Chapter 5 Ed Tech Criticism

The Ed Tech Rapture

Singler (2017) highlighted how much of the language of those who promote artificial intelligence has religious connotations: “There are AI ‘oracles’ and technology ‘evangelists’ of a future that’s yet to come, plus plenty of loose talk about angels, gods and the apocalypse.” Watters (2013b) also wrote about myth and faith in Silicon Valley, particularly with regard to the theory of disruption, which has a religious tone: “The structure to this sort of narrative is certainly a well-known and oft-told one in folklore—in tales of both a religious and secular sort. Doom. Suffering. Change. Then paradise.” Christensen’s (1997) disruption theory demands the end of one industry, which is replaced by another, and this can be viewed as an exodus to a new promised land led by a technology visionary. People often self-identify or are labelled by others as “evangelists” for a particular technology. And though this might be partly self-mocking, it aligns with the rapture view of ed tech. According to the Oxford English Dictionary (2021), an evangelist, after all, is someone described as “a zealous advocate of a cause or promulgator of a doctrine” or “one who evangelizes or brings the gospel to (a heathen nation, etc.).” Those who do not share the vision of the particular technology are the “heathens” in this view. There is little room for doubt or nuance in an evangelist’s perspective. Visions of ed tech futures are often pitched with resonances to religious beliefs about cataclysm and salvation.

The apocalypse is a recurring theme across many religions. The Encyclopaedia Britannica (2006) states that “arising in Zoroastrianism, an Iranian religion founded by the 6th-century-BC prophet Zoroaster, apocalypticism was developed more fully in Judaic, Christian, and Islamic eschatological speculation and movements.” A related concept is that of eschatology, concerned with the end of history and the judgment of humanity. Although versions occur in most of the main religions, apocalypticism also features in many mythologies, such as the Norse Ragnorak. Often allied with eschatology is an essential offer of salvation for believers. The Christian rapture in which Christ returns to the Earth at the apocalypse and takes his believers with him is one example, particularly prevalent in the United States. But it can also be seen in popular culture, with films such as Avengers Endgame and Armageddon and novels such as The Hunger Games. With extreme climate change and nuclear war distinct possibilities, a realistic form of apocalypse hangs over much of the modern era. Netflix has invested heavily in series and films set in a post-apocalyptic world (Stone, 2017), suggesting that the company knows what its viewers want. The popularity and universality across different religions, mythologies, and media indicate that apocalypse and survival are ideas that appeal in some deep sense to the human psyche. It is perhaps not hard to see why—most people share the need to belong (identity theory suggests that we define who we are by the groups that we associate with) and the desire to feel exceptional. And what stronger sense of belonging and exceptionality is there than to be one of the saved come the end of the world? That is a powerful offer. Whether that salvation comes from the pursuance of a good life determined by religious beliefs or by being well prepared with a nuclear bunker is irrelevant in some sense—the psychological appeal derives from being exceptional.

The language and concepts of the apocalypse are thus deeply rooted in the modern world, particularly in a North American context. And this apocalyptic vein is often present in ed tech futurist visions. The basic premise is that some cataclysmic change is coming that will be catastrophic for the current model of education. Here are some examples for education:

• AI will make teachers redundant: Kai-Fu Lee, a former president of Google China, says that in education he would like to “make everything go away and start from scratch” (quoted in Corcoran, 2018). He proposes a teacher-student ratio of 1:1,000. Seldon and Abidoye (2018) talk of a fourth education revolution dominated by artificial intelligence.
• Robots will transform all jobs: related to the above, automation is set to take over a lot of jobs, and higher education needs to respond to the resultant society and economy (e.g., Ford, 2015).
• Universities will cease to exist: MOOC founder Sebastian Thrun (Leckart, 2012) famously predicted that by 2062 there will be only 10 global education providers, and his hope that his MOOC company Udacity will be one of them can be interpreted in eschatological terms, the end of days for universities. Similarly, Rigg (2014) asked “can universities survive the digital age?” as if it is an external extinction event rather than something that universities themselves have shaped considerably.
• Everyone will become an autodidact: Facebook’s Mark Zuckerberg has a vision of “a billion students across the world . . . able to learn on their own” (quoted in Wang, 2017). Mitra (2005) talked of self-organized learning, with his hole-in-the-wall project, in which children spontaneously learned using a computer; however, when others tried to replicate his experiments, they did not find the same results (e.g., Arora, 2010).

This is not to suggest that these claims are without some element of truth—automation will undoubtedly have impacts on jobs and the economy, and education will need to respond to that social change. Such claims form the context within which ed tech operates. Much of the language of ed tech futurists is couched in catastrophic terms: “revolution,” “tsunami,” “disruption,” “fundamental change,” “irrevocable damage.” It also transpires that many Silicon Valley billionaires are investing in “some level of ‘apocalypse insurance,’ like an underground bunker” (Robinson, 2017). So, the apocalypse, it seems, is never far from their minds.

So, given some form of impending catastrophe, the rapture-type offer becomes crucial. By becoming a believer—in a start-up, a particular technology, a concept, a new labour force model, the AI singularity—you (and your institution) can be saved. But it is always a time-limited offer, since any delay is seen as fatal, and belief has to be total. When Thrun made his rash prediction about a limited number of global education providers, the unstated message was that, if others wished to survive, they should join him. Prensky (2016, p. 7), who invented the flawed metaphor of digital natives, says in his book that he is setting out an educational vision of “how the fragmented elements of a future vision are now coming together, allowing people who want fundamental change to finally say, ‘I don’t choose the educational vision of the past (and today); I choose the educational vision of tomorrow.’” What he means here is largely the acceptance of his vision of the future.

One can contrast this ed tech rapture with a more pragmatic approach. For example, the Open Science Laboratory at the Open University brings together a number of different online lab tools, such as a virtual microscope, virtual field trips, and live lab demonstrations with interactive elements. All of these tools—developed based upon research and feedback—benefit distance education students. This type of ed tech is not pitched as the end of education as we know it. It is focused on students’ needs and in use now without reference to an imagined future. Similarly, much of the work on open textbooks is focused on direct benefits to students. These books, openly licensed so that they can be adapted, and the digital versions are free. I will show later how they can facilitate open approaches in pedagogy, but much of the language and research on them is based upon pragmatic benefits. For example, Jhangiani and Jhangiani (2017) conclude a study of open textbook adoption in Canada by stating that “students assigned open textbooks perceive these resources to be of generally high quality and value [because of] the cost savings, immediate access, portability, and other benefits they confer.” Similarly, Hilton (2016, p. 573) compared open textbook adoptions and concluded that “results across multiple studies indicate that students generally achieve the same learning outcomes when OERs (Open Educational Resources) are utilized and simultaneously save significant amounts of money.” These are not claims couched in a mythical future that require revolution to be realized but identifiable and realistic benefits for learners. They are, in short, useful.

This is perhaps a meaningful distinction to make when encountering media for ed tech. If you are uncomfortable reading an article and detect grandiose claims or a desire for fundamental change across the global education sector, it is worth asking if you are being given a “rapture” pitch or a “useful” pitch. Ironically, COVID-19, an actual crisis with connotations of an apocalypse, has revealed that it is the useful framing that we need most.

Education Is Broken

Related to the type of language seen with the ed tech rapture, a common phrase that one encounters is that in some way “education is broken.” This might not seem like an analogy in the more complex mapping form, but it is a type of metaphor. Education is cast as an entity that can be broken, and this brings with it a number of connotations. First, there is a finality about the term. Consider other terms that could be used, themselves all metaphorical—one could describe education as “evolving,” “adapting,” “growing,” “ailing,” “besieged,” “sustaining,” or “struggling.” The term “broken” implies that it is not undergoing a process but has reached a final stage. Second, use of that term suggests that something broken can be fixed. However, this is no minor repair; it is usually cast as a major overhaul by an external agent. And third, it implies judgment. With the exception of glass ceilings and piñatas, there are few things that we prefer when they are broken.

Here are some examples of the education is broken metaphor.

• Sal Khan, founder of the Khan Academy, speaking of the current model of education, stated that “the real problem is that the process is broken” (quoted in Adams, 2013).
• Campbell Brown, a former CNN host, said of her involvement with an educational website that her conversations with others “have a common starting point that the system is broken” (quoted in Daspin, 2015).
• Vermeulen (2019) began an article by stating bluntly that “education is broken. But I still believe it matters.”
• Max Ventilla, the founder of an educational start-up, AltSchool, which aimed to fix education (and recently closed its schools and pivoted to become Altitude Learning), realized that he could change education because “this thing that I want personally actually calls out for the kind of solution, like a platform solution, a systemic solution, a network solution, that I kind of know how to build” (quoted in Batelle, 2016).
• Sebastian Thrun declared that “education is broken. Face it. It is so broken at so many ends, it requires a little bit of Silicon Valley magic” (quoted in Wolfson, 2013).
• An influential report from the Institute for Public Policy Research entitled “An Avalanche Is Coming” claimed that “the models of higher education that marched triumphantly across the globe in the second half of the 20th century are broken” (Barber et al., 2013).

This is not to argue that many of the criticisms that people make are not valid or that their solutions have no credit. But the aim here is to explore how the metaphorical language and framing shape the discourse. There are three problems associated with the education is broken metaphor, I would argue.

1. It is simplistic: saying that something is broken avoids having to do any subtle investigation and does not permit further analysis. Similarly, technology advocates are prone to declare that something is “dead” when in fact technologies rarely die; rather, they lose their monopolies and become specialized, adapted, mutated. One can think of radio or books in this respect and how they have changed with the arrival of the networked world.
2. It frames technological change as a crisis and not an opportunity. Once a broken metaphor is adopted, a whole set of language accompanies it and frames it as a problem to be fixed. This is in contrast to language framed in terms of opportunity, in which some improvements move forward, whereas other initiatives do not.
3. It is used for gain: those who propose that education is broken usually have something to gain from the acceptance of this idea. Either they want to sell a solution that will mend it (after all, something broken needs to be fixed), or they want to gain prestige by being seen as someone who can at least see the means of fixing it.

If one adopts the broken metaphor, then there is the implication that one wants to start afresh, which is rarely beneficial. Instead, one might want to instigate change in a sector of higher education, for example by taking an existing course and adding some new approaches to it, campaigning for open access to all historical archives, exploring new forms of assessment, finding ways of making courses and their associated pedagogies more accessible and open, and so on. These are opportunities to build upon an approach that already does many things well. Such an approach does not dismiss the roles of those in the sector who understand it and have worked hard to realize outcomes for students. This suggests another reservation regarding the broken metaphor: it is fundamentally elitist. The underlying message is that those already in the sector do not understand technology or care about students. They are seen as being embedded in an old-fashioned way of thinking that is hopelessly broken, and this is the underlying tone of many who propose solutions to fix education. For instance, Forbes published a “30 under 30” list of significant people in education for 2020, and not one of them was a college or university educator; they were all founders or entrepreneurs of start-up companies (Howard et al., 2020). The implication is clear: only those outside traditional education can effect change.

Many of education’s problems are not of its making; they arise from wider social issues, such as how higher education is funded, how a sector behaves when it is forced to operate in a market, how economic and social contexts for graduates are changing, and so on. There is no easy solution to any of the issues facing higher education, and I would advocate suspicion of any simple solution proposed for the varied and messy domain of education. But many of those involved in education are working on specific problems with specific approaches. Education as a whole is not a problem waiting to be fixed but a set of issues, problems, and opportunities to be addressed.

Digital Natives

There is a horror film called The Human Centipede (if you have previously not heard of it, I apologize for bringing it to your attention). I have no desire to see the film, but the mere idea that it contains has given me disturbed nights. In some respects, the director deserves credit for this—he has conceived the idea of a human centipede and then put it into a film, which you do not even need to see to give you nightmares. This demonstrates that bad ideas have their own power. Which brings me to the concept of digital natives. I include it in this book as a counterexample of the benefit of metaphors in ed tech. It is a powerful metaphor that did much to shape thinking about ed tech, even though it is almost entirely without basis.

The idea was proposed by Prensky (2001). He claimed in his article that “our students have changed radically. Today’s students are no longer the people our educational system was designed to teach.” The metaphor that he applied was that of natives and immigrants. The students who have grown up in a digital world are “native speakers of the digital language of computers, video games and the Internet.” They stand in contrast to “those of us who were not born into the digital world but have, at some later point in our lives, become fascinated by and adopted many or most aspects of the new technology;[we] are, and always will be compared to them, Digital Immigrants.” Such people retain “accents” of their pasts.

This was a popular view with the arrival of the internet, and Prensky was not alone in promoting the “otherness” of young people. Oblinger and Oblinger (2005) claimed as one of the defining characteristics of the net generation that “they want parameters, rules, priorities, and procedures. . . . [T]hey think of the world as scheduled and someone must have the agenda. As a result, they like to know what it will take to achieve a goal. Their preference is for structure rather than ambiguity.” This prompted a question about whether previous generations exhibited a preference for ambiguity and lack of structure. Similarly, Tapscott (1998, p. 11), referring to education, declared that “there is growing appreciation that the old approach is ill-suited to the intellectual, social, motivational, and emotional needs of the new generation.”

Bennett et al. (2008), among others, performed a thorough job of dismissing the claims associated with digital natives. They assessed the evidence in the following areas.

• Information technology use and skills among young people: although there was evidence that many young people were adept at using technology, it was not uniform and often not advanced. They concluded that “there is as much variation within the digital native generation as between the generations” (p. 779).
• Distinctive digital native learning styles and preferences: multitasking might not be beneficial, and there was evidence that the type of interaction in video games did not transfer to learning. In addition, learning style itself is a metaphor almost as harmful as that of digital natives (Willingham et al., 2015), so any call to it in validating a theory is suspect.
• Fundamental changes in education: there was little evidence of the disaffection among students claimed by commentators and doubt about whether many of the skills often proclaimed (e.g., looking up cheat codes) led to deeper learning.

Jones and Shao (2011, p. 1) reported similar findings: “Students do not naturally make extensive use of many of the most discussed new technologies such as Blogs, Wikis and 3D Virtual Worlds.” They concluded that “advice derived from generational arguments should not be used by government and government agencies to promote changes in university structure designed to accommodate a Net Generation of Digital Natives.”

Prensky (2011) later claimed that the metaphor of digital natives was intended only as such and that people took it too literally, although he built a considerable career upon it, so maybe he did little to dampen that enthusiasm. He is undoubtedly correct, though, that it is a metaphor, and as such it demonstrates the problem of approaching metaphors with insufficient caution or that some are just plain wrong. It was an appealing metaphor, particularly when we were in the first grip of the digital revolution and so much seemed to be different. As with Mitra’s hole in the wall (2005), it appealed to a sense of the magic of technology. It seemed that one only had to give every child an iPad, then get out of the way, and educational problems would be solved.

It would be an interesting exercise to calculate how much money has been spent on the idea of digital natives over the years. There have been innumerable keynotes from people proclaiming to be experts in the area; schools, universities, and companies have hired consultants to advise them on how to deal with this strange new breed; there are extensive publications on the subject; funders have paid for research projects examining whether it has existed or not; and last, and by no means least, there are all those essays, theses, and dissertations that take it almost as a given fact. A mini-industry developed centred on a fashionable idea that under examination had no real basis in evidence.

It is a shame because the overapplication of the idea has led to a distinct reaction against any suspicion of it. There might well be some subtle attitudinal differences between people who have never known a pre-digital age; however, as Helsper and Eynon (2010) report from an analysis of technology use, age was not the only factor, and how technology was used was also influenced by factors such as location, socio-economic status, gender, type of technology, and context. The generational obsession has continued with the media focus on millennials, who have been blamed for killing everything from napkins to marriage (Donvito, 2021). The more interesting aspect is how technology made society different for everyone rather than an age-based split. Highlighting changes in the education system made possible by this new technological context were positive but wrapping them up as a generational shift has ultimately simplified the argument.

Part of the problem was that people did not consciously frame digital natives as a metaphor. Perhaps it was the sort of playful metaphor that one would put in a blog post, while acknowledging that it was not rooted in evidence and intended only as a way of thinking about current changes, but this caution was not applied to it. As a metaphor, it carries a number of connotations.

• The difference between natives and immigrants is insurmountable (this also reinforces many racist ideas about real “natives” and “immigrants”).
• Being a native is superior.
• Technology use is natural and does not require any structure.
• Technology use leads to different modes of thinking and preferences in education.
• Education is fundamentally shaped by technology.

These are all considerable assumptions to make, and had it been more explicitly framed as a metaphor more people might have questioned these elements. Instead, it became accepted as a fact. Even now, when it has been widely dismissed, we see varieties of it popping up in rhetoric about the use of technology, like playing a game of bad concept whack-a-mole. Let digital natives then stand as a warning about the power of bad metaphors.

Uber for Education

There is a strange tendency in writing about technology to take any successful business and view it as an acid that burns through everything. It seems to be the most accessible metaphor, for much of ed tech is another technology company, and this is seen particularly when applying new models to education. We have had Netflix for education (Anderson, 2019), the AirBnB of education (Smooke, 2018), and inevitably Uber for education. This is in addition to the more literal instances of companies such as Amazon, Facebook, and Google and their specific educational programs.

So, although in this section I focus on Uber, it can stand for any of the metaphors that take a current technological success story and apply it to education. Kundukulam (2017) argues that Uber models are proliferating across many sectors, for example dog walking, furniture removals, even private jets. Therefore, it could be applicable to education, he asserts, suggesting that Uber’s essential offering is as follows.

• Two-sided platform that matches latent supply with unmet demand: teaching can be done by anyone with certain expertise and on a wider range of subjects than the current curriculum.
• On-demand, mobile access: this is what you want when you want it.
• High-quality, community-rated suppliers: the rating of teachers allows poor ones to be filtered out.

There was the inevitable start-up (InstaEDU) that aimed to offer on-demand tutorial support “just like calling an Uber”; students are “in control of when and how they get the support they need and are assured of the high quality of the service” (Rogers, 2014).

Similarly, Burke (2015) reports an epiphany while getting an Uber and concludes that, “in response to Uber, wise government officials like those in Portsmouth, New Hampshire are eliminating outdated regulations like taxi medallions and price controls. If we want to see more innovative educational options that benefit both consumers and providers, such as teacher-led schools, then we must also liberate learning.”

Burke’s argument is one of unbundling education into distinct components. Unbundling education refers to “the process of disaggregating educational provision into its component parts, very often with external actors” (Czerniewicz, 2018). A learner can get content, one-to-one tuition, assessment, and recognition from different providers. The idea has occurred often in higher education since the arrival of the internet. Reporting on the Unbundled University project, which examined the extent to which it is occurring, Czerniewicz found different forms of both unbundling and rebundling taking place within and outside the university. She posed the following questions that we should ask about unbundling approaches: “Who’s doing this monetizing? Why? For what purpose? Which types of knowledge are being valued? What is considered ‘valuable’ in higher education? What is the meaning of the academic ‘brand’? Who is regulating and shaping those markets? And why is this all so urgent now?”

Woolf University, which sought to combine several of the models, has been hailed as the “world’s first blockchain university,” describing itself as “Uber for students, AirBnB for Professors” (Davies, 2018). The announcement of the start-up led to excited headlines such as “The University Is Dead, Long Live the University” (Hamilton, 2019). However, by 2019, the university had quietly dropped the blockchain tag (Gerard, 2019). Then it seemed to become rather quiet, and at the time of writing in 2021 its website seemed to offer courses from its own Ambrose College and a couple of other institutions. Courses cost about $1,500 each and offered personalized tuition with weekly video calls from a tutor (attempting to replicate the Oxbridge seminar model). There were no student testimonials, and Woolf University had not tweeted anything since October 2020, indicating that this model had gone the way of so many others. Transforming start-ups into viable businesses is a notoriously difficult task, of course, so the failure of some of them should be no surprise. However, maybe these ones have failed to have the impact anticipated by some because Uber for education is a fundamentally flawed idea.

One issue with such metaphors is that their proposers are uncritical of the original models. If you are suggesting a radical new model for education, then you don’t want to consider all of the problems inherent in it, since it is meant to be a solution to the problems of education and should not have its own set of problems. Of course, there were considerable issues with Uber in its original form. When it filed paperwork for an initial public offering, it revealed a number of problems with Uber’s business and operating models (Wong, 2019). These problems included criticisms of aggressive workplace culture, legal disputes, and poor treatment of drivers, which makes them ineligible for benefits, minimum wage, overtime, and worker’s compensation insurance. Its business model has been criticized as unsustainable since Uber loses money on every ride. McBride (2019) argued that, after losing $5 billion in one quarter, its options were to pay drivers less or to increase prices, but neither is possible because drivers are already operating at near minimum wage and Uber is in a price war with competitors. Its model seems to be to take losses until it reaches a state of monopoly and then to increase prices. Yet Uber has barriers in realizing this plan since many cities and countries are effectively banning the company; for example, London, England, initially removed its licence after it was found that drivers faked their identities (Topham, 2019).

Some of these issues might be peculiar to Uber, but in general they represent factors essential to the Uber model: removing many labour conditions and undercutting costs in an attempt to establish a global monopoly. Far more than the app, and the convenience, these are the elements that we should map across for an Uber for education model, and then it might seem to be less appealing.

The basic idea of an Uber for education metaphor is that universities will be made redundant (again, it would seem) because individual learners will go directly to a marketplace of private educators. As well as the deep problems that such a model relies on, as highlighted above, people rarely consider why a sector is not like Uber.

In order to do so, let’s examine the key elements of the Uber offering.

• A taxi ride is a brief interaction. It helps if the consumer likes the driver, but it’s generally over in 15 minutes, so the consumer does not have to worry too much about an investment in the transaction.
• A taxi ride can vary in some local variables in terms of car, environment, et cetera, but it’s essentially the same product every day and anywhere in the world.
• It’s something for which many people possess the equipment (a car) and the capability (driving).
• The consumer has experience in this type of transaction and knows what they want from it (to get to their destination safely and at low cost).
• Getting a taxi is largely a solitary pursuit.
• Uber utilizes mobile technology and pervasive connectivity to overcome some of the limitations of the previous model, such as waving down a cab or finding the number of a local provider.

Turning to education, then, very few of those conditions are replicated.

• It requires a long time frame (certainly longer than 15 minutes usually) to achieve the required outcome. This means considerably more investment, of both money and time, from the individual, so they need to build a more complex relationship of trust.
• It is very diverse, both by place and by discipline, so any model would be required to replicate such diversity and thus be difficult to use compared with the simplicity of Uber.
• Although there might be a large pool of people who can act as tutors, the ability to construct a curriculum or design a learning activity that can be delivered effectively online is rare. Also, whereas getting a driver’s licence is fairly easy, being licensed to offer formal credit for learning is a complex and highly regulated process.
• Meno’s paradox argues that, if you know what you are looking for, inquiry is unnecessary; however, if you don’t know what you’re looking for, then inquiry is impossible. Put simply, if you are a learner in a new discipline, then you don’t know what it is that you need to know. This means that it is exceedingly difficult to bypass institutions constructed to help learners overcome this very problem.
• Learning is often a social activity undertaken collaboratively with a cohort of people with similar interests and goals.
• Education is already engaging with online learning and mobile delivery, so it is not obvious that it is solving a problem.

There are already some aspects of an Uber-type model in education. For instance, it is often difficult for an institution to compete with an individual consultant on a price for research that does not require large resources. The overhead of a university makes a bid excessive compared with that of a lone researcher working out of a home office. Similarly, the online tutoring model is already under way and will likely expand, particularly in combination with OERs and MOOCs. It will be largely in conjunction with higher education, though, and not in competition with or as a replacement of it.

Most successful start-ups are based upon the transformation of a labour model, usually to the detriment of workers, and these are the elements that we should consider in any such metaphor. Also, the appeal of apps and businesses such as Uber is their simplicity for the user. It is not impossible to address all of the reservations set out above in some Uberized fashion, but it would likely end up being a convoluted and unwieldy system that would defeat the very purpose of its existence. And that is the biggest difference between Uber and education from the consumer’s perspective—getting a taxi is simple (although driving a taxi well is an expert skill), gaining an education is complex. That is why we value it highly—after all, you put letters after your name to indicate your education, not to show how many taxi rides you have taken.

Uber for education can be seen as an example of a broader metaphorical trend that involves how the language and values of start-up culture have been co-opted into education. One example is the cherished status of risk, and universities, educators, and students need to be less risk averse (e.g., Furedi, 2018). However, this deification of risk is often a proxy for justifying privilege in which someone successful believes that their status is merited because they are willing to take the risk. But risk itself is often a privilege.

Blanchflower and Oswald (1998, p. 26) investigated what successful entrepreneurs had in common, and their overwhelming conclusion was that it had nothing to do with personality or genes; rather, “it is access to start-up capital that matters.” Not only do entrepreneurs not have a higher propensity for risk, but also, according to Xu and Ruef (2004, p. 331) in a controlled experiment, “nascent entrepreneurs are more risk-averse than non-entrepreneurs.” However, highlighting privilege is unpopular in start-up culture, which has a belief in meritocracy. But access to capital and a comfortable background seem to be the more salient factors than any personality-related ones. Groth (2015) concludes that “there’s certainly a lot of hard work that goes into building something, [but] there’s also a lot of privilege involved—a factor that is often underestimated.”

For those who promote the value of risk, it is not limited to taking risks with their own careers, however; it also means that they are happy to risk other people’s welfare too. A senior university manager once told me that they loved risk, but that was perhaps because they were unaffected by it. They would likely go on to a well-paid job elsewhere if the risk did not pay off; crucially, not only would they be untouched by any failure of their risk, but also it would likely boost their status. They become a person willing to take risk, which has increased currency in a world where the metaphor for all institutions is the Silicon Valley start-up. Compare their likely outcome with that of an academic in their 50s who might become unemployed with little chance of re-employment as a result of the change that they sought to introduce. The risk of taking a risk is not distributed evenly.

Risk becomes a vehicle by which privilege reinforces itself—only the privileged can take risks, and then risk is rewarded beyond other attributes. This is not to say that we should all be cautious and that people or institutions should never venture to do unusual things. But it is important to ask, “who is really at risk?” and to recognize that the veneration of risk comes from assuming that the start-up culture is an appropriate metaphor for higher education. The Uber for education metaphor is one example of how this culture has permeated much of education, and shapes public discourse on it, but a review of our attitudes to risk-taking reveals that it is far more deeply entrenched than simply one or two analogies of popular tech companies.