How long will it be before you lose your job to a robot?

ReshoringMatt Blease

❝ How long will it be before you, too, lose your job to a computer? This question is taken up by a number of recent books, with titles that read like variations on a theme: “The Industries of the Future,” “The Future of the Professions,” “Inventing the Future.” Although the authors of these works are employed in disparate fields — law, finance, political theory — they arrive at more or less the same conclusion. How long? Not long.

❝ “Could another person learn to do your job by studying a detailed record of everything you’ve done in the past?” Martin Ford, a software developer, asks early on in “Rise of the Robots: Technology and the Threat of a Jobless Future”…“Or could someone become proficient by repeating the tasks you’ve already completed, in the way that a student might take practice tests to prepare for an exam? If so, then there’s a good chance that an algorithm may someday be able to learn to do much, or all, of your job.”

Later, Ford notes, “A computer doesn’t need to replicate the entire spectrum of your intellectual capability in order to displace you from your job; it only needs to do the specific things you are paid to do.”…

❝ The “threat of a jobless future” is, of course, an old one, almost as old as technology…Each new technology displaced a new cast of workers: first knitters, then farmers, then machinists. The world as we know it today is a product of these successive waves of displacement, and of the social and artistic movements they inspired: Romanticism, socialism, progressivism, Communism.

Meanwhile, the global economy kept growing, in large part because of the new machines. As one occupation vanished, another came into being. Employment migrated from farms and mills to factories and offices to cubicles and call centers.

❝ Economic history suggests that this basic pattern will continue, and that the jobs eliminated by Watson and his ilk will be balanced by those created in enterprises yet to be imagined — but not without a good deal of suffering. If nearly half the occupations in the U.S. are “potentially automatable,” and if this could play out within “a decade or two,” then we are looking at economic disruption on an unparalleled scale. Picture the entire Industrial Revolution compressed into the life span of a beagle.

And that’s assuming history repeats itself. What if it doesn’t? What if the jobs of the future are also potentially automatable?

RTFA. Sooner or later this will be key to a national election. In every nation in the industrial world. Probably every nation, industrial or otherwise. Mechanizing most agricultural work doesn’t even require AI.

Cynic that I am I expect the United States to drift into a tidy, tightly-class-structured version of Dicken’s 19th Century industrial England. It will take Socialist-led Scandinavian nations or a later version of China’s morphing Communist-led economy to build inclusive models. American capitalism and American workers will probably continue to elect variations of Trump or Hillary depending more on ad campaigns, sloganeering, than competent economics.

11 thoughts on “How long will it be before you lose your job to a robot?

  1. Daneel Olivaw says:

    “Artificial intelligence (AI) is learning – from the real world. Nine months ago, a computer beat one of the world’s best players at one of the world’s oldest games, Go. That was the start of a new era, the era of new IT: Intelligent Technology, according to Fei-Yue Wang, a professor at the Chinese Academy of Sciences.
    “This victory stunned many in the AI field and beyond,” wrote Wang in an editorial published in IEEE/CAA Journal of Automatica Sinica (JAS), based on a speech he gave at the 30th anniversary of the Institute of Artificial Intelligence and Robotics at the Xian Jiaotong University in Xian, China. “It marked the beginning of a new era in AI… parallel intelligence.”
    Defined as the interaction between actual reality and virtual reality, parallel intelligence flips traditional AI. Rather than big, universal laws directing small amounts of data, small, complex laws guide huge data, a jump from Newton to Merton, as pointed out by Professor Wang. AlphaGo, the computer victorious against Go player Lee Sedol, played more than 30 million games with itself – more than a single, century-old person could play in their entire life. And the computer learned from every game.” (Chinese Association of Automation 12/21/16) Full text of the paper “Steps toward Parallel Intelligence” is available @ IEEE/CAA Journal of Automatica Sinica synopsis @

    • Practice makes perfect says:

      “Tic-tac-toe, checkers, chess, Go, poker. Artificial intelligence rolled over each of these games like a relentless tide. Now Google’s DeepMind is taking on the multiplayer space-war videogame StarCraft II. No one expects the robot to win anytime soon. But when it does, it will be a far greater achievement than DeepMind’s conquest of Go” The number of valid positions on a Go board is a 1 followed by 170 zeros. Researchers estimate that you’d need to add at least 100 more zeros to get into the realm of StarCraft’s complexity. “It’s a big step up,” says Oriol Vinyals, a DeepMind researcher working on StarCraft. “This game will require us to innovate in planning, memory, and how we deal with uncertainty.”

  2. Jeeves says:

    Japanese white-collar workers are already being replaced by artificial intelligence Artificial intelligence systems like IBM’s are poised to upend knowledge-based professions, like insurance and financial services, according to the Harvard Business Review, due to the fact that many jobs can be “composed of work that can be codified into standard steps and of decisions based on cleanly formatted data.” But whether that means augmenting workers’ ability to be productive, or replacing them entirely remains to be seen.

  3. Layoff says:

    “Robots are replacing managers, too” “Automation is often associated with repetitive work such as torquing a bolt or combing through contracts during an audit. Orchestra and other systems like it demonstrate that the management of that work, and even work too complex to fully automate, also involves tasks with high automation potential. According to a McKinsey analysis, 25% of even a CEO’s current job can be handled by robots, and 35% of management tasks can be automated.
    …A Bain report published in April suggested that by the end of 2027, most of a company’s activity will be automated or outsourced.”Teams will be self-managed, leading to a vast reduction in the number of traditional managers,” the report’s authors write. “Employees will have no permanent bosses, but will instead have formal mentors who help guide their careers from project to project.”

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