2016-10-07


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Increasing numbers of teachers are finding themselves in a situation not dissimilar to that facing many cab drivers today.



The following is an excerpt from the new book The Uberfication of the University by Gary Hall (University of Minnesota Press, 2016):

At first the 2008 financial crisis looked as if it was going to constitute a major threat to the long-term viability of neoliberalism. Viewed from our current vantage point, however, it seems merely to have given the champions of the free market an opportunity to carry out with increased intensity their program of privatization, deregulation, and reduction to a minimum of the state, public sector, and welfare system. The result is a condition we can describe as postwelfare capitalism.

My book, The Uberfication of the University, explores what neoliberalism’s further weakening of the social is likely to mean for the future organization of labor by examining data and information companies associated with the emergence of the corporate sharing economy. It focuses on the sharing economy because it is here that the implications for workers of such a shift to a postwelfare capitalist society are most apparent today. This is a society in which we are encouraged to become not just what Michel Foucault calls entrepreneurs of the self but micro-entrepreneurs of the self, acting as if we are our own, precarious, freelance microenterprises in a context in which we are being steadily deprived of employment rights, public services, and welfare support. Witness the description one futurologist gives of how the nature of work will change, given that 30 to 80 percent of all jobs are predicted to disappear in the next twenty years as a result of developments in automation and advanced robotics: “You might be driving Uber part of the day, renting out your spare bedroom on Airbnb a little bit, renting out space in your closet as storage for Amazon or housing the drone that does delivery for Amazon.”

Talk about being careful what you wish for: a recent survey of university vice-chancellors in the United Kingdom identifies a number of areas of innovation with the potential to reshape higher education. Among them are “uses of student data analytics for personalized services” (the number one innovation priority for 90 percent of vice-chancellors); “uses of technology to transform learning experiences” (massive open online courses [MOOCs]; mobile virtual learning environments [VLEs]; “anytime-anywhere learning” (leading to the demise of lectures and timetables); and “student-driven flexible study modes” (“multiple entry points” into programs, bringing about an end to the traditional academic year). Responding to this survey, an editorial in the academic press laments that “the UK has world-leading research universities, but what it doesn’t have is a higher education equivalent of Amazon or Google, with global reach and an aggressive online strategy.” Yet one wonders whether any of those proclaiming the merits of such disruptive innovation have ever stopped to consider what a higher education institution emulating the expansionist ambitions of U.S. companies like Amazon and Google would actually mean for those currently employed in universities.

We can see the impact such aggressive, global, for-profit technology companies have on the organization of labor by looking at information and data analytics businesses associated with the sharing economy. Emerging from the mid-2000s onward, the sharing economy is a socioeconomic ecosystem that supplies individuals with information that makes access to things like ridesharing and sofa surfing possible on a more efficient, expanded basis. Indeed, because of the emphasis that is placed on the cooperative sharing and renting of preowned and unused goods, the activities and services of the sharing economy are frequently held as being very different from, or as even as offering an alternative to, those that are provided through private, state, or public channels. As such, the sharing economy is portrayed as a means of bringing community values back into the ways in which people consume. It is also said to help address environmental issues resulting from the depletion of the planet’s resources, for example, by reducing the carbon footprint of transport. Yet the sharing economy is just part of a much larger socioeconomic ecosystem, one that is dominated by the use of computing and satellite technology to coordinate workforces and create global transnational supply chains and that enables just-in-time manufacturing through the production of low-wage labor and the exploitation of outsourced workers. Given this, it is almost as if the sharing economy has been devised to take the edge off some of the harsher aspects of life in advanced, postindustrial capitalist society, including those that have been generated in the name of austerity: unemployment, precarity, increasing income inequality, large discrepancies in property ownership, high levels of debt, and low levels of class mobility.

In the interests of capital, the for-profit sharing economy can therefore be seen to be involved in the process whereby each of us is being transformed into a dispersed, atomized, precarious, freelance microentrepreneur. That said, concerns about the sharing economy are all too easy to push to the back of our minds when we’re trying to find an inexpensive place to stay for a weekend break or calling a taxi to take us home from a friend’s place late at night. Many women especially consider Uber to be safer than a minicab, with its unknown driver (although there have been complaints that the company could do more to ensure the safety of female passengers). Uber also has the advantage of costing less than a licensed taxi and being easier and more convenient than both. With Uber you can track your vehicle as it approaches in real time and so be sure you are getting into the right one. Others appreciate the freedom from having to deal with cash that Uber’s frictionless digital payment system provides. It is only when we begin to think about these information and data management intermediaries from the point of view of a worker rather than a user, and consider their potential to disrupt our own sphere of employment—with the associated consequences for our job security, income, sick pay, retirement benefits, pensions, and, as we shall see, subjectivities—that the full implications of the shift to a socially weakened form of capitalism they are helping to enact are really brought home. So what is the potential effect of this transformation in the organization of labor on higher education?

In April 2015, LinkedIn, the social networking platform for professionals based in Mountain View, California, spent £1.5 billion purchasing Lynda.com (also based in California), a supplier of online consumer-focused courses. Although it does not address the sharing economy specifically, a report of this deal published shortly afterward in the U.S. Chronicle of Higher Education under the title of “How LinkedIn’s Latest Move May Matter to Colleges” was quick to draw attention to its potential implications for higher education. Of course, with its University Pages and University Rankings Based on Career Outcomes, LinkedIn already has enough data to be able to provide the kind of detailed analysis of which institutions and courses are launching graduates into which jobs and long-term career trajectories that no single traditional university can hope to match—and that’s before its purchase of Lynda.com. But what the piece in the Chronicle made clear is that, with LinkedIn’s imminent transition into being both a social network and an actual provider of education, such data could easily be used to develop a successful information and data intermediary business model for higher education: if not next year, then certainly in the near future, and if not by LinkedIn, then by some other for-profit technology company (Uber or Academia.edu, say, the latter having a business plan that depends on its ability to exploit data flows related to research). Such a model would be based on providing “transparent” information on a finely grained basis to employers, students, funding agencies, governments, and policy makers. This information would indicate which of the courses, classes, and possibly even teachers on any such educational “sharing economy” platform are better at enabling students from a given background to obtain a particular academic degree classification or other educational credential or qualification, make the successful transition to a desirable job or career, reach the top of a given profession in a particular town, city, or country, and so achieve a high level of job satisfaction, security, salary, income, and earning capacity over a specific period or even a lifetime. You know the kind of thing: if you liked reading this book by this author, then you might also like taking this undergraduate course at X college, and this master’s course at Y, and applying for this starter post at company Z.

It doesn’t end there. The Chronicle article also detailed how, in 2014, LinkedIn bought a company called Bright. Bright has developed algorithms enabling it to match posts with applicants according to the latters’ particular achievements, competencies, and skill sets. And it wouldn’t be too difficult for a for-profit business, with the kind of data LinkedIn now has the potential to gather, to do much the same for employers and students—right down to the level of their salary expectations, extracurricular activities, “likes,” or even reputational standing and degree of trustworthiness. This business could charge a fee for doing so, just as online dating agencies make a profit from introducing people with compatible personalities and interests as deduced by algorithms. It could then charge a further fee for making this ultra-detailed information and data available on a live basis in real time—something that would no doubt be highly desirable in today’s “flexible economy,” where many employers want to be able to draw from a pool of part-time, hourly paid, zero-hours and no-contract workers who are available “on tap,” often at extremely short notice. Moreover, feeding all the data gathered back into the system would mean the courses, curricula, and class content of any such educational data and information intermediary, along with their cost, could be continuously refined and so made highly responsive to student and employer needs at local, national, and international levels. More ominously still, given that it would be able to control the platform, software, data, and associated ecosystem, it is clear that such a platform capitalist higher education business would also have the power to decide who could be most easily seen and found in any such alternative market for education, much as Google does with its page ranking. (In April 2015, the European commission decided that Google has a case to answer regarding the possible abuse of its dominance of search through “systematically” awarding greater prominence to its own ads.)

Perhaps understandably, following all the furor over MOOCs, the Chronicle’s analysis of LinkedIn’s acquisition of Lynda.com shied away from arriving at any overly pessimistic conclusions as to what all this may mean for higher education and its system of certification and credentialing. Nevertheless, if a company like LinkedIn made the decision to provide this level of finely grained information and data for its own unbundled, relatively inexpensive online courses (and perhaps any other nontraditional for-profit education providers that sign up with them), but not for those offered by its more expensive market competitors in the public, nonprofit sector, it would surely have the potential to be at least as disruptive as Coursera, Udacity, FutureLearn, and others have proven to be to date, if not considerably more so. For the kind of information about degrees and student final destinations, and ability to react to market changes any traditional bricks-and-mortar institution is capable of providing on its own would appear extremely unsophisticated, limited, and slow to compile by comparison. And lest the adoption by a for-profit sharing economy business of such an aggressive stance toward public universities seems unlikely, it is worth noting that Google maintains its dominance of search in much the same way. In the words of its chief research guru, Peter Norvig, the reason Google has a 90 to 95 percent share of the European market for search is not because it has better algorithms than Yahoo! and Bing but rather “it just has more data.” Indeed, one of the great myths about neoliberalism is that it strives to create competition on an open market. Yet, as the venture capitalist Peter Thiel, cofounder of PayPal and early Facebook investor, emphasizes in his book Zero to One, what neoliberal businesses actually want is to be a monopoly: to be so dominant in their areas of operation that they in fact escape the competition and become a market of one. “Competition,” as Thiel puts it elsewhere, “is for losers.” As if to testify to this belief, LinkedIn was itself bought by Microsoft in mid-2016 for $26.2 billion.

Of course, as a consequence of neoliberalism’s program of privatization, deregulation, reduction to a minimum of the public sector, and insistence that even publicly funded universities operate like businesses and embrace a lot of the same practices and value systems as for-profit corporations (despite that many are registered charities and therefore have education, not profit generation, as their primary function), large numbers of those who work in higher education already have temporary, fixed-term, part-time, hourly paid, zero-hour, and other forms of contingent positions that make it difficult for them to offer much by way of resistance to the erosion of their academic freedom and economic security. According to the American Federation of Teachers, “76% of the total faculty workforce is now in non-permanent posts and 70% of these are part time.” Meanwhile a report by the University and College Union (UCU) finds that “54% of all academic staff, and 49% of teaching staff in UK universities are employed on insecure contracts,” with a UCU survey of twenty-five hundred casualized staff identifying one-third of those in universities as already experiencing difficulty paying household bills, while as many as one-fifth have problems finding enough money to buy food. Yet if something along the lines of the preceding scenario regarding the development of a successful information and data intermediary business model for higher education does come to pass, it will without doubt have the effect of further disrupting the public, nonprofit university system—only this time by means of a profit-driven company operating according to a postwelfare capitalist philosophy, just as Uber is currently disrupting state-regulated taxi companies and Airbnb the state-regulated hotel industry. Increasing numbers of university workers will thus find themselves in a situation not dissimilar to that facing many cab drivers today. Instead of operating in a sector regulated by the state, they will have little choice but to sell their cheap and easy-to-access courses to whoever is prepared to pay for them in the “alternative” sharing economy education market created by platform capitalism. They too will become atomized, freelance microentrepreneurs in business for themselves. And as such, they will experience all the problems of deprofessionalization, precarity (in the sense of being unable to control or even anticipate their own future), and continuous performance monitoring by networked surveillance technologies that such an economy brings. Is this what vice-chancellors and university presidents actually want?

Excerpt from The Uberfication of the University by Gary Hall (University of Minnesota Press, 2016, footnotes omitted). www.upress.umn.edu

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