Marshall Van Alstyne on Platform Economics

Content Locations




      Latest Poll

      Refresh this widget
      Are you using big data and analytics for competitive advantage? (log in to vote)

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

      Most Recent Blog Posts

      Refresh this widget

      In today’s digital age, everyone wants to be an entrepreneur—to start their own business instead of working for someone else. It’s cool. It’s appealing, and according to Bill Aulet, Managing Director, of the Martin Trust Center for MIT Entrepreneurship, it takes a tremendous amount of hard work and discipline.aulet.jpg


      Entrepreneurship was a key topic discussed at the recent Second Machine Age Conference hosted by the MIT Industrial Liaison Program earlier this month. University administrators, researchers and faculty—including Aulet, and his MIT colleagues--are taking seriously the predictions in the recent book,The Second Machine Age, by MIT's Erik Brynjolfsson and Andrew McAfee. In fact, the Sloan business school, as well as other MIT centers and programs, are exploring new ways to train future leaders for the disruptions that automation and digitization are already causing. They're reexamining their fundamental educational role in fostering innovation and responding to global economic challenges--and in some cases, they want industry collaboration to jump-start the efforts.


      The Rise of Innovation-driven Enterprises

      At the conference, Fiona Murray, Associate Dean for Innovation, Sloan School, and Co-Director of the MIT Innovation Initiative, said that the “rise of the innovation-driven enterprise” means that MIT graduates need to adapt to global market shifts, to problem-solve at scale, and to help employers re-tool their organizations and policies.


      “Is this code for entrepreneurship?” she asked. Perhaps. It clearly requires people who have a “problem-solving portfolio” to show an employer before landing a job.

      Job-seekers need demonstrated project experience on the local and global level. They must initiate, and then be prepared to execute these ideas quickly, Murray said. In short, they need entrepreneurial mindsets--whether they work for themselves or for others.

      Fiona murray pic.jpg


      For his part, Aulet wants to make sure MIT grads have the right skill sets to meet demands. “Increasingly, recent graduates and other young people entering the workforce want to start companies of  their own, rather than find one to work for,” he said. “As the economic and technological landscape continues to shift in the wake of the digital revolution,” we can help them cultivate new capabilities.


      Entrepreneurship With Discipline

      The MIT Center for Entrepreneurship offers student clubs, conferences, competitions, networking events, awards, hackathons, trips, and most recently, accelerators, to keep the ideas—and the business plans--flowing. Last year, Aulet won the Adolf F. Monosson Prize for Entrepreneurial Mentoring at MIT. His latest book Disciplined Entrepreneurship (Wiley, 2013), describes 24 steps that can lead to a successful startup. Clearly, he believes that entrepreneurs are taught, not born. With a 25-year track record of launching and funding new businesses, Aulet has raised more than $100 million, creating hundreds of millions of dollars in market value in the companies he founded.


      Other universities are realizing that they have a big role to play in shaping digital leaders, too. For instance, last week the University of California last week approved a venture-capital fund of up to $250 million, called UC Ventures, that will invest in “UC research-fueled enterprises.” The purpose is to “generate attractive, risk-adjusted returns,” said UC President Janet Napolitano. She also sees this fund as “a potential vehicle for providing resources to support the basic research and talent.”


      MIT’s Murray said that designing an “innovation-centric campus” includes changing the pedagogy so that teams of students can attack unstructured problems with measurable outcomes. Murray would like businesses to become stakeholders in MIT programs to solve their real-world problems using MIT student and research resources.


      Aulet said that innovation will spur new jobs and create new markets, and he sees MIT as the prime place to think outside traditional boxes. Nevertheless, he described a gap in entrepreneurial education today--even at quality universities such as MIT.

      Overall, the spirit and desire to succeed are ready, Aulet said, but execution is lagging. He wants to further develop the skills, the support and rigor that often impede success. “Jobs will be entrepreneurial in the future,” he said. “It’s not a fad,”

      and those companies that 'get it' will learn from, and buy, the small guys, and will thrive. Others will be left behind. “Starting a business is easy,” he said, “success is much more difficult.”



      Slides from Bill Aulet’s presentation can be found here and video here.

      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.



      Gary Loveman Discusses Impediments to Analytics

      MIT CDB's Andrew McAfee talks with Caesar's CEO Gary Loveman about why businesses don't make better use of analytics, especially in a weak economy.

      The Big Data Revolution

      At the last MIT CDB conference on Big Data, Erik Brynjolfsson discussed how big data will profoundly change the way business is conducted going forward and why CEOs must get on board or be left behind.

      Andrew McAfee on Technology and the American Workforce

      On the PBS NewsHour last April, Andy McAfee spoke about how increased use of technology does play a role in the current disappointing job growth statistics.