This talk was presented at The University of Edinburgh’s Moray House School of Education
Let me begin with a story. In December 2012 – we all remember 2012 right? “The Year of the MOOC” – I was summoned to Palo Alto, California for a small gathering to discuss the future of teaching, learning, and technology. I use the verb “summoned” deliberately.
The event was organized by Sebastian Thrun, who at the beginning of the year had announced that he was resigning his full time professor position at Stanford in order to launch Udacity, his online education startup. It was held at Stanford in its artificial intelligence lab, which was a little awkward a venue as Thrun’s office – he still had an office on campus, of course – was right next to those of Daphne Koller and Andrew Ng, his fellow Stanford AI professors who’d announced in April that they were launching a competitor company, Coursera.
When Thrun first invited us all to this event – about ten of us – he promised that at the end of the weekend, we would take a ride in a zeppelin over San Francisco. And I thought “like hell I will.” I’ve seen A View to a Kill. I know what happened to the dissenters who got into a zeppelin in that movie. But as it turned out, the zeppelin company had gone out of business – I imagine that many people, like myself, could only think about Christopher Walken and Grace Jones’ characters and opted not to go.
So instead of a zeppelin, we got to ride in one of Google’s self-driving cars, which was of course the project that Thrun had been working on when he gave his famous TED Talk in 2011 – and that, in turn, was where he heard Salman Khan give his famous TED Talk. It was when and where Thrun decided that he needed to rethink his work as a Stanford professor in order to “scale” education.
Thrun “drove.” He steered the car onto I–280 and then let the car take over, and I have to say – and I say this as a professional skeptic of technology – it was this strange combination of the utterly banal and the utterly impressive. (It was 2012, I should reiterate, so it was right at the beginning of all this hype about a future of autonomous vehicles.)
The car was covered in cameras and sensors, inside and out – even a QR code on the driver’s side glove compartment that you were supposed to scan to sign Google’s Terms of Service before riding. Seemingly the most dangerous element of our little jaunt was that other drivers swerved and slowed down as they stared at the car, with its giant camera on top and Google logo on the sides. There was Thrun with his hands off the wheel, feet off the pedals, eyes not on the road, sometimes turning around entirely to face the passengers in the back seat, explaining how the car (and Google, of course) collected massive amounts of data in order to map the road and move efficiently along it.
Efficiency. That’s the goal of the self-driving car. (You’re free to insert here some invented statistic about the percentage of space and energy that are wasted by human-driven traffic and human driving patterns and that will be corrected by roads full of autonomous vehicles. I vaguely recall Thrun doing so at least.)
It was then and there on that trip that I had a revelation about how many entrepreneurs and engineers in Silicon Valley conceive of education and the role of technology in reshaping it: that is, if you collect enough data – lots and lots and lots of data – you can build a map. This is their conceptual framework for visualizing how “learners” (and that word is used to describe various, imagined students, workers, and consumers) get from here to there, whether it’s through a course or through a degree program or towards a job. With enough data and some machine learning, you can identify – statistically – the most common obstacles. You can plot the most frequently traveled path and the one that folks traverse most quickly. You can optimize. And once you’ve trained those algorithms, you can apply them everywhere. You can scale.
We can debate this model (we should debate this model) – how it works or doesn’t work when applied to education. (Is learning “like a map”? Is learning an engineering problem? Is the absence of “data” or algorithms really a problem?) But one of the most important things to remember is that this is (largely) a computer scientist’s model. It’s the model of human learning by someone who claims expertise in machine learning, a field of study which has aspired to model if not surpass the human mind. And that makes it a model in turn that rests on a lot of assumptions about “learning” – both how humans “learn” and how machines “learn” to conceptualize and navigate their worlds.
It’s a model. It’s a metaphor.
It’s an aspiration – a human aspiration, to be clear. This isn’t what machines “want.” (Machines have no wants.)
I think many of us quickly recognized back in 2012 that, despite the AI expertise in the executive offices of these MOOC companies, there wasn’t much “artificial intelligence” beyond a few of their course offerings; there wasn’t much “intelligence” in their assessments or in their course recommendation engines. What these MOOCs were, nonetheless, were (and still are) massive online honeypots into which we’ve been lured – registering and watching and clicking in order to generate massive education datasets.
Perhaps with this data, the MOOC providers can build a map of professional if not cognitive pathways. Perhaps. Someday. Maybe. In the meantime, these companies continue to collect a lot of “driving” data.
Who controls the mapping data and who controls the driving data and who controls the autonomous vehicle patents are, of course, a small part of the legal and financial battles that are brewing over the future of autonomous vehicles. Google versus Uber. Google versus Didi (a Chinese self-driving car company). We can speculate, I suppose, about what the analogous battles might be in education – which corporation will sue which corporation, claiming they “own” learning data and learning roadmaps and learning algorithms and learning software IP.
(Spoiler alert: it won’t actually be learners – just like it’s not actually drivers – even though that’s where the interesting data comes from: not from mapping the roads, but from monitoring the traffic.)
As we were driving on the freeways around Palo Alto in the Google autonomous vehicle, someone asked Sebastian Thrun what happens if there’s an unexpected occurrence while the car is in self-driving mode. Now, the car is constantly making small adjustments – to its speed, to its distance to other vehicles. “But what would happen if, say, a tree suddenly came crashing down in the road right in front of it,” the passenger asked Thrun.
“The car would stop,” he said. The human driver would be prompted to take over. Hopefully the human driver is paying attention. Hopefully there’s a human driver.
Of course, the “unexpected” occurs all the time – on the road and in the classroom.
Recently the “ride-sharing” company Uber flouted California state regulations in order to start offering an autonomous vehicle ride-sharing service in San Francisco. The company admitted that it hadn’t addressed at least one flaw in their programming: that its cars would make a right hand turn through a bicycle lane (the equivalent of a left-hand turn here in the UK). Uber didn’t have a model for recognizing the existence of “bike lane” (and as such “cyclists”). It’s not that the car didn’t see something “unexpected”; that particular “unexpected” was not fully modeled, and the self-driving car didn’t slow, and it didn’t stop.
In this testing phase of Uber’s self-driving cars, it did still have a driver sitting behind the wheel. Documents recently obtained by the tech publication Recode revealed that Uber’s autonomous vehicles drove, on average, less than a mile without requiring human intervention.
The technology simply isn’t that good yet.
At the conclusion of our ride, Thrun steered the Google self-driving car back to his house, where he summoned a car service to take us back to our hotel. Giddy from the experience, one professor boasted to the driver what we’d just done. He frowned. “Oh,” he said. “So, you just put me out of a job?”
“Put me out of a job.” “Put you out of a job.” “Put us all out of work.” We hear that a lot, with varying levels of glee and callousness and concern. “Robots are coming for your job.”
We hear it all the time. To be fair, of course, we have heard it, with varying frequency and urgency, for about 100 years now. “Robots are coming for your job.” And this time – this time – it’s for real.
I want to suggest – and not just because there are flaws with Uber’s autonomous vehicles (and there was just a crash of a test vehicle in Arizona last Friday) – that this is not entirely a technological proclamation. Robots don’t do anything they’re not programmed to do. They don’t have autonomy or agency or aspirations. Robots don’t just roll into the human resources department on their own accord, ready to outperform others. Robots don’t apply for jobs. Robots don’t “come for jobs.” Rather, business owners opt to automate rather than employ people. In other words, this refrain that “robots are coming for your job” is not so much a reflection of some tremendous breakthrough (or potential breakthrough) in automation, let alone artificial intelligence. Rather, it’s a proclamation about profits and politics. It’s a proclamation about labor and capital.
And this is as true in education as it is in driving.
As Recode wrote in that recent article,
Successfully creating self-driving technology has become a crucial factor to Uber’s profitability. It would allow Uber to generate higher sales per ride since it would keep all of the fare. Uber has currently suffered losses in some markets partly because of having to offer subsidies to attract drivers. Computers are cheaper in the long run.
“Computers are cheaper in the long run.” Cheaper for whom? Cheaper how?
Well, robots don’t take sick days. They don’t demand retirement or health insurance benefits. You tell them the rules, and they obey the rules. They don’t ask questions. They don’t unionize. They don’t strike.
A couple of years ago, there was a popular article in circulation in the US that claimed that the most common occupation in every state is “truck driver.” The data is a little iffy – the US is a service economy, not a shipping economy – but its claim about why “truck driver” is still fairly revealing: unlike other occupations, the work of “truck driver” has not been affected by globalization, the article claimed, and it has not (yet) been affected by automation. (The CEO of Otto, a self-driving trucking company now owned by Uber, just predicted this week that AI will reshape the industry within the next ten years.)
Truck driving is also a profession – an industry – that’s been subject to decades of regulation and deregulation.
That regulatory framework is just one of the objects of derision – of “disruption” and dismantling – of the ride-sharing company Uber. Founded in 2008 – ostensibly when CEO Travis Kalanick was unable to hail a cab while in Paris – the company has become synonymous with the so-called “sharing” or “freelance” economy, Silicon Valley’s latest rebranding of technologically-enhanced economic precarity and job insecurity.
“Anyone” can drive for Uber, no special training or certification required. Well, anyone who’s 21 or older and has three years of driving experience and a clean driving record. Anyone with car insurance. Anyone whose car has at least four doors and is newer than 2001 – Uber will also help you finance a new car, even if you have a terrible credit score. Your loan payments are simply deducted from your Uber earnings each week.
All along, Uber has been quite clear, that despite wooing drivers to its platform, using “independent contractors” is only temporary. The company plans to replace drivers with driverless cars.
Since its launch, Uber has become infamous for its opposition to regulations and to unions. (Uber has recently been using podcasts broadcast from its app in order to dissuade drivers in Seattle from unionizing, for example.)
And I’ll note here in case this sounds too much like a talk on autonomous vehicles and not enough on automated education, I am purposefully putting these two “disruptions” side by side. After all, education is fairly regulated as well – accreditation, for example, dictates who gets to offer “real” degrees. There are rules about who gets to run a “real school.” Trump University, not a real school. And there are rules as to who gets to be in the classroom, rules about who can teach. But any semblance of job protections – at both the K–12 level and at the higher education level in the US – is under attack. (Again, this isn’t simply about replacing teachers with computers because computers have become so powerful. But it is about replacing teachers nonetheless.) You no longer need a teaching degree (or any teaching training) in Utah. And while the certification demands might still be in place in colleges and universities, they’ve been moving towards a precarious teaching labor force for some time now. More than three-quarters of the teaching staff in the US are adjuncts – short-time employees with no job security and often no benefits. “Independent contractors.” Uber encourages educators to earn a little cash on the side as drivers.
Like I said, I’m not sure I believe that the most prevalent job in the US is “truck driver.” But I do know this to be true: the largest union in the United States is the National Education Association. The other teachers’ union, the American Federation of Teachers, is the sixth largest. Many others who work in public education are represented by the second largest union in the US, the Service Employees International Union.
Silicon Valley hates unions. It loathes organized labor just as it loathes regulations (until it benefits from regulations, of course).
Now, for its part, Uber has also been accused of violating “regulations” like the Americans with Disabilities Act for refusing to pick up riders with service dogs or with wheelchairs. A fierce proponent of laissez-faire capitalism, Uber has received a fair amount of negative press for its price gouging practices – it uses what it calls “surge pricing” during peak demand, increasing the amount a ride will cost in order, Uber says, to lure more drivers out onto the road. It’s implemented surge pricing not just on holidays like New Year’s Eve but during several weather-related emergencies. The company has also actively sabotaged its rivals – attacking other ride service companies as well as journalists.
None of this makes the phrase “Uber for Education” particularly appealing. But that’s how Sebastian Thrun described his company Udacity in a series of interviews in 2015.
“At Udacity, we built an Uber-like platform,” he told the MIT Technology Review. “With Uber any normal person with a car can become a driver, and with Udacity now every person with a computer can become a global code reviewer. … Just like Uber, we’ve made the financials line up. The best-earning global code reviewer makes more than 17,000 bucks a month. I compare this to the typical part-time teacher in the U.S. who teaches at a college – they make about $2,000 a month.”
“We want to be the Uber of education,” Thrun told The Financial Times, which added that, “Mr Thrun knows what he doesn’t want for his company: professors in tenure, which he claims limits the ability to react to market demands.”
In other words, “disrupt” job protections through a cheap, precarious labor force doing piecemeal work until the algorithms are sophisticated enough to perform those tasks. Universities have already taken plenty of steps towards this end, without the help of algorithms or for-profit software providers. But universities are still bound by accreditation (and by tradition). “Anyone can teach” is not a stance on labor and credentialing that many universities are ready to take.
Udacity is hardly the only company that invokes the “Uber for Education” slogan. There’s PeerUp, whose founder describes the company as “Uber for tutors.” There’s ProfHire and Adjunct Professor Link, Uber for contingent faculty. There’s The Graide Network, Uber for teaching assistants and exam markers. There’s Parachute Teachers, which describes itself as “Uber for substitute teachers.”
Again, what we see here with these services are companies that market “on demand” labor as “disruption.” These certainly reflect larger trends at work dismantling the teaching profession – de-funding, de-professionalization, adjunctification, a dismissal of expertise and experience.
Anyone can teach. Indeed, the only ones who shouldn’t are probably the ones in the classroom right now – or so this story goes. The right wing think tank The Heritage Foundation has called for an “Uber-ized Education.” The right wing publication The National Review has called for “an Uber for Education.” Echoing some of the arguments made by Uber CEO Travis Kalanick, these publications (and many many others) speak of ending the monopolies that “certain groups” (unions, women, liberals, I don’t know) have on education – ostensibly, I guess, on public schools – and bringing more competition to the education system.
US Secretary of Education in a speech earlier this week also invoked Uber as a model that education should emulate: “Just as the traditional taxi system revolted against ridesharing,” she told the Brookings Institution, “so too does the education establishment feel threatened by the rise of school choice. In both cases, the entrenched status quo has resisted models that empower individuals.”
All this is a familiar refrain in Silicon Valley, which has really cultivated its own particular brand of consumerism wrapped up in the mantle of libertarianism.
Travis Kalanick is just one of many tech CEOs who have praised the work of objectivist “philosopher” and “novelist” Ayn Rand, once changing the background of his Twitter profile to the cover of her book The Fountainhead. He told The Washington Post in a 2012 Q&A that the regulations that the car service industry faced bore an “uncanny resemblance” to Rand’s other novel, Atlas Shrugged.
(A quick summary for those lucky enough to be unfamiliar with the plot: the US has become a dystopia overrun by regulations that cause industries to collapse, innovation to be stifled. The poor are depicted as leeches; the heroes are selfish individualists. Eventually business leaders rise up against the government, led by John Galt. The government collapses, and Galt announced that industrialists will rebuild the world. It is a terrible, terrible novel. It is nonetheless many libertarians’ Bible of sorts.)
I’ve argued elsewhere (and I’ve argued repeatedly) that libertarianism is deeply intertwined in the digital technologies developed by those like Uber’s Kalanick. And I don’t mean here simply or solely that these technologies are wielded to dismantle “big government” or “big unions.” I mean that embedded in these technologies, in their design and in their development and in their code, are certain ideological tenets – in the case of libertarianism, a belief in order, freedom, work, self-governance, and individualism.
That last one is key, I think, for considering the future of education and education technology – as designed and developed and coded by Silicon Valley. Individualism.
Now obviously these beliefs are evident throughout American culture and have been throughout American history. Computers didn’t cause neoliberalism. Computers didn’t create libertarians. (It just hooked them all up on Twitter.)
Indeed, there’s that particular strain of individualism that is deeply, deeply American which contributed to libertarianism and to neoliberalism and to computers in turn.
I’d argue that that strain of individualism has been a boon for the automotive industry – for car culture. Many Americans would rather drive their own vehicles rather than rely on – and/or fund – public transportation. I think this is both Uber’s great weakness and also, strangely, its niche: you hail a car, rather than take the bus. The car comes immediately; you do not have to wait. It takes you to your destination; you needn’t stop for others. As such, you can dismiss the need to develop a public transportation infrastructure as some cities in the US have done, some opting to outsource this to Uber instead.
In a car, you can move at your own pace. In a car, you can move in the direction you choose – when and where you want to go. In a car, you can stop and start, sure, but most often you want to get where you’re going efficiently. In a car – and if you watch television ads for car companies, you can see evidence of this powerful imaginary most strikingly – you are truly free.
Unlike the routes of public transportation – the bus route, the subway line – routes that are prescribed for and by the collective, the car is for you and you alone. The car is another one of these radically individualistic, individualizing technologies.
The car is a prototype of sorts for the concept of “personalization.”
Branded. Controlled. Manufactured en masse. Mass-marketed. And yet somehow this symbol of the personal, the individual.
We can think about the relationship too between education systems and individualism. I believe increasingly that’s how education is defined – not as a collective endeavor or a public good, but as an individual investment.
“Personalization” is a reflection of that.
“Personalized” education promises you can move at your own pace. You can (ostensibly) move in the direction you choose. You can stop and start, sure, but most often you want to get where you’re going efficiently. With “personalized” software – – and if you read publications like Edsurge, you can see evidence of this powerful imaginary most strikingly – the learner is truly free.
Unlike the routes of “traditional” education – the lecture hall, the classroom – those routes that are prescribed for and by the collective, “personalized software” is for you and you alone. The computer is a radically individualistic, individualizing technology; education becomes a radically individualistic act.
(I’ll just whisper this because I’d hate to ruin the end of the movie for folks: this freedom actually involves you driving.)
Let me pause here and note that there are several directions that I could take this talk: data collection and analysis as “personalization,” for example. The New York Times just wrote about an app called Greyball that Uber has utilized to avoid scrutiny from law enforcement and regulators in the cities into which it’s tried to expand. The app would ascertain, based on a variety of signals, when cops might be trying to summon an Uber and would prevent them from doing so. Instead, they’d see a special version of Uber – “personalized” – that misinformed them that there were no cars in the vicinity.
How is “personalized learning” – the automation of education through algorithms – a form of “greyballing”? I am really intrigued by this question.
Another piece of the automation puzzle for education (and for “smart car” and for “smart homes”) involves questions of what we mean by “intelligence” in that phrase “artificial intelligence.” What are the histories and practices of “intelligence” – how have humans been ranked, categorized, punished, and rewarded based on an assessment of intelligence? How is intelligence performed – by man (and I do mean “man”) and by machine? What do we read as signs of intelligence? What do we cultivate as signs of intelligence – in our students and in our machines? What role have educational institutions had in developing and sanctioning intelligence? How does believing there’s such a thing as “machine intelligence” challenge some institutions (and prop up others)?
But I want to press on a little more with a look at automation and labor: this issue of driverless cars and driverless school, this issue of “freedom” as being intertwined with algorithmic decision-making and precarious labor.
I am lifting the phrase “driverless school” for the title of this talk from Karen Gregory who recently tweeted something about the “driverless university.” I believe she was at a conference, but in the horrible way that Twitter strips context from our utterances, I’m going to borrow it without knowing who or what she was referring to and re-contextualize the phrase here for my purposes because that’s the visiting speaker’s prerogative.
I do think that in many ways MOOCs were envisioned – by Thrun and by others – as a move towards this idea of a “driverless university.” And that phrase and the impulse behind it should prompt us to ask, no doubt, who is currently “driving” school? Who do education engineers imagine is doing the driving? Is it the administration? The faculty? The government? The unions? Who is exactly going to be displaced by algorithms, by software that purport to make a university “driverless”?
What’s important to consider, I’d argue, is that if we want to rethink how the university functions – and I’ll just assume that we all do in some way or another – “driverlessness” certainly doesn’t give the faculty a greater say in governance. (Indeed, faculty governance seems, in many cases, one of the things that automation seeks to eliminate. Think Thrun’s comments on tenure, for example.) More troubling, the “driverlessness” of algorithms is opaque – even more opaque than universities’ decision-making already is (and that is truly saying something).
And despite all the talk of catering to what Silicon Valley has lauded in the “self-directed learner,” to those whom Tressie McMillan Cottom has called the “roaming autodidacts,” the “driverless university” certainly does not give students a greater say in their own education either. The “driverless university,” rather, is controlled by the engineers who write the algorithms, those who model the curriculum, those who think they can best navigate a learning path. There is still a “driver,” but that labor and decision-making power is obscured.
We can see the “driverless university” already under development perhaps at the Math Emporium at Virginia Tech, which The Washington Post once described as “the Wal-Mart of higher education, a triumph in economy of scale and a glimpse at a possible future of computer-led learning.”
Eight thousand students a year take introductory math in a space that once housed a discount department store. Four math instructors, none of them professors, lead seven courses with enrollments of 200 to 2,000. Students walk to class through a shopping mall, past a health club and a tanning salon, as ambient Muzak plays.
The pass rates are up. That’s good traffic data, I suppose, if you’re obsessed with moving bodies more efficiently along the university’s pre-determined “map.” Get the students through pre-calc and other math requirements without having to pay for tenured faculty or, hell, even adjunct faculty. “In the Emporium, the computer is teacher,” The Washington Post tells us.
“Students click their way through courses that unfold in a series of modules.” Of course, students who “click their way through courses” seem unlikely to develop a love for math or a deep understanding of math. They’re unlikely to become math majors. They’re unlikely to become math graduate students. They’re unlikely to become math professors. (And perhaps you think this is a good thing if you believe there are too many mathematicians or if you believe that the study of mathematics has nothing to offer a society that seems increasingly obsessed with using statistics to solve every single problem that it faces or if you think mathematical reasoning is inconsequential to twenty-first century life.)
Students hate the Math Emporium, by the way.
Despite The Washington Post’s pronouncement that “the time has come” for computers as teachers, the time has been coming for years now. “Programmed instruction” and teaching machines – these are concepts that are almost one hundred years old. (So to repeat, the push to automate education is not about technology as much as it’s about ideology.)
In his autobiography, B. F. Skinner described how he came upon the idea of a teaching machine in 1953: Visiting his daughter’s fourth grade classroom, he was struck by the inefficiencies. Not only were all the students expected to move through their lessons at the same pace, but when it came to assignments and quizzes, they did not receive feedback until the teacher had graded the materials – sometimes a delay of days. Skinner believed that both of these flaws in school could be addressed by a machine, so he built a prototype that he demonstrated at a conference the following year.
Skinner’s teaching machine broke concepts down into small concepts – “bite-sized learning” is today’s buzzword. Students moved through these concepts incrementally, which Skinner believe was best for “good contingency management.” Skinner believed that the machines could be used to minimize the number of errors that students made along the way, maximizing the positive behavioral reinforcement that students received. Skinner called this process “programmed instruction.”
“In acquiring complex behavior the student must pass through a carefully designed sequence of steps,” Skinner wrote, “often of considerable length. Each step must be so small that it can always be taken, yet in taking it the student moves somewhat closer to fully competent behavior. The machine must make sure that these steps are taken in a carefully prescribed order.”
Driverless and programmatically constrained.
Skinner had a dozen of the machines he prototyped installed in the self-study room at Harvard in 1958 for use in teaching the undergraduate course Natural Sciences 114. “Most students feel that machine study has compensating advantages,” he insisted. “They work for an hour with little effort, and they report that they learn more in less time and with less effort than in conventional ways.” (And we all know that if it’s good enough for Harvard students…) “Machines such as those we use at Harvard,” Skinner boasted, “could be programmed to teach, in whole and in part, all the subjects taught in elementary and high school and many taught in college.” The driverless university.
One problem – there are many problems, but here’s a really significant one – those Harvard students hated the teaching machines. They found them boring. And certainly we can say “well, the technology just wasn’t very good” – but it isn’t very good now either.
Ohio State University psychology professor Sidney Pressey – he’d invented a teaching machine about a decade before B. F. Skinner did – said in 1933 that,
There must be an “industrial revolution” in education, in which educational science and the ingenuity of educational technology combine to modernize the grossly inefficient and clumsy procedures of conventional education. Work in the schools of the future will be marvelously though simply organized, so as to adjust almost automatically to individual differences and the characteristics of the learning process. There will be many labor-saving schemes and devices, and even machines – not at all for the mechanizing of education, but for the freeing of teacher and pupil from educational drudgery and incompetence.
Oh not replace you, teacher. To free you from drudgery, of course. Just like the Industrial Revolution freed workers from the drudgery of handicraft. Just like Uber drivers have been freed from the drudgery of full-time employment by becoming part of the “gig economy” and just like Uber will free them from the drudgery of precarious employment when it replaces them with autonomous vehicles.
Teaching machines – the driverless school – will replace just some education labor at first, the bits of it the engineers and their investors have deemed repetitive, menial, unimportant, and let’s be honest, those bits that are too liberal. But it doesn’t seem interested, however, in stopping students from having to do menial tasks. The “driverless university” will still mandate students sit in front of machines and click on buttons and answer multiple choice questions. “Personalized,” education will be stripped of all that is personal.
It’s a dismal future, this driverless one, and not because “the machines have taken over,” but because the libertarians who build the machines have.
A driverless future offers us only more surveillance, more algorithms, less transparency, fewer roads, and less intellectual freedom. Skinner would love it. Trump would love it. But we, we should resist it.
from Hack Education http://ift.tt/2nnseVW
“Former Lobbyist With For-Profit Colleges Quits Education Department,” ProPublica reports. That’s Taylor Hansen who was a lobbyist for Career Education Colleges and Universities. He’s the son of Bill Hansen, the son of USA Funds, another student loan guarantee agency, Inside Higher Ed notes.
Via The New York Times: “Betsy DeVos’s Hiring of For-Profit College Official Raises Impartiality Issues.” That’s Robert Eitel, a lawyer for Bridgepoint Education, a for-profit that recently settled with the federal government over charges of deceptive student lending.
Via The Atlantic: “Trump Reverses Obama-Era Protections on Student Debt.”
Via Inside Higher Ed: “Two debt collectors said in separate statements this week that they will not assess collection fees on defaulted student loan borrowers who quickly enter repayment, despite new guidance from the Department of Education.” That’s the Great Lakes Higher Education Corporation and TG.
Via PR Watch: “Betsy DeVos Ethics Report Reveals Ties to Student Debt Collection Firm.” That’s Performant Financial Co for those keeping track of who’s charging fees on student loan repayments.
Via Wired: “The Senate Prepares to Send Internet Privacy Down a Black Hole.”
Via The New York Times: “School Choice Fight in Iowa May Preview the One Facing Trump.”
Via The Atlantic: “How Betsy DeVos Could End the School-Integration Comeback.”
Representative Glenn Grothman (R-WI) claimed during a hearing before the Subcommittee on Higher Education and Workforce Development that Pell Grants discourage marriage. He also suggested low-income students spend their financial aid on “goodies and electronics.” Vote these assholes out.
Via Edsurge: “How Former NYC Mayor Michael Bloomberg’s iZone Went from ‘Cool’ to Cold.”
“A Public University Mends Fences With Its State” – that’s UW Madison mending fences with the state of Wisconsin. Mended fences according to The Chronicle of Higher Education at least.
“How Budget Battles Are Stacked Against Higher Education,” according to The Pacific Standard.
Via WBEZ News: “Chicago After-School Programs Face Axe Under Trump’s Budget.”
The state of New Jersey is poised to pass a bill that would cap public university speaker fees at $10,000. “The Snooki bill” is a response to $32,000 that the Jersey Shore star received from Rutgers in 2011.
Via The Sacramento Bee: “Lawmaker wants tuition-free college in California by taxing millionaires.”
Via The Washington Post: “ Is your school worth one star or five? D.C. officials approve new rating system.”
More on how the IER, the Department of Education’s research arm, fails to protect student data in the infosec section below.
Racism, Immigration, and Education
Via The USA Today: “Kids on winning robotics team told, ‘Go back to Mexico’.” The kids were from Pleasant Run Elementary School in Indianapolis.
Via The New York Times: “Amid ‘Trump Effect’ Fear, 40% of Colleges See Dip in Foreign Applicants.”
Education in the Courts
Via NPR: “The Supreme Court Rules In Favor Of A Special Education Student,” ruling 8–0 in Endrew F. v. Douglas County School District. “Supreme Court sets higher bar for education of students with disabilities,” says The Washington Post. More via The New York Times.
Via The Atlantic: “An Israeli American Teen Has Been Arrested in the JCC Bomb Threats Case.”
Via Chalkbeat: “After explosive allegations of anti-union intimidation, KIPP files a federal lawsuit against the UFT.”
Via Inside Higher Ed: “Princeton University filed a lawsuit against the Education Department on Friday in an effort to stop the release of hundreds of pages of documents that would reveal some of the university’s private admissions procedures.”
The Chronicle of Higher Education on the opening day of the trial of Graham Spanier, the former Penn State president for his role in ignoring the Jerry Sandusky sex abuse scandal. And The Chronicle of Higher Education on the trial’s closing arguments.
“Free college didn’t die with the Clinton campaign. It’s just getting started,” says The Hechinger Report’s Jon Marcus.
More on legislation relating to free college in the politics section above.
The “New” For-Profit Higher Ed
Via Politico: “The cost to taxpayers of the implosion of ITT Tech last fall has so far exceeded $141 million, according to court documents filed last week by attorneys representing the Education Department in the ongoing bankruptcy proceedings of the now-defunct for-profit college giant.”
“How to Con Black Law Students: A Case Study” – Elie Mystal in The New York Times on a partnership between the HBCU Bethune-Cookman and the for-profit Arizona Summit Law School. Tressie McMillan Cottom weighs in.
“Predator Colleges May Thrive Again,” says The New York Times Editorial Board.
More on for-profit lobbyists who’ve been hired by the Department of Education in the education politics section above.
Online Education and the Once and Future “MOOC”
“Coursera Removes Biometric Identity Verification Using Keystroke Matching,” Class Central reports.
An update on Coursera co-founder Andrew Ng’s employment status in the HR section below.
Meanwhile on Campus…
Buzzfeed’s Molly Hensley-Clancy reports on Camelot Education – “Inside all of Camelot’s publicly funded schools, security, order, and behavior modification take precedence over academics.”
Also via Buzzfeed, which does some of the best education reporting around right now: “A Former Student Says UC Berkeley’s Star Philosophy Professor Groped Her And Watched Porn At Work.” The accused: John R. Searle.
“Who Gets a Bathroom Pass? The History of School Bathrooms” by Jennifer Borgioli Binis.
Via Inside Higher Ed: “U of Maryland University College pursues a strategy of spinning off units into stand-alone companies, seeking financial gain for itself and affordable tuition rates for its students.”
Via The Washington Post: “The heartbreaking reason some schools never seem to grant snow days.”
Via The Guardian: “Boston public schools map switch aims to amend 500 years of distortion.” Bye, Mercator.
Via Google’s blog: “Howard University opens a new campus at the Googleplex.” It’s a three-month summer program with classes taught by Google engineers and Howard faculty.
Via The Washington Post: “Rick Perry challenges election of Texas A&M’s first gay student body president, says it was ‘stolen’ in ‘name of diversity’.” Because clearly all is well with the US nuclear arsenal and there’s nothing else the Secretary of Energy should be fussing about.
“Trump Will Deliver Keynote Address at Liberty U. Commencement,” says The Chronicle of Higher Education.
Via The New York Times: “CUNY to Revamp Remedial Programs, Hoping to Lift Graduation Rates.”
Bryan Alexander looks at the shift of Aquinas College and its shift away from offering liberal arts undergraduate degrees and back towards being a “normal school.”
“Universities are changing their business model,” Microsoft’s Ray Fleming claims. Something about unbundling.
Via The New York Times: “How the Depressed Find Solace on Yik Yak, Believe It or Not.”
Another (typical) NYT story: “Where Halls of Ivy Meet Silicon Dreams, a New City Rises.” NYU. Cornell. Columbia.
And The NYT strikes again: “How Colleges Can Admit Better Students,” writes Devin Pope. Me, I’d rather see colleges better support the students they already have.
Accreditation and Certification
“Despite the buzz, competency-based education remains a challenging market for software vendors,” says Inside Higher Ed.
“MissionU Says It Can Replace Traditional College With a One-Year Program,” Edsurge’s Jeffrey Young writes. The founder, of course, has a degree from an Ivy League school. MissionU seems like a pretty raw deal with its plan to take a cut of participants’ income. An even rawer deal: not having a (prestigious) higher ed degree when you’re not affluent, white, male. Paging Tressie McMillan Cottom.
In other news of white men with degrees arguing that folks don’t really need degrees: “Independent study, a replacement for college” by Larry Sanger. Sanger, the co-founder of Wikipedia, has a PhD incidentally.
That these sorts of stories still make headlines should prompt us to think about why and to whom credentialing matters. Via Buzzfeed: “This Biotech CEO Doesn’t Have A PhD, But He Did Leave School Under A Cloud.” That’s Gabriel Otte, ceo of Freenome, which is backed by the dukes of due diligent, Andreessen Horowitz.
Go, School Sports Team!
More on the trial of former Penn State president Graham Spanier in the courts section above.
From the HR Department
Via the MIT Technology Review: “Andrew Ng Is Leaving Baidu in Search of a Big New AI Mission.” Ng is, of course, the co-founder of the MOOC startup Coursera.
Sara Schapiro, co-founder of Digital Promise, is the new education VP at PBS.
HR news as “fake news.” Via NJ.com: “Superintendent: I’m a consultant for fed govt. Feds: We’ve never heard of this guy.” This story is something.
Via The New York Times: “Mary Maples Dunn, Advocate of Women’s Colleges, Dies at 85.”
Via Chalkbeat: “William Sanders, pioneer of controversial value-added model for judging teachers, dies.”
Contests and Awards
Maggie MacDonnell is the winner of the Varkey Foundation’s Global Teacher Prize.
More on racism at a robotics competition in the immigration section above.
This Week in Betteridge’s Law of Headlines
“Could blockchain tech make the registrar’s office obsolete?” asks Education Dive.
“ Can Silicon Valley’s autocrats save democracy?” asks the Idaho Press.
“Will Dropping the LSAT Requirement Create More Miserable Lawyers?” asks The New York Times.
(Reminder: according to Betteridge’s Law of Headlines, “Any headline that ends in a question mark can be answered by the word no.”)
Upgrades and Downgrades
— Cody Brown (@CodyBrown) March 22, 2017
Via The Verge: “Google built a new app so your kids can have a Google account, too.” This app is gross on so many levels – surveillance, privacy, data collection, behavior modification.
Google.org pledges $50 million over the next two years to support “organizations that use technology and innovation to help more children get a better education.” Edsurge covers one of them, Learning Equality, which makes educational videos and textbooks available offline.
More on UC Berkeley and publicly accessible video content. Via Phil Hill on the e-Literate blog: “Clarifications On UC Berkeley’s Accessibility Decision To Restrict Video Access.” A follow-up to the blockchain startup LBRY’s claims last week that it had rescued the videos from Mike Caulfield. “What is LBRY and what does it mean for education?” asks Bryan Alexander. Well, they’re the kind of folks who would retweet a story from William Kristol’s Weekly Standard, one that calls the ADA and Berkeley’s decision part of the “grievance industrial complex.” So they can fuck right off, IMHO.
Via the MIT Technology Review: “Controlling VR with Your Mind.”
“ VR makes a big classroom impact,” Education Dive claims.
More on how VR makes women puke in the research section below.
“A Continuum on Personalized Learning: First Draft” by Stanford professor Larry Cuban.
Via Nature: “Gates Foundation announces open-access publishing venture.”
TechDirt on ResearchGate: “Bill Gates And Other Major Investors Put $52.6 Million Into Site Sharing Unauthorized Copies Of Academic Papers.”
One of the resources I use to pull together this list of education stories has been RealClear Education. But I have to note that since the election (perhaps since editor Andrew Rotherham left for The 74) is has taken a hard, hard turn to the conspiracy-theory right. One headline it curated this week: “Colleges May Break IRS Rules With Trump-Hating” from The Washington Times (a conservative paper owned by “the Moonies”). Another headline, this one from the LA Daily News: “The Hate Group That Incited Middlebury College Melee.” That “hate group”? The Southern Poverty Law Center. (FWIW, if you’re looking for a good source of curated headlines, particularly about digital access and digital security, I recommend Doug Levin’s “A Thinking Person’s Guide to EdTech News.”)
Robots and Other Ed-Tech SF
“By 2030 students will be learning from robots,” the World Economic Forum claims. Hopefully it’s not the robots that power Google’s search algorithm. (See the upgrades/downgrades section above.)
“Living with an AI: A Glimpse Into The Future” by The Scholarly Kitchen’s David Smith.
More on AI expert Andrew Ng in the HR section above.
Venture Capital and the Business of Ed-Tech
WayUp has raised $18.5 million in Series B funding from Trinity Ventures, Axel Springer, BoxGroup, CAA Ventures, Female Founders Fund, General Catalyst, Index Ventures, Lerer Hippeau Ventures, OurCrowd-GCai, and SV Angel. The startup, which offers a job placement marketplace for college students has raised $27.47 million total.
Tutoring company Nactus has raised an undisclosed amount of funding from Sandeep Aggarwal, Gautam Chhaochharia, and R Balachandar.
Education Brands has acquired Ravenna Solutions.
Testing companies Taskstream and Tk20 are merging.
Privacy, Surveillance, and Information Security
Via Krebs on Security: “Student Aid Tool Held Key for Tax Fraudsters.” This is an update on the FAFSA / IRS tool.
Via the Go to Hellman blog: “Reader Privacy for Research Journals is Getting Worse.”
Via The Register Guard: “Virus possibly exposes Lane Community College data.” Specifically, data from its health clinic.
Via The Hechinger Report: “Schools collect reams of data, inspiring a move to make sense of it all.” (Or! Or! You could not collect it if you don’t need it.)
Via Education Week: “With Hacking in Headlines, K–12 Cybersecurity Ed. Gets More Attention.”
“Internet of Things could have eventual data-collection impact on K–12,” says Education Dive.
Via the AP: “Google Maps already tracks you; now other people can, too.”
Via Education Week: “The U.S. Department of Education’s office of inspector general has released an audit sharply critiquing the Institute of Education Sciences’ security screenings for federal education contractors.”
Data and “Research”
“Placement rates, other data colleges provide consumers are often alternative facts,” says The Hechinger Report.
“Do After-School Programs Positively Impact Children?” asks The Atlantic. “Proponents of President Trump’s budget say no. Their evidence may be faulty.”
Via NPR: “Kids Who Suffer Hunger In First Years Lag Behind Their Peers In School.”
Via Quartz: “Stanford researchers show we’re sending many children to school way too early.” Or! Or! We could make kindergarten kindergarten again.
The Atlantic writes about a Century Foundation report on private school vouchers and segregation.
The Atlantic also covers research linking food quality and student achievement.
Via New World Notes: “Confirming danah boyd’s Early Concerns, Studies Suggest Women Much More Likely to Get Motion Sickness from Using VR.”
Via Inside Higher Ed: “Report on Role of College Search-and-Review Sites.”
Via the Foundation Center: “Visualizing Funding for Libraries,” a database of library funding.
Via Inside Higher Ed: “Internet speeds at colleges have nearly tripled since 2012 as IT departments have fought to keep up with students bringing new internet-connected devices to campus, streaming music and video, and gaming online, a new study found.”
Via The Dallas Morning News: “15 percent of female undergraduates at UT have been raped, survey says.”
Via NPR: “The Earth Is Flat? Check Wikipedia.” Shaq. Dude. Check Wikipedia.
Also via NPR: “You Probably Believe Some Learning Myths: Take Our Quiz To Find Out.”
Icon credits: The Noun Project
from Hack Education http://ift.tt/2nwj2RU