{"id":6968,"date":"2018-06-14T15:07:25","date_gmt":"2018-06-14T19:07:25","guid":{"rendered":"https:\/\/blog.brainstation.io\/?p=6968"},"modified":"2020-05-12T13:57:15","modified_gmt":"2020-05-12T17:57:15","slug":"survival-strategies-for-the-robot-invasion","status":"publish","type":"post","link":"https:\/\/brainstation.io\/blog\/survival-strategies-for-the-robot-invasion","title":{"rendered":"Survival Strategies for the Robot Invasion"},"content":{"rendered":"

Call it what you want \u2014 Robogeddon? the Robopocalypse? \u2014 it\u2019s <\/span>now accepted<\/span>\u00a0that <\/span>automation will have a large impact on the job market<\/span><\/a>. The Brookfield Institute <\/span>estimates the number<\/span><\/a> of Canadian jobs at risk over the next two decades at 42 percent, while a widely-cited <\/span>study out of Oxford University<\/span><\/a> puts the figure for US jobs at 47 percent. <\/span><\/p>\n

Mechanical automation has been eliminating jobs for centuries\u2014at least as far back as the invention of the steam engine\u2014but artificial intelligence (AI) is qualitatively different; it rivals the capabilities of humans mind as well as their bodies \u2014 just take a look at <\/span>this recent video<\/span><\/a> of an automated voice assistant and you\u2019ll see why the Oxford study put the odds that robots will soon displace human telemarketers at 99 percent. <\/span><\/p>\n

So, just as mechanical automation gave rise to new industries and job markets (while it decimated others), the expanding frontier of artificial intelligence demands that we adapt along with it.<\/span><\/p>\n

The question is, then, how do you survive the coming robot invasion? Here are two important ideas that can help inoculate your career against automation.<\/span><\/p>\n

Understand the Limitations of AI<\/b><\/h2>\n

Elon Musk recently<\/span> called AI \u201can existential threat to humanity<\/span><\/a>, which isn\u2019t going to do much to keep people calm. He may very well be right, but it\u2019s important to understand that AI still has very real limitations (which gives you time to adapt).\u00a0<\/span><\/p>\n

“The deep learning systems we have…are remarkable in how well [they] do given the particular tasks that we give them, but they are actually quite narrow and brittle in their scope. So I think it\u2019s important to keep in context how good these systems are, and actually how bad they are too, and how long we have to go until these systems actually pose that kind of a threat,” Gil Pratt, CEO at the Toyota Institute <\/span>told TechCrunch<\/span><\/a>.<\/span><\/p>\n

The narrow scope of deep learning systems, as Pratt calls it, are partially due to the fact that AI learns from given<\/em> data. Yes, modern AI programs may complete vastly more calculations per second than their predecessors, with much larger data sets, but for now, AI still follows the directions (and data) we give it. They are also usually programmed to perform a clearly defined task, with established parameters. The system programmed to predict heart disease<\/a>, for example, will not be able to able to identify music.\u00a0<\/span><\/p>\n

AI also struggles with emotional intelligence<\/a> \u2014 the ability to read what other people are feeling or thinking and then reacting to that.\u00a0\u201cEven the most sophisticated AI technologies lack essential factors like emotional intelligence and the ability to contextualize information like human beings,\u201d Naveen Joshi, the founder and CEO of enterprise development company Allerin, wrote<\/a>.<\/p>\n

And then there’s creativity. We are, at the moment, in the early stages (or the “laughter” stage”) <\/a>of computational creativity, but that may change. In the meantime, though, there is reason to believe that creative work is safe from automation.\u00a0In fact, a<\/span>ccording to Martin Ford, futurist and author of <\/span>Rise of the Robots: Technology and the Threat of a Jobless Future<\/span><\/i>, the last jobs automation will claim are those that require \u201cgenuine creativity.\u201d\u00a0<\/span><\/p>\n

The work he’s describing depends on the kind of\u00a0 lateral thinking that comes not from taking calculated<\/i> risks, but from weighing the potential outcomes of scenarios where risks are unknowable \u2014 either due to a shortage of information, or the simple fact that nobody has ever tried them before.\u00a0Put simply, anytime we take a step into the unknown, we rely on the kind of expertise and overarching judgment that the robots have yet to master.\u00a0<\/span><\/p>\n

\u201cPeople naively believe that if you take deep learning and scale it 100 times more layers, and add 1000 times more data, a neural net will be able to do anything a human being can do, but that\u2019s just not true,\u201d Fran\u00e7ois Chollet, a researcher at Google <\/span>told Wired<\/span><\/a>. “The systems…demand huge sets of training data. [And] when a neural net is given a \u201ctransfer test\u201d\u2014 confronted with scenarios that differ from the examples used in training \u2014 it cannot contextualize the situation and frequently breaks.”<\/span><\/p>\n

All this to say, t<\/span>here\u00a0are a number of in-demand, digital skills and career paths that depend on the things that can be challenging for AI, including:\u00a0Product managers<\/a>, who must create and then manage the development process of a product that does not already exist;\u00a0data analysts, <\/a>who have to determine the appropriate parameters for analysis (before they can even discover anything from a data set), and then apply this insight to situations that often have no pre-established guidelines;\u00a0<\/span>and user experience designers<\/a> and user interface designers<\/a>, who have to find ways to improve human interaction with technology and digital properties.\u00a0 \u00a0<\/span><\/p>\n

Boost Your Data Skills<\/b><\/h2>\n

If you can’t beat them, join them. Right?<\/p>\n

\u201cI always joke that the safest job on the planet is AI researcher,\u201d Toby Walsh, an AI professor with the University of New South Wales, <\/span>told Tech Republic<\/span><\/a>. \u201cWhen we\u2019ve automated AI researchers, the machines will literally be able to do everything else by definition.\u201d<\/span><\/p>\n

So how do you get into artificial intelligence? By pursuing one foundational field that feeds into <\/span>all areas of AI development: <\/span>data science<\/span><\/a>. As we recently wrote about,\u00a0<\/span>data science is one of the fastest growing, most in-demand jobs<\/a> in technology, and with AI, it may soon become even more\u00a0indispensable.
\nFind out more about BrainStation’s Data Science courses<\/a>.\u00a0<\/em><\/p>\n

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Learn data skills to boost your career \u2013 from home!<\/p>\n

BrainStation offers Online Live Certificate Courses<\/a> in data science, data analytics, machine learning, and python programming. Attend live classes and interact with Instructors and peers from anywhere in the world.<\/p>\n

Speak to a Learning Advisor<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Automation will have a huge impact on the world of work, but it also brings great opportunities. <\/p>\n","protected":false},"author":7,"featured_media":6969,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[343,70,84],"tags":[494,481,331,405,418,495],"yoast_head":"\nSurvival strategies for the robot invasion | BrainStation Blog<\/title>\n<meta name=\"description\" content=\"Automation will have a large impact on the job market. Oxford University estimates 47 percent of US jobs are at risk. This kind of upheaval brings opportunities. 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