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Tag: learning to code

  • Coding Bootcamps and the New For-Profit Higher Ed

    Coding Bootcamps and the New For-Profit Higher Ed

    By Audrey Watters
    ~
    After decades of explosive growth, the future of for-profit higher education might not be so bright. Or, depending on where you look, it just might be…

    In recent years, there have been a number of investigations – in the media, by the government – into the for-profit college sector and questions about these schools’ ability to effectively and affordably educate their students. Sure, advertising for for-profits is still plastered all over the Web, the airwaves, and public transportation, but as a result of journalistic and legal pressures, the lure of these schools may well be a lot less powerful. If nothing else, enrollment and profits at many for-profit institutions are down.

    Despite the massive amounts of money spent by the industry to prop it up – not just on ads but on lobbying and legal efforts, the Obama Administration has made cracking down on for-profits a centerpiece of its higher education policy efforts, accusing these schools of luring students with misleading and overblown promises, often leaving them with low-status degrees sneered at by employers and with loans students can’t afford to pay back.

    But the Obama Administration has also just launched an initiative that will make federal financial aid available to newcomers in the for-profit education sector: ed-tech experiments like “coding bootcamps” and MOOCs. Why are these particular for-profit experiments deemed acceptable? What do they do differently from the much-maligned for-profit universities?

    School as “Skills Training”

    In many ways, coding bootcamps do share the justification for their existence with for-profit universities. That is, they were founded in order to help to meet the (purported) demands of the job market: training people with certain technical skills, particularly those skills that meet the short-term needs of employers. Whether they meet students’ long-term goals remains to be seen.

    I write “purported” here even though it’s quite common to hear claims that the economy is facing a “STEM crisis” – that too few people have studied science, technology, engineering, or math and employers cannot find enough skilled workers to fill jobs in those fields. But claims about a shortage of technical workers are debatable, and lots of data would indicate otherwise: wages in STEM fields have remained flat, for example, and many who graduate with STEM degrees cannot find work in their field. In other words, the crisis may be “a myth.”

    But it’s a powerful myth, and one that isn’t terribly new, dating back at least to the launch of the Sputnik satellite in 1957 and subsequent hand-wringing over the Soviets’ technological capabilities and technical education as compared to the US system.

    There are actually a number of narratives – some of them competing narratives – at play here in the recent push for coding bootcamps, MOOCs, and other ed-tech initiatives: that everyone should go to college; that college is too expensive – “a bubble” in the Silicon Valley lexicon; that alternate forms of credentialing will be developed (by the technology sector, naturally); that the tech sector is itself a meritocracy, and college degrees do not really matter; that earning a degree in the humanities will leave you unemployed and burdened by student loan debt; that everyone should learn to code. Much like that supposed STEM crisis and skill shortage, these narratives might be powerful, but they too are hardly provable.

    Nor is the promotion of a more business-focused education that new either.

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    Career Colleges: A History

    Foster’s Commercial School of Boston, founded in 1832 by Benjamin Franklin Foster, is often recognized as the first school established in the United States for the specific purpose of teaching “commerce.” Many other commercial schools opened on its heels, most located in the Atlantic region in major trading centers like Philadelphia, Boston, New York, and Charleston. As the country expanded westward, so did these schools. Bryant & Stratton College was founded in Cleveland in 1854, for example, and it established a chain of schools, promising to open a branch in every American city with a population of more than 10,000. By 1864, it had opened more than 50, and the chain is still in operation today with 18 campuses in New York, Ohio, Virginia, and Wisconsin.

    The curriculum of these commercial colleges was largely based around the demands of local employers alongside an economy that was changing due to the Industrial Revolution. Schools offered courses in bookkeeping, accounting, penmanship, surveying, and stenography. This was in marketed contrast to those universities built on a European model, which tended to teach topics like theology, philosophy, and classical language and literature. If these universities were “elitist,” the commercial colleges were “popular” – there were over 70,000 students enrolled in them in 1897, compared to just 5800 in colleges and universities – something that highlights what’s a familiar refrain still today: that traditional higher ed institutions do not meet everyone’s needs.

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    The existence of the commercial colleges became intertwined in many success stories of the nineteenth century: Andrew Carnegie attended night school in Pittsburgh to learn bookkeeping, and John D. Rockefeller studied banking and accounting at Folsom’s Commercial College in Cleveland. The type of education offered at these schools was promoted as a path to become a “self-made man.”

    That’s the story that still gets told: these sorts of classes open up opportunities for anyone to gain the skills (and perhaps the certification) that will enable upward mobility.

    It’s a story echoed in the ones told about (and by) John Sperling as well. Born into a working class family, Sperling worked as a merchant marine, then attended community college during the day and worked as a gas station attendant at night. He later transferred to Reed College, went on to UC Berkeley, and completed his doctorate at Cambridge University. But Sperling felt as though these prestigious colleges catered to privileged students; he wanted a better way for working adults to be able to complete their degrees. In 1976, he founded the University of Phoenix, one of the largest for-profit colleges in the US which at its peak in 2010 enrolled almost 600,000 students.

    Other well-known names in the business of for-profit higher education: Walden University (founded in 1970), Capella University (founded in 1993), Laureate Education (founded in 1999), Devry University (founded in 1931), Education Management Corporation (founded in 1962), Strayer University (founded in 1892), Kaplan University (founded in 1937 as The American Institute of Commerce), and Corinthian Colleges (founded in 1995 and defunct in 2015).

    It’s important to recognize the connection of these for-profit universities to older career colleges, and it would be a mistake to see these organizations as distinct from the more recent development of MOOCs and coding bootcamps. Kaplan, for example, acquired the code school Dev Bootcamp in 2014. Laureate Education is an investor in the MOOC provider Coursera. The Apollo Education Group, the University of Phoenix’s parent company, is an investor in the coding bootcamp The Iron Yard.

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    Promises, Promises

    Much like the worries about today’s for-profit universities, even the earliest commercial colleges were frequently accused of being “purely business speculations” – “diploma mills” – mishandled by administrators who put the bottom line over the needs of students. There were concerns about the quality of instruction and about the value of the education students were receiving.

    That’s part of the apprehension about for-profit universities’ (almost most) recent manifestations too: that these schools are charging a lot of money for a certification that, at the end of the day, means little. But at least the nineteenth century commercial colleges were affordable, UC Berkley history professor Caitlin Rosenthal argues in a 2012 op-ed in Bloomberg,

    The most common form of tuition at these early schools was the “life scholarship.” Students paid a lump sum in exchange for unlimited instruction at any of the college’s branches – $40 for men and $30 for women in 1864. This was a considerable fee, but much less than tuition at most universities. And it was within reach of most workers – common laborers earned about $1 per day and clerks’ wages averaged $50 per month.

    Many of these “life scholarships” promised that students who enrolled would land a job – and if they didn’t, they could always continue their studies. That’s quite different than the tuition at today’s colleges – for-profit or not-for-profit – which comes with no such guarantee.

    Interestingly, several coding bootcamps do make this promise. A 48-week online program at Bloc will run you $24,000, for example. But if you don’t find a job that pays $60,000 after four months, your tuition will be refunded, the startup has pledged.

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    According to a recent survey of coding bootcamp alumni, 66% of graduates do say they’ve found employment (63% of them full-time) in a job that requires the skills they learned in the program. 89% of respondents say they found a job within 120 days of completing the bootcamp. Yet 21% say they’re unemployed – a number that seems quite high, particularly in light of that supposed shortage of programming talent.

    For-Profit Higher Ed: Who’s Being Served?

    The gulf between for-profit higher ed’s promise of improved job prospects and the realities of graduates’ employment, along with the price tag on its tuition rates, is one of the reasons that the Obama Administration has advocated for “gainful employment” rules. These would measure and monitor the debt-to-earnings ratio of graduates from career colleges and in turn penalize those schools whose graduates had annual loan payments more than 8% of their wages or 20% of their discretionary earnings. (The gainful employment rules only apply to those schools that are eligible for Title IV federal financial aid.)

    The data is still murky about how much debt attendees at coding bootcamps accrue and how “worth it” these programs really might be. According to the aforementioned survey, the average tuition at these programs is $11,852. This figure might be a bit deceiving as the price tag and the length of bootcamps vary greatly. Moreover, many programs, such as App Academy, offer their program for free (well, plus a $5000 deposit) but then require that graduates repay up to 20% of their first year’s salary back to the school. So while the tuition might appear to be low in some cases, the indebtedness might actually be quite high.

    According to Course Report’s survey, 49% of graduates say that they paid tuition out of their own pockets, 21% say they received help from family, and just 1.7% say that their employer paid (or helped with) the tuition bill. Almost 25% took out a loan.

    That percentage – those going into debt for a coding bootcamp program – has increased quite dramatically over the last few years. (Less than 4% of graduates in the 2013 survey said that they had taken out a loan). In part, that’s due to the rapid expansion of the private loan industry geared towards serving this particular student population. (Incidentally, the two ed-tech companies which have raised the most money in 2015 are both loan providers: SoFi and Earnest. The former has raised $1.2 billion in venture capital this year; the latter $245 million.)

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    The Obama Administration’s newly proposed “EQUIP” experiment will open up federal financial aid to some coding bootcamps and other ed-tech providers (like MOOC platforms), but it’s important to underscore some of the key differences here between federal loans and private-sector loans: federal student loans don’t have to be repaid until you graduate or leave school; federal student loans offer forbearance and deferment if you’re struggling to make payments; federal student loans have a fixed interest rate, often lower than private loans; federal student loans can be forgiven if you work in public service; federal student loans (with the exception of PLUS loans) do not require a credit check. The latter in particular might help to explain the demographics of those who are currently attending coding bootcamps: if they’re having to pay out-of-pocket or take loans, students are much less likely to be low-income. Indeed, according to Course Report’s survey, the cost of the bootcamps and whether or not they offered a scholarship was one of the least important factors when students chose a program.

    Here’s a look at some coding bootcamp graduates’ demographic data (as self-reported):

    Age
    Mean Age 30.95
    Gender
    Female 36.3%
    Male 63.1%
    Ethnicity
    American Indian 1.0%
    Asian American 14.0%
    Black 5.0%
    Other 17.2%
    White 62.8%
    Hispanic Origin
    Yes 20.3%
    No 79.7%
    Citizenship
    Yes, born in the US 78.2%
    Yes, naturalized 9.7%
    No 12.2%
    Education
    High school dropout 0.2%
    High school graduate 2.6%
    Some college 14.2%
    Associate’s degree 4.1%
    Bachelor’s degree 62.1%
    Master’s degree 14.2%
    Professional degree 1.5%
    Doctorate degree 1.1%

    (According to several surveys of MOOC enrollees, these students also tend to be overwhelmingly male from more affluent neighborhoods, and MOOC students also tend to already possess Bachelor’s degrees. The median age of MITx registrants is 27.)

    It’s worth considering how the demographics of students in MOOCs and coding bootcamps may (or may not) be similar to those enrolled at other for-profit post-secondary institutions, particularly since all of these programs tend to invoke the rhetoric about “democratizing education” and “expanding access.” Access for whom?

    Some two million students were enrolled in for-profit colleges in 2010, up from 400,000 a decade earlier. These students are disproportionately older, African American, and female when compared to the entire higher ed student population. While one in 20 of all students are enrolled in a for-profit college, 1 in 10 African American students, 1 in 14 Latino students, and 1 in 14 first-generation college students are enrolled at a for-profit. Students at for-profits are more likely to be single parents. They’re less likely to enter with a high school diploma. Dependent students in for-profits have about half as much family income as students in not-for-profit schools. (This demographic data is drawn from the NCES and from Harvard University researchers David Deming, Claudia Goldin, and Lawrence Katz in their 2013 study on for-profit colleges.)

    Deming, Goldin, and Katz argue that

    The snippets of available evidence suggest that the economic returns to students who attend for-profit colleges are lower than those for public and nonprofit colleges. Moreover, default rates on student loans for proprietary schools far exceed those of other higher-education institutions.

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    According to one 2010 report, just 22% of first- and full-time students pursuing Bachelor’s degrees at for-profit colleges in 2008 graduated, compared to 55% and 65% of students at public and private non-profit universities respectively. Of the more than 5000 career programs that the Department of Education tracks, 72% of those offered by for-profit institutions produce graduates who earn less than high school dropouts.

    For their part, today’s MOOCs and coding bootcamps also boast that their students will find great success on the job market. Coursera, for example, recently surveyed its students who’d completed one of its online courses and 72% who responded said they had experienced “career benefits.” But without the mandated reporting that comes with federal financial aid, a lot of what we know about their student population and student outcomes remains pretty speculative.

    What kind of students benefit from coding bootcamps and MOOC programs, the new for-profit education? We don’t really know… although based on the history of higher education and employment, we can guess.

    EQUIP and the New For-Profit Higher Ed

    On October 14, the Obama Administration announced a new initiative, the Educational Quality through Innovative Partnerships (EQUIP) program, which will provide a pathway for unaccredited education programs like coding bootcamps and MOOCs to become eligible for federal financial aid. According to the Department of Education, EQUIP is meant to open up “new models of education and training” to low income students. In a press release, it argues that “Some of these new models may provide more flexible and more affordable credentials and educational options than those offered by traditional higher institutions, and are showing promise in preparing students with the training and education needed for better, in-demand jobs.”

    The EQUIP initiative will partner accredited institutions with third-party providers, loosening the “50% rule” that prohibits accredited schools from outsourcing more than 50% of an accredited program. Since bootcamps and MOOC providers “are not within the purview of traditional accrediting agencies,” the Department of Education says, “we have no generally accepted means of gauging their quality.” So those organizations that apply for the experiment will have to provide an outside “quality assurance entity,” which will help assess “student outcomes” like learning and employment.

    By making financial aid available for bootcamps and MOOCs, one does have to wonder if the Obama Administration is not simply opening the doors for more of precisely the sort of practices that the for-profit education industry has long been accused of: expanding rapidly, lowering the quality of instruction, focusing on marketing to certain populations (such as veterans), and profiting off of taxpayer dollars.

    Who benefits from the availability of aid? And who benefits from its absence? (“Who” here refers to students and to schools.)

    Shawna Scott argues in “The Code School-Industrial Complex” that without oversight, coding bootcamps re-inscribe the dominant beliefs and practices of the tech industry. Despite all the talk of “democratization,” this is a new form of gatekeeping.

    Before students are even accepted, school admission officers often select for easily marketable students, which often translates to students with the most privileged characteristics. Whether through intentionally targeting those traits because it’s easier to ensure graduates will be hired, or because of unconscious bias, is difficult to discern. Because schools’ graduation and employment rates are their main marketing tool, they have a financial stake in only admitting students who are at low risk of long-term unemployment. In addition, many schools take cues from their professional developer founders and run admissions like they hire for their startups. Students may be subjected to long and intensive questionnaires, phone or in-person interviews, or be required to submit a ‘creative’ application, such as a video. These requirements are often onerous for anyone working at a paid job or as a caretaker for others. Rarely do schools proactively provide information on alternative application processes for people of disparate ability. The stereotypical programmer is once again the assumed default.

    And so, despite the recent moves to sanction certain ed-tech experiments, some in the tech sector have been quite vocal in their opposition to more regulations governing coding schools. It’s not just EQUIP either; there was much outcry last year after several states, including California, “cracked down” on bootcamps. Many others have framed the entire accreditation system as a “cabal” that stifles innovation. “Innovation” in this case implies alternate certificate programs – not simply Associate’s or Bachelor’s degrees – in timely, technical topics demanded by local/industry employers.

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    The Forgotten Tech Ed: Community Colleges

    Of course, there is an institution that’s long offered alternate certificate programs in timely, technical topics demanded by local/industry employers, and that’s the community college system.

    Vox’s Libby Nelson observed that “The NYT wrote more about Harvard last year than all community colleges combined,” and certainly the conversations in the media (and elsewhere) often ignore that community colleges exist at all, even though these schools educate almost half of all undergraduates in the US.

    Like much of public higher education, community colleges have seen their funding shrink in recent decades and have been tasked to do more with less. For community colleges, it’s a lot more with a lot less. Open enrollment, for example, means that these schools educate students who require more remediation. Yet despite many community colleges students being “high need,” community colleges spend far less per pupil than do four-year institutions. Deep budget cuts have also meant that even with their open enrollment policies, community colleges are having to restrict admissions. In 2012, some 470,000 students in California were on waiting lists, unable to get into the courses they need.

    This is what we know from history: as the funding for public higher ed decreased – for two- and four-year schools alike, for-profit higher ed expanded, promising precisely what today’s MOOCs and coding bootcamps now insist they’re the first and the only schools to do: to offer innovative programs, training students in the kinds of skills that will lead to good jobs. History tells us otherwise…
    _____

    Audrey Watters is a writer who focuses on education technology – the relationship between politics, pedagogy, business, culture, and ed-tech. She has worked in the education field for over 15 years: teaching, researching, organizing, and project-managing. Although she was two chapters into her dissertation (on a topic completely unrelated to ed-tech), she decided to abandon academia, and she now happily fulfills the one job recommended to her by a junior high aptitude test: freelance writer. Her stories have appeared on NPR/KQED’s education technology blog MindShift, in the data section of O’Reilly Radar, on Inside Higher Ed, in The School Library Journal, in The Atlantic, on ReadWriteWeb, and Edutopia. She is the author of the recent book The Monsters of Education Technology (Smashwords, 2014) and working on a book called Teaching Machines. She maintains the widely-read Hack Education blog, on which an earlier version of this essay first appeared, and writes frequently for The b2 Review Digital Studies magazine on digital technology and education.

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  • Program and Be Programmed

    Program and Be Programmed

    Programmed Visions: Software and Memory (MIT Press, 2013)a review of Wendy Chun, Programmed Visions: Software and Memory (MIT Press, 2013)
    by Zachary Loeb
    ~

    Type a letter on a keyboard and the letter appears on the screen, double-click on a program’s icon and it opens, use the mouse in an art program to draw a line and it appears. Yet knowing how to make a program work is not the same as knowing how or why it works. Even a level of skill approaching mastery of a complicated program does not necessarily mean that the user understands how the software works at a programmatic level. This is captured in the canonical distinctions between users and “power users,” on the one hand, and between users and programmers on the other. Whether being a power user or being a programmer gives one meaningful power over machines themselves should be a more open question than injunctions like Douglas Rushkoff’s “program or be programmed” or the general opinion that every child must learn to code appear to allow.

    Sophisticated computer programs give users a fantastical set of abilities and possibilities. But to what extent does this sense of empowerment depend on faith in the unseen and even unknown codes at work in a given program? We press a key on a keyboard and a letter appears on the screen—but do we really know why? These are some of the questions that Wendy Hui Kyong Chun poses in Programmed Visions: Software and Memory, which provides a useful history of early computing alongside a careful analysis of the ways in which computers are used—and use their users—today. Central to Chun’s analysis is her insistence “that a rigorous engagement with software makes new media studies more, rather than less, vapory” (21), and her book succeeds admirably in this regard.

    The central point of Chun’s argument is that computers (and media in general) rely upon a notion of programmability that has become part of the underlying societal logic of neoliberal capitalism. In a society where computers are tied ever more closely to power, Chun argues that canny manipulation of software restores a sense of control or sovereignty to individual users, even as their very reliance upon this software constitutes a type of disempowerment. Computers are the driving force and grounding metaphor behind an ideology that seeks to determine the future—a future that “can be bought and sold” and which “depends on programmable visions that extrapolate the future—or more precisely, a future—based on the past” (9).

    Yet, one of the pleasures of contemporary computer usage, is that one need not fully understand much of what is going on to be able to enjoy the benefits of the computer. Though we may use computer technology to answer critical questions, this does not necessarily mean we are asking critical questions about computer technology. As Chun explains, echoing Michel Foucault, “software, free or not, is embodied and participates in structures of knowledge-power” (21); users become tangled in these structures once they start using a given device or program. Much of this “knowledge-power” is bound up in the layers of code which make software function, the code is that which gives the machine the directions—that which ensures that the tapping of the letter “r” on the keyboard leads to that letter appearing on the screen. Nevertheless, this code typically goes unseen, especially as it becomes source code, and winds up being buried ever deeper, even though this source code is what “embodies the power of the executive, the power of enforcement” (27). Importantly, the ability to write code, the programmer’s skill, does not in and of itself provide systematic power: computers follow “a set of rules that programmers must follow” (28). A sense of power over certain aspects of a computer is still incumbent upon submitting to the control of other elements of the computer.

    Contemporary computers, and our many computer-esque devices (such as smart phones and tablets), are the primary sites in which most of us encounter the codes and programming about which Chun writes, but she takes lengths to introduce the reader to the history of programming. For it is against the historical backdrop of military research, during the Second World War, that one can clearly see the ways in which notions of control, the unquestioning following of orders, and hierarchies have long been at work within computation and programming. Beyond providing an enlightening aside into the vital role that women played in programming history, analyzing the early history of computing demonstrates how as a means of cutting down on repetitive work structured programming emerged that “limits the logical procedures coders can use, and insists that the program consist of small modular units, which can be called from the main program” (36). Gradually this emphasis on structured programming allows for more and more processes to be left to the machine, and thus processes and codes become hidden from view even as future programmers are taught to conform to the demands that will allow for new programs to successfully make use of these early programs. Therefore the processes that were once a result of expertise come to be assumed aspects of the software—they become automated—and it is this very automation (“automatic programming”) that “allows the production of computer-enabled human-readable code” (41).

    As the codes and programs become hidden by ever more layers of abstraction, the computer simultaneously and paradoxically appears to make more of itself visible (through graphic user interfaces, for example), while the code itself recedes ever further into the background. This transition is central to the computer’s rapid expansion into ever more societal spheres, and it is an expansion that Chun links to the influence of neoliberal ideology. The computer with its easy-to-use interfaces creates users who feel as though they are free and empowered to manipulate the machine even as they rely on the codes and programs that they do not see. Freedom to act becomes couched in code that predetermines the range and type of actions that the users are actually free to take. What transpires, as Chun writes, is that “interfaces and operating systems produce ‘users’—one and all” (67).

    Without fully comprehending the codes that lead from a given action (a user presses a button) to a given result, the user is positioned to believe ever more in the power of the software/hardware hybrid, especially as increased storage capabilities allow for computers to access vast informational troves. In so doing, the technologically-empowered user has been conditioned to expect a programmable world akin to the programmed devices they use to navigate that world—it has “fostered our belief in the world as neoliberal: as an economic game that follows certain rules” (92). And this takes place whether or not we understand who wrote those rules, or how they can be altered.

    This logic of programmability may be linked to inorganic machines, but Chun also demonstrates the ways in which this logic has been applied to the organic world as well. In truth, the idea that the organic can be programmed predates the computer; as Chun explains “breeding encapsulates an early logic of programmability… Eugenics, in other words, was not simply a factor driving the development of high-speed mass calculation at the level of content… but also at the level of operationality” (124). In considering the idea that the organic can be programmed, what emerges is a sense of the way that programming has long been associated with a certain will to exert control over things be they organic or inorganic. Far from being a digression, Chun’s discussion of eugenics provides for a fascinating historic comparison given the way in which its decline in acceptance seems to dovetail with the steady ascendance of the programmable machine.

    The intersection of software and memory (or “software as memory”) is an essential matter to consider given the informational explosion that has occurred with the spread of computers. Yet, as Chun writes eloquently: “information is ‘undead’; neither alive nor dead, neither quite present nor absent” (134), since computers simultaneously promise to make ever more information available while making the future of much of this information precarious (insofar as access may rely upon software and hardware that no longer functions). Chun elucidates the ways in which the shift from analog to digital has permitted a wider number of users to enjoy the benefits of computers while this shift has likewise made much that goes on inside a computer (software and hardware) less transparent. While the machine’s memory may seem ephemeral and (to humans) illegible, accessing information in “storage” involves codes that read by re-writing elsewhere. This “battle of diligence between the passing and the repetitive” characterizing machine memory, Chun argues, “also characterizes content today” (170). Users rely upon a belief that the information they seek will be available and that they will be able to call upon it with a few simple actions, even though they do not see (and usually cannot see) the processes that make this information present and which do or do not allow it to be presented.

    When people make use of computers today they find themselves looking—quite literally—at what the software presents to them, yet in allowing this act of seeing the programming also has determined much of what the user does not see. Programmed Visions is an argument for recognizing that sometimes the power structures that most shape our lives go unseen—even if we are staring right at them.

    * * *

    With Programmed Visions, Chun has crafted a nuanced, insightful, and dense, if highly readable, contribution to discussions about technology, media, and the digital humanities. It is a book that demonstrates Chun’s impressive command of a variety of topics and the way in which she can engagingly shift from history to philosophy to explanations of a more technical sort. Throughout the book Chun deftly draws upon a range of classic and contemporary thinkers, whilst raising and framing new questions and lines of inquiry even as she seeks to provide answers on many other topics.

    Though peppered with many wonderful turns of phrase, Programmed Visions remains a challenging book. While all readers of Programmed Visions will come to it with their own background and knowledge of coding, programming, software, and so forth—the simple truth is that Chun’s point (that many people do not understand software sufficiently) may make many a reader feel somewhat taken aback. For most computer users—even many programmers and many whose research involves the study of technology and media—are quite complicit in the situation that Chun describes. It is the sort of discomforting confrontation that is valuable precisely because of the anxiety it provokes. Most users take for granted that the software will work the way they expect it to—hence the frustration bordering on fury that many people experience when suddenly the machine does something other than that which is expected provoking a maddened outburst of “why aren’t you working!” What Chun helps demonstrate is that it is not so much that the machines betray us, but that we were mistaken in our thinking that machines ever really obeyed us.

    It will be easy for many readers to see themselves as the user that Chun describes—as someone positioned to feel empowered by the devices they use, even as that power depends upon faith in forces the user cannot see, understand, or control. Even power users and programmers, on careful self-reflection may identify with Chun’s relocation of the programmer from a position of authority to a role wherein they too must comply with the strictures of the code presents an important argument for considerations of such labor. Furthermore, the way in which Chun links the power of the machine to the overarching ideology of neoliberalism makes her argument useful for discussions broader than those in media studies and the digital humanities. What makes these arguments particularly interesting is the way in which Chun locates them within thinking about software. As she writes towards the end of the second chapter, “this chapter is not a call to return to an age when one could see and comprehend the actions of our computers. Those days are long gone… Neither is this chapter an indictment of software or programming… It is, however, an argument against common-sense notions of software precisely because of their status as common sense” (92). Such a statement refuses to provide the anxious reader (who has come to see themselves as an uninformed user) with a clear answer, for it suggests that the “common-sense” clear answer is part of what has disempowered them.

    The weaving of historic details regarding computers during World War II and eugenics provide an excellent and challenging atmosphere against which Chun’s arguments regarding programmability can grow. Chun lucidly describes the embodiment and materiality of information and obsolescence that serve as major challenges confronting those who seek to manage and understand the massive informational flux that computer technology has enabled. The idea of information as “undead” is both amusing and evocative as it provides for a rich way of describing the “there but not there” of information, while simultaneously playing upon the slight horror and uneasiness that seems to be lurking below the surface in the confrontation with information.

    As Chun sets herself the difficult task of exploring many areas, there are some topics where the reader may be left wanting more. The section on eugenics presents a troubling and fascinating argument—one which could likely have been a book in and of itself—especially when considered in the context of arguments about cyborg selves and post-humanity, and it is a section that almost seems to have been cut short. Likewise the discussion of race (“a thread that has been largely invisible yet central,” 179), which is brought to the fore in the epilogue, confronts the reader with something that seems like it could in fact be the introduction for another book. It leaves the reader with much to contemplate—though it is the fact that this thread was not truly “largely invisible” that makes the reader upon reaching the epilogue wish that the book could have dealt with that matter at greater length. Yet, these are fairly minor concerns—that Programmed Visions leaves its readers re-reading sections to process them in light of later points is a credit to the text.

    Programmed Visions: Software and Memory is an alternatively troubling, enlightening, and fascinating book. It allows its reader to look at software and hardware in a new way, with a fresh insight about this act of sight. It is a book that plants a question (or perhaps subtly programs one into the reader’s mind): what are you not seeing, what power relations remain invisible, between the moment during which the “?” is hit on the keyboard and the moment it appears on the screen?


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    Zachary Loeb is a writer, activist, librarian, and terrible accordion player. He earned his MSIS from the University of Texas at Austin, and is currently working towards an MA in the Media, Culture, and Communications department at NYU. His research areas include media refusal and resistance to technology, ethical implications of technology, alternative forms of technology, and libraries as models of resistance. Using the moniker “The Luddbrarian” Loeb writes at the blog librarianshipwreck. He has previously reviewed The People’s Platform by Astra Taylor and Social Media: A Critical Introduction by Christian Fuchs for boundary2.org.

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