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Shawn Boyer served as Snagajob’s CEO from the website’s launch in early 2000, to 2013; leading the company from a start-up to national employment network. Boyer was named America’s Small Business Person of the year in 2008 by the Small Business Administration[4] and Virginia Business magazine’s Person of the Year in 2009[5].
None of this is to say that automation and AI aren’t having an important impact on the economy. But that impact is far more nuanced and limited than the doomsday forecasts suggest. A rigorous study of the impact of robots in manufacturing, agriculture, and utilities across 17 countries, for instance, found that robots did reduce the hours of lower-skilled workers—but they didn’t decrease the total hours worked by humans, and they actually boosted wages. In other words, automation may affect the kind of work humans do, but at the moment, it’s hard to see that it’s leading to a world without work. McAfee, in fact, says of his earlier public statements, “If I had to do it over again, I would put more emphasis on the way technology leads to structural changes in the economy, and less on jobs, jobs, jobs. The central phenomenon is not net job loss. It’s the shift in the kinds of jobs that are available.”
Finally, had a last round call with a Sr. Director, only last about 20 minutes and we just high level recapped the interviews and expectations. Throughout the whole process, the recruiter was amazing and made sure I was informaed and prepared for what to expect and who I was meeting with prior to each interview. He did a great job of covering mine and the companies needs ensuring a great candidate process!
A warehouse equipped with Kiva robots can handle up to four times as many orders as a similar unautomated warehouse, where workers might spend as much as 70 percent of their time walking about to retrieve goods. (Coincidentally or not, Amazon bought Kiva soon after a press report revealed that workers at one of the retailer’s giant warehouses often walked more than 10 miles a day.)
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To get some insight into Katz’s question, it is worth looking at how today’s most advanced technologies are being deployed in industry. Though these technologies have undoubtedly taken over some human jobs, finding evidence of workers being displaced by machines on a large scale is not all that easy. One reason it is difficult to pinpoint the net impact on jobs is that automation is often used to make human workers more efficient, not necessarily to replace them. Rising productivity means businesses can do the same work with fewer employees, but it can also enable the businesses to expand production with their existing workers, and even to enter new markets.
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Manual work seems to shorten one’s lifespan.[2] High rank[3] (a higher position at the pecking order) has a positive effect. Professions that cause anxiety have a direct negative impact on health and lifespan.[4] Some data is more complex to interpret due to the various reasons of long life expectancy; thus skilled professionals, employees with secure jobs and low anxiety occupants may live a long life for variant reasons.[5] The more positive characteristics one’s job is, the more likely he or she will have a longer lifespan.[6][7] Gender, country,[8] and actual (what statistics reveal, not what people believe) danger are also notable parameters.[9][10]
Of course, if automation is happening much faster today than it did in the past, then historical statistics about simple machines like the ATM would be of limited use in predicting the future. Ray Kurzweil’s book The Singularity Is Near (which, by the way, came out 12 years ago) describes the moment when a technological society hits the “knee” of an exponential growth curve, setting off an explosion of mutually reinforcing new advances. Conventional wisdom in the tech industry says that’s where we are now—that, as futurist Peter Nowak puts it, “the pace of innovation is accelerating exponentially.” Here again, though, the economic evidence tells a different story. In fact, as a recent paper by Lawrence Mishel and Josh Bivens of the Economic Policy Institute puts it, “automation, broadly defined, has actually been slower over the last 10 years or so.” And lately, the pace of microchip advancement has started to lag behind the schedule dictated by Moore’s law.
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I love that I can apply for jobs in my phone and upload more current resumes, but here is what I would change (Indeed, pay attention) • allow candidates to note that they didn’t get the job rather than “archive” it • allow candidates to permanently remove a job posting from ever being seen again…
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Take the bright-orange Kiva robot, a boon to fledgling e-commerce companies. Created and sold by Kiva Systems, a startup that was founded in 2002 and bought by Amazon for $775 million in 2012, the robots are designed to scurry across large warehouses, fetching racks of ordered goods and delivering the products to humans who package the orders. In Kiva’s large demonstration warehouse and assembly facility at its headquarters outside Boston, fleets of robots move about with seemingly endless energy: some newly assembled machines perform tests to prove they’re ready to be shipped to customers around the world, while others wait to demonstrate to a visitor how they can almost instantly respond to an electronic order and bring the desired product to a worker’s station.
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Though advances like these suggest how some aspects of work could be subject to automation, they also illustrate that humans still excel at certain tasks—for example, packaging various items together. Many of the traditional problems in robotics—such as how to teach a machine to recognize an object as, say, a chair—remain largely intractable and are especially difficult to solve when the robots are free to move about a relatively unstructured environment like a factory or office.
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“We were lucky and steadily rising productivity raised all boats for much of the 20th century,” he says. “Many people, especially economists, jumped to the conclusion that was just the way the world worked. I used to say that if we took care of productivity, everything else would take care of itself; it was the single most important economic statistic. But that’s no longer true.” He adds, “It’s one of the dirty secrets of economics: technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit.” In other words, in the race against the machine, some are likely to win while many others lose.
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What’s more, even if today’s digital technologies are holding down job creation, history suggests that it is most likely a temporary, albeit painful, shock; as workers adjust their skills and entrepreneurs create opportunities based on the new technologies, the number of jobs will rebound. That, at least, has always been the pattern. The question, then, is whether today’s computing technologies will be different, creating long-term involuntary unemployment.
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Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson’s contention really is. ­Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.
If automation were truly remaking the job market, you’d also expect to see a lot of what economists call job churn as people move from company to company and industry to industry after their jobs have been destroyed. But we’re seeing the opposite of that. According to a recent paper by Robert Atkinson and John Wu of the Information Technology and Innovation Foundation, “Levels of occupational churn in the United States are now at historic lows.” The amount of churn since 2000—an era that saw the mainstreaming of the internet and the advent of AI—has been just 38 percent of the level of churn between 1950 and 2000. And this squares with the statistics on median US job tenure, which has lengthened, not shortened, since 2000. In other words, rather than a period of enormous disruption, this has been one of surprising stability for much of the American workforce. Median job tenure today is actually similar to what it was in the 1950s—the era we think of as the pinnacle of job stability.
For that reason, Leonard says, it is easier to see how robots could work with humans than on their own in many applications. “People and robots working together can happen much more quickly than robots simply replacing humans,” he says. “That’s not going to happen in my lifetime at a massive scale. The semiautonomous taxi will still have a driver.”
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