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Robot Workers' Real Draw: Reducing Dependence on Human Workers
HughPickens.com writes: Zeynep Tufekci writes in an op-ed at the NY Times that machines are getting better than humans at figuring out who to hire, who's in a mood to pay a little more for that sweater, and who needs a coupon to nudge them toward a sale. It turns out most of what we think of as expertise, knowledge and intuition is being deconstructed and recreated as an algorithmic competency, fueled by big data. "Machines aren't used because they perform some tasks that much better than humans, but because, in many cases, they do a "good enough" job while also being cheaper, more predictable and easier to control than quirky, pesky humans," writes Tufekci. "Technology in the workplace is as much about power and control as it is about productivity and efficiency."
According to Tufekci technology is being used in many workplaces: to reduce the power of humans, and employers' dependency on them, whether by replacing, displacing or surveilling them. Optimists insist that we've been here before, during the Industrial Revolution, when machinery replaced manual labor, and all we need is a little more education and better skills. Tufekci points out that one historical example is no guarantee of future events. "Confronting the threat posed by machines, and the way in which the great data harvest has made them ever more able to compete with human workers, must be about our priorities," concludes Tufekci. "This problem is not us versus the machines, but between us, as humans, and how we value one another."
According to Tufekci technology is being used in many workplaces: to reduce the power of humans, and employers' dependency on them, whether by replacing, displacing or surveilling them. Optimists insist that we've been here before, during the Industrial Revolution, when machinery replaced manual labor, and all we need is a little more education and better skills. Tufekci points out that one historical example is no guarantee of future events. "Confronting the threat posed by machines, and the way in which the great data harvest has made them ever more able to compete with human workers, must be about our priorities," concludes Tufekci. "This problem is not us versus the machines, but between us, as humans, and how we value one another."
This fallacy that machines on net balance create unemployment has been destroyed a thousand times, and yet it keeps rising like a malignant Phoenix as hardy and vigorous as ever. This time, the government is not the sole coercive agent. The Luddite rebellion in early 19th-century England is the prime example.
Labor unions have succeeded in restricting automation and other labor-saving improvements in many cases. The half-truth of the fallacy is evident here. Jobs are destroyed for particular groups and in the short term. Overall, the wealth created by using the labor-saving devices and practices generates far more jobs than are lost directly.
Arkwright invented his cotton-spinning machinery in 1760. The use of it was opposed on the ground that it threatened the livelihood of the workers, and the opposition had to be put down by force. 27 years later, there were over 40 times as many people working in the industry.
What happens when jobs are destroyed by a new machine? The employer will use his savings in one or more of three ways:
(1) to expand his operations by buying more machines; (2) to invest the extra profits in some other industry; or (3) spend the extra profits on his own consumption.
The direct effect of this spending will be to create as many jobs as were destroyed. The overall net effect to the economy is to create wealth and even more jobs. We must remember that the short-term local effect is to destroy jobs. In some cases where this effect is major, special relief measures through charities and non-profits might be taken, but blocking the progress leads to stagnation and poverty.