predicts that the next wave of job losses will be different. The main reason for this difference, he argues, is Moore’s Law. Formulated in the mid-1960s by Intel founder Gordon Moore, that axiom predicts that advances in chip technology will increase computing power exponentially. When combined with advances in robotics and artificial intelligence, these gains will make robots the most efficient way to perform routine work now allocated to humans.
We shouldn’t underestimate the consequences of accelerating automation, but Ford’s thesis is vulnerable to two sets of counterarguments. The first set is economic. Yes, American jobs are disappearing, but Ford never makes a convincing case that automation — rather than the neoliberal policies we have pursued for decades — is the main culprit. Indeed, it often seems he has read but not fully digested the relevant literature in labor economics, international trade, economic history and political economy. This lack of expertise doesn’t prevent him from offering a wide range of policy prescriptions.
Much of Ford’s book considers the role of automation in various sectors of the economy, not all of which conform to his thesis. By putting robots at the center of his health care discussion, for example, he seems to overlook the real reasons Americans pay so much (and show worse health outcomes) compared with residents of other advanced countries. In the second half of the chapter, however, Ford turns to the well-known drawbacks of the American approach. He concludes that “health care is a broken market and no amount of technology is likely to bring down costs until the structural problems of the industry are resolved.” This conclusion appears to be a setback for his argument, but instead of modifying his thesis, he suggests “a brief detour from our technology narrative” to offer his policy solutions for this sector. Then, having acknowledged a tenuous connection between automation and the 18 percent of the American economy that comprises our health care costs, Ford returns to his robo-centric discussion.
The other main challenge to Ford’s analysis, one he never addresses, is philosophical. More than four decades ago, philosopher Hubert Dreyfus outlined the conceptual limits of artificial intelligence in “What Computers Can’t Do” (1972). Those limits revolve around the difference between computation, which machines do very well, and consciousness, which machines don’t possess. Many in the high-tech community ignored or mocked Dreyfus’ argument, but by the early 1990s, most had conceded that his critique was on point. It resurfaced in 1999, when Dreyfus’ former colleague, John Searle, assessed Ray Kurzweil’s book, “The Age of Spiritual Machines: When Computers Exceed Human Intelligence.” Searle called that work “an extended reflection on the implications of Moore’s Law” and argued that Kurzweil, an accomplished high-tech inventor and controversial futurist, had left a “huge gulf between the spectacular claims advanced and the weakness of the arguments given in their support.” The main drawback, Searle claimed, was that Kurzweil had failed to distinguish between artificial intelligence and consciousness. When Kurzweil complained about the review in print, Searle made quick work of him.
Basic Books
To see long excerpts from “Rise of the Robots” at Google Books, click here.
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A book by Martin Ford
There’s good reason to believe that robots will replace more and more workers, especially those who perform routine tasks, in the coming years. According to one analysis, up to 47 percent of jobs in the United States now performed by humans will be performed by machines within two decades. In the past, this sort of job loss was attributed to “creative destruction” — the destruction of something old by something new, which economist Joseph Schumpeter considered “the essential fact about capitalism.” Continuous innovation sustained economic growth even as it destroyed older modes of production. Predictions of long-term joblessness went awry because innovation also transformed our wants and needs. When I was running Fortran programs using punched cards, I didn’t realize I would eventually need a handheld computer that also doubled as my telephone, camera and navigational guide.
In “Rise of the Robots: Technology and the Threat of a Jobless Future,” author Martin Ford, software developer and computer designer, predicts that the next wave of job losses will be different. The main reason for this difference, he argues, is Moore’s Law. Formulated in the mid-1960s by Intel founder Gordon Moore, that axiom predicts that advances in chip technology will increase computing power exponentially. When combined with advances in robotics and artificial intelligence, these gains will make robots the most efficient way to perform routine work now allocated to humans.
We shouldn’t underestimate the consequences of accelerating automation, but Ford’s thesis is vulnerable to two sets of counterarguments. The first set is economic. Yes, American jobs are disappearing, but Ford never makes a convincing case that automation — rather than the neoliberal policies we have pursued for decades — is the main culprit. Indeed, it often seems he has read but not fully digested the relevant literature in labor economics, international trade, economic history and political economy. This lack of expertise doesn’t prevent him from offering a wide range of policy prescriptions.
Much of Ford’s book considers the role of automation in various sectors of the economy, not all of which conform to his thesis. By putting robots at the center of his health care discussion, for example, he seems to overlook the real reasons Americans pay so much (and show worse health outcomes) compared with residents of other advanced countries. In the second half of the chapter, however, Ford turns to the well-known drawbacks of the American approach. He concludes that “health care is a broken market and no amount of technology is likely to bring down costs until the structural problems of the industry are resolved.” This conclusion appears to be a setback for his argument, but instead of modifying his thesis, he suggests “a brief detour from our technology narrative” to offer his policy solutions for this sector. Then, having acknowledged a tenuous connection between automation and the 18 percent of the American economy that comprises our health care costs, Ford returns to his robo-centric discussion.
The other main challenge to Ford’s analysis, one he never addresses, is philosophical. More than four decades ago, philosopher Hubert Dreyfus outlined the conceptual limits of artificial intelligence in “What Computers Can’t Do” (1972). Those limits revolve around the difference between computation, which machines do very well, and consciousness, which machines don’t possess. Many in the high-tech community ignored or mocked Dreyfus’ argument, but by the early 1990s, most had conceded that his critique was on point. It resurfaced in 1999, when Dreyfus’ former colleague, John Searle, assessed Ray Kurzweil’s book, “The Age of Spiritual Machines: When Computers Exceed Human Intelligence.” Searle called that work “an extended reflection on the implications of Moore’s Law” and argued that Kurzweil, an accomplished high-tech inventor and controversial futurist, had left a “huge gulf between the spectacular claims advanced and the weakness of the arguments given in their support.” The main drawback, Searle claimed, was that Kurzweil had failed to distinguish between artificial intelligence and consciousness. When Kurzweil complained about the review in print, Searle made quick work of him.
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