Friday, January 17, 2014

What Will Your Children Do For A Living?

The Economist takes on the problem of mechanization and enormous inequality, by @DavidOAtkins
Of course the solutions, such as they are, that the Economist offers up are woefully inadequate. But at least they are covering the issue. And the issue is, we're quickly automating the bulk of humanity out of a job. And that is going to require major, major shifts in the structure of society.
The prosperity unleashed by the digital revolution has gone overwhelmingly to the owners of capital and the highest-skilled workers. Over the past three decades, labour's share of output has shrunk globally from 64% to 59%. Meanwhile, the share of income going to the top 1% in America has risen from around 9% in the 1970s to 22% today. Unemployment is at alarming levels in much of the rich world, and not just for cyclical reasons. In 2000, 65% of working-age Americans were in work; since then the proportion has fallen, during good years as well as bad, to the current level of 59%. Worse, it seems likely that this wave of technological disruption to the job market has only just started. From driverless cars to clever household gadgets (see article), innovations that already exist could destroy swathes of jobs that have hitherto been untouched. The public sector is one obvious target: it has proved singularly resistant to tech-driven reinvention. But the step change in what computers can do will have a powerful effect on middle-class jobs in the private sector too. Until now the jobs most vulnerable to machines were those that involved routine, repetitive tasks. But thanks to the exponential rise in processing power and the ubiquity of digitised information ("big data"), computers are increasingly able to perform complicated tasks more cheaply and effectively than people. Clever industrial robots can quickly "learn" a set of human actions. Services may be even more vulnerable. Computers can already detect intruders in a closed-circuit camera picture more reliably than a human can. By comparing reams of financial or biometric data, they can often diagnose fraud or illness more accurately than any number of accountants or doctors. One recent study by academics at Oxford University suggests that 47% of today's jobs could be automated in the next two decades.

Typos courtesy of my iPhone

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