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Imagine that 7 out of 10 working Americans got fired tomorrow. What would they all do? Second Part, by Kevin Kelly
By Admin (from 12/01/2013 @ 03:04:51, in en - Science and Society, read 1978 times)


Baxter was invented in a century-old brick building near the Charles River in Boston. In 1895 the building was a manufacturing marvel in the very center of the new manufacturing world. It even generated its own electricity. For a hundred years the factories inside its walls changed the world around us. Now the capabilities of Baxter and the approaching cascade of superior robot workers spur Brooks to speculate on how these robots will shift manufacturing in a disruption greater than the last revolution. Looking out his office window at the former industrial neighborhood, he says, “Right now we think of manufacturing as happening in China. But as manufacturing costs sink because of robots, the costs of transportation become a far greater factor than the cost of production. Nearby will be cheap. So we’ll get this network of locally franchised factories, where most things will be made within 5 miles of where they are needed.”

That may be true of making stuff, but a lot of jobs left in the world for humans are service jobs. I ask Brooks to walk with me through a local McDonald’s and point out the jobs that his kind of robots can replace. He demurs and suggests it might be 30 years before robots will cook for us. “In a fast food place you’re not doing the same task very long. You’re always changing things on the fly, so you need special solutions. We are not trying to sell a specific solution. We are building a general-purpose machine that other workers can set up themselves and work alongside.” And once we can cowork with robots right next to us, it’s inevitable that our tasks will bleed together, and soon our old work will become theirs—and our new work will become something we can hardly imagine.

To understand how robot replacement will happen, it’s useful to break down our relationship with robots into four categories, as summed up in this chart:

The rows indicate whether robots will take over existing jobs or make new ones, and the columns indicate whether these jobs seem (at first) like jobs for humans or for machines.

Let’s begin with quadrant A: jobs humans can do but robots can do even better. Humans can weave cotton cloth with great effort, but automated looms make perfect cloth, by the mile, for a few cents. The only reason to buy handmade cloth today is because you want the imperfections humans introduce. We no longer value irregularities while traveling 70 miles per hour, though—so the fewer humans who touch our car as it is being made, the better.

And yet for more complicated chores, we still tend to believe computers and robots can’t be trusted. That’s why we’ve been slow to acknowledge how they’ve mastered some conceptual routines, in some cases even surpassing their mastery of physical routines. A computerized brain known as the autopilot can fly a 787 jet unaided, but irrationally we place human pilots in the cockpit to babysit the autopilot “just in case.” In the 1990s, computerized mortgage appraisals replaced human appraisers wholesale. Much tax preparation has gone to computers, as well as routine x-ray analysis and pretrial evidence-gathering—all once done by highly paid smart people. We’ve accepted utter reliability in robot manufacturing; soon we’ll accept it in robotic intelligence and service.

Next is quadrant B: jobs that humans can’t do but robots can. A trivial example: Humans have trouble making a single brass screw unassisted, but automation can produce a thousand exact ones per hour. Without automation, we could not make a single computer chip—a job that requires degrees of precision, control, and unwavering attention that our animal bodies don’t possess. Likewise no human, indeed no group of humans, no matter their education, can quickly search through all the web pages in the world to uncover the one page revealing the price of eggs in Katmandu yesterday. Every time you click on the search button you are employing a robot to do something we as a species are unable to do alone.

While the displacement of formerly human jobs gets all the headlines, the greatest benefits bestowed by robots and automation come from their occupation of jobs we are unable to do. We don’t have the attention span to inspect every square millimeter of every CAT scan looking for cancer cells. We don’t have the millisecond reflexes needed to inflate molten glass into the shape of a bottle. We don’t have an infallible memory to keep track of every pitch in Major League Baseball and calculate the probability of the next pitch in real time.

We aren’t giving “good jobs” to robots. Most of the time we are giving them jobs we could never do. Without them, these jobs would remain undone.

Now let’s consider quadrant C, the new jobs created by automation—including the jobs that we did not know we wanted done. This is the greatest genius of the robot takeover: With the assistance of robots and computerized intelligence, we already can do things we never imagined doing 150 years ago. We can remove a tumor in our gut through our navel, make a talking-picture video of our wedding, drive a cart on Mars, print a pattern on fabric that a friend mailed to us through the air. We are doing, and are sometimes paid for doing, a million new activities that would have dazzled and shocked the farmers of 1850. These new accomplishments are not merely chores that were difficult before. Rather they are dreams that are created chiefly by the capabilities of the machines that can do them. They are jobs the machines make up.

Before we invented automobiles, air-conditioning, flatscreen video displays, and animated cartoons, no one living in ancient Rome wished they could watch cartoons while riding to Athens in climate-controlled comfort. Two hundred years ago not a single citizen of Shanghai would have told you that they would buy a tiny slab that allowed them to talk to faraway friends before they would buy indoor plumbing. Crafty AIs embedded in first-person-shooter games have given millions of teenage boys the urge, the need, to become professional game designers—a dream that no boy in Victorian times ever had. In a very real way our inventions assign us our jobs. Each successful bit of automation generates new occupations—occupations we would not have fantasized about without the prompting of the automation.

To reiterate, the bulk of new tasks created by automation are tasks only other automation can handle. Now that we have search engines like Google, we set the servant upon a thousand new errands. Google, can you tell me where my phone is? Google, can you match the people suffering depression with the doctors selling pills? Google, can you predict when the next viral epidemic will erupt? Technology is indiscriminate this way, piling up possibilities and options for both humans and machines.

It is a safe bet that the highest-earning professions in the year 2050 will depend on automations and machines that have not been invented yet. That is, we can’t see these jobs from here, because we can’t yet see the machines and technologies that will make them possible. Robots create jobs that we did not even know we wanted done.


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