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      Paula KleinCreated by Paula Klein on Aug 29, 2012 in Featured Content

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      Previously, I discussed a recent Pew Research report on the impact of AI, robotics and other advanced technologies on the future of jobs.  The report was based on the responses of nearly 1,900 experts to a few open-ended questions, including “Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?”  The expert’s responses to this question where divided down the middle. 


      Beyond predictions based on responses to a survey, can one develop an overall framework to help analyze these critical issues?  Along this line, I like a recent paper by MIT economist David Autor, - Polanyi’s Paradox and the Shape of Employment Growth.  The paper was presented at the annual Jackson Hole Federal Reserve symposium, a gathering of some of the world’s most prominent central bankers, finance experts and academics, where the theme this year was “Re-evaluating Labor Market Dynamics”.  The paper carefully laid out its arguments based on existing empirical evidence. Let me summarize its key points:


      Computers have made huge advances in automating many physical and cognitive human tasks, especially those tasks that can be well described by a set of rules.  But, Professor Autor argues, despite continuing advances in AI and robotics, the “challenges to substituting machines for workers in tasks requiring flexibility, judgment, and common sense remain immense.”


      Central to his argument is the concept of tacit knowledge, first introduced in the 1950s by scientist and philosopherMichael PolanyiExplicit knowledge is formal, codified, and can be readily explained to people and captured in a computer program.  Tacit knowledge, on the other hand, is the kind of knowledge we are often not aware we have, and is therefore difficult to transfer to another person, let alone to a machine.  Generally, this kind of knowledge is best transmitted through personal interactions and practical experiences.  Everyday examples include speaking a language, riding a bike, driving a car, and easily recognizing many different objects and animals.


      “We can know more than we can tell,” noted Polanyi in what Autor refers to as Polanyi’s paradox.  This seeming paradox succinctly captures the fact that we tacitly know a lot about the way the world works, yet are not able to explicitly describe this knowledge.


      The paper builds on Autor’s earlier research on the polarization of job opportunities in the US, where he examined the changing dynamics of the US labor market by looking at three different segments:


      • High-skill, high-wage jobs, where opportunities have significantly expanded, with the earnings of the college educated workers needed to fill such jobs rising steadily over the past thirty years;
      • Low-skill, low-wage jobs, which have also been expanding, while their wage growth, particularly since 2000, has been flat to negative;
      • Mid-skill, mid-wage jobs which have been declining, while their wage growth has also declined over the years, especially since 2000.
      • Many mid-skill activities involve relatively routine tasks, that is, tasks or processes that can be well described by a set of rules.  They include blue-collar manual activities such as manufacturing and other forms of production, as well as white-collar, information-based activities like accounting, record keeping, dealing with simple customer service questions, and many kinds of administrative tasks.  “Because the core tasks of these occupations follow precise, well understood procedures, they are increasingly codified in computer software and performed by machines,” writes Autor.  “This force has led to a substantial decline in employment in clerical, administrative support and, to a lesser degree, production and operative employment.”


      To continue reading the full blog, see my post of September 9, here


      David Autor also spoke about Polany's Paradox at the recent MIT ILP Second Machine Age conference. View his slides and a video of his presentation here.


      As we enter the Second Machine Age, the power of computers will be pushed far beyond current boundaries and limitations. As a result, we will see just how much automation can complement-- and how much it replaces--human labor in countless industries and businesses.


      That was one takeaway offered by MIT Professor, CDB Director and IDE co-director, Erik Brynjolfsson, at The Second Machine Age conference hosted by the MIT Industrial Liaison Program September 10-11. Whether to allay fears or speaking from a pragmatic perspective, Brynjolfsson and other MIT speakers said that machines and humans can co-exist and complement each other in work environments to maximize productivity—at least for now. Implicit is the uncomfortable realization that innumerable jobs will be eliminated outright as robotic technologies march forward.


      In his opening remarks, Brynjolfsson expanded on the premise of the book, The Second Machine Age, which he co-authored with MIT’s Andrew McAfee. What’s different now versus the past is the rapid-fire pace of change and the widening scale and scope of automation, he said. The impact already taking place on society is huge and growing.


      Rapid-fire Machine Advances

      In the past decade, for instance, machines have mastered fine motor control, language and communications, pattern matching and other tasks that many expected to lag for many years to come. Advances in driverless cars, voice-activated Smartphones and physical robots, sold at low cost, are all outpacing predictions. Machine-intelligent robots able to solve problems and learn in unstructured environments are proving their value in call centers, medical diagnostics and even in legal, HR, academic and financial settings, Brynjolfsson said.


      Later in the day, Assistant Professors Daniela Rus and Julie Shah, both working at the MIT CSAIL AI Center for Robotics, bolstered this point by demonstrating how personal robots can be programmed for individual tasks now performed by humans on the factory floor. Each explained that these technologies are ready to leave the lab and enter mainstream business environments to work alongside human peers.


      What’s it all mean for the economy? As Brynjolfsson has outlined previously, several key implications for productivity, labor and wages are unfolding. He notes that businesses are not generally keeping pace with technical advances and the ubiquitous proliferation of mobile apps have already made products such as answering machine, cameras and navigation systems nearly obsolete.


      Huge Economic Disparities

      U.S. GDP is at a record high, and profits and investment are all rising. Clearly, in the digital economy the overall economic “pie is bigger,” he said, yet employment and median income are lower and falling. “People are not sharing in the pie equally, and many are worse off.” Brynjolfsson and McAfee call this a “great decoupling” of GDP, productivity, employment and income. Economic progress is biased—and there will be winners and losers.


      The disparities and polarization between high and low-skilled labor will widen, he said; “the rising tide no longer lifts all boats.” In addition, mid-level skills—clerical and managerial jobs--are being hard hit too. For now, low-end service jobs are still needed, though that will change, too. Moreover, businesses—not workers-- gain when processes are automated and profits go up.


      What’s needed to address these trends, Brynjolfsson contends, are new business models where skills are reinvented and technology is merely a tool to shape the future. “Technology is not destiny, we shape our destiny,” he said. Fiona Murray, Associate Dean for Innovation at MIT Sloan, spoke specifically about preparing MIT graduates for the new work environment and partnering with businesses to meet their demands.


      Throughout the day, MIT economists, technologists, entrepreneurs and industry partners offered approaches and ways to re-tool the workforce and organizations to meet these challenges.


      What are your thoughts and solutions? How rapidly is automation disrupting your business? Share your comments with our community.



      Video of Erik Brynjolfsson’s talk can be found here; the slide presentation can be found here

      We will be summarizing other speaker presentations in upcoming blogs. Meanwhile, select slides and video can be found on this agenda here.


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