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Submission + - Economists Say Newest AI Technology Destroys More Jobs Than It Creates

HughPickens.com writes: Claire Cain Miller writes at the NYT that economists long argued that, just as buggy-makers gave way to car factories, technology used to create as many jobs as it destroyed. But now there is deep uncertainty about whether the pattern will continue, as two trends are interacting. First, artificial intelligence has become vastly more sophisticated in a short time, with machines now able to learn, not just follow programmed instructions, and to respond to human language and movement. At the same time, the American work force has gained skills at a slower rate than in the past — and at a slower rate than in many other countries. Self-driving vehicles are an example of the crosscurrents. Autonomous cars could put truck and taxi drivers out of work — or they could enable drivers to be more productive during the time they used to spend driving, which could earn them more money. But for the happier outcome to happen, the drivers would need the skills to do new types of jobs.

When the University of Chicago asked a panel of leading economists about automation, 76 percent agreed that it had not historically decreased employment. But when asked about the more recent past, they were less sanguine. About 33 percent said technology was a central reason that median wages had been stagnant over the past decade, 20 percent said it was not and 29 percent were unsure. Perhaps the most worrisome development is how poorly the job market is already functioning for many workers. More than 16 percent of men between the ages of 25 and 54 are not working, up from 5 percent in the late 1960s; 30 percent of women in this age group are not working, up from 25 percent in the late 1990s. For those who are working, wage growth has been weak, while corporate profits have surged. “We’re going to enter a world in which there’s more wealth and less need to work,” says Erik Brynjolfsson. “That should be good news. But if we just put it on autopilot, there’s no guarantee this will work out.”

Submission + - Inside the Facebook algorithm most users don't even know exists (dailydot.com)

catparty writes: An examination of what we can know about Facebook's new machine learning News Feed algorithm:

Facebook's current News Feed algorithm might be smarter, but some of its core considerations don't stray too far from the groundwork laid by EdgeRank, though thanks to machine learning, Facebook's current algorithm has a better ear for "signals from you." Facebook confirmed to us that the new News Feed ranking algorithm does indeed take 100,000 weighted variables into account to determine what we see. These factors help Facebook display an average 300 posts culled from roughly 1,500 possible posts per day, per user.


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