Your career is now a game of musical chairs: you need to be ready when the song stops
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Although sixty years old, artificial intelligence remained mostly a curiosity until half a decade ago, when IBM's Watson trounced the world's best Jeopardy! players in a televised match. At the time, you might have thought nothing of that - what does a game show matter in the scheme of things?
It didn't stop there. IBM sent Watson to train with oncologists and lawyers and financial advisers. Quite suddenly, three very established professions, just the sort of thing you'd tell your kids to pursue as a ticket to prosperity, seemed a lot less certain of their futures in a world where intelligence, like computing before it, becomes pervasive, then commoditised.
These top-of-their-profession projects show that the driver to bring artificial intelligence into any field isn't the amount of labor, but rather the cost of that labor. A lawyer costs fifty times more per hour than a retail worker and so is that many times more likely to find themselves with an AI competitor.
(Score: 2) by stormreaver on Tuesday November 15 2016, @06:44PM
The market for so-called Artificial Intelligence is limited to fields that computers have always excelled at: grunt work.
Any profession which relies upon creativity will always be safe from computer takeover.
(Score: 5, Funny) by pkrasimirov on Tuesday November 15 2016, @07:24PM
Yeah, there always will be jobs for Art majors.
(Score: 1, Touché) by Anonymous Coward on Tuesday November 15 2016, @07:47PM
But no jobs for code monkeys. Git bisect has already made debugging obsolete, and you can rest assured every project on GitHub is completely free of bugs.
(Score: 1, Informative) by Anonymous Coward on Wednesday November 16 2016, @12:54AM
Well, actually computers can be pretty good at creativity, generating myriads of random and unforeseen combinations and variations of initial patterns or criteria. Culling them for the market is hard part. But even there automation can help test variations via measuring ad clicks and visitors.
Click-bait and spamming co's more or less do that now: generate gazillion combinations, measure click traffic to find the most popular, then cross-breed the popular ones to improve them more. Essentially a genetic algorithm.
Imagine a sewing bot that automatically creates samples of computer-generated fashion designs. Based on sales, the best trials are then cross-bred and re-tested.