A Silicon Valley scheme to “disrupt” America’s education system would hurt the people who need it the most

The plot to destroy education: Why technology could ruin American classrooms — by trying to fix them

The plot to destroy education: Why technology could ruin American classrooms — by trying to fix them
(Credit: Warner Bros. Entertainment Inc./Pgiam via iStock/Salon)

How does Silicon Valley feel about college? Here’s a taste: Seven words in a tweet provoked by a conversation about education started by Silicon Valley venture capitalist Marc Andreeseen.

Arrogance? Check. Supreme confidence? Check. Oblivious to the value actually provided by a college education? Check.

The $400 billion a year that Americans pay for education after high school is being wasted on an archaic brick-and-mortar irrelevance. We can do better! 

But how? The question becomes more pertinent every day — and it’s one that Silicon Valley would dearly like to answer.

The robots are coming for our jobs, relentlessly working their way up the value chain. Anything that can be automated will be automated. The obvious — and perhaps the only — answer to this threat is a vastly improved educational system. We’ve got to leverage our human intelligence to stay ahead of robotic A.I.! And right now, everyone agrees, the system is not meeting the challenge. The cost of a traditional four-year college education has far outpaced inflation. Student loan debt is a national tragedy. Actually achieving a college degree still bequeaths better job prospects than the alternative, but for many students, the cost-benefit ratio is completely out of whack.

No problem, says the tech industry. Like a snake eating its own tail, Silicon Valley has the perfect solution for the social inequities caused by technologically induced “disruption.” More disruption!

Universities are a hopelessly obsolete way to go about getting an education when we’ve got the Internet, the argument goes. Just as Airbnb is disemboweling the hotel industry and Uber is annihilating the taxi industry, companies such as Coursera and Udacity will leverage technology and access to venture capital in order to crush the incumbent education industry, supposedly offering high-quality educational opportunities for a fraction of the cost of a four-year college.



There is an elegant logic to this argument. We’ll use the Internet to stay ahead of the Internet. Awesome tools are at our disposal. In MOOCs — “Massive Open Online Courses” — hundreds of thousands of students will imbibe the wisdom of Ivy League “superprofessors” via pre-recorded lectures piped down to your smartphone. No need even for overworked graduate student teaching assistants. Intelligent software will take care of the grading. (That’s right — we’ll use robots to meet the robot threat!) The market, in other words, will provide the solution to the problem that the market has caused. It’s a wonderful libertarian dream.

But there’s a flaw in the logic. Early returns on MOOCs have confirmed what just about any teacher could have told you before Silicon Valley started believing it could “fix” education. Real human interaction and engagement are hugely important to delivering a quality education. Most crucially, hands-on interaction with teachers is vital for the students who are in most desperate need for an education — those with the least financial resources and the most challenging backgrounds.

Of course, it costs money to provide greater human interaction. You need bodies — ideally, bodies with some mastery of the subject material. But when you raise costs, you destroy the primary attraction of Silicon Valley’s “disruptive” model. The big tech success stories are all about avoiding the costs faced by the incumbents. Airbnb owns no hotels. Uber owns no taxis. The selling point of Coursera and Udacity is that they need own no universities.

But education is different than running a hotel. There’s a reason why governments have historically considered providing education a public good. When you start throwing bodies into the fray to teach people who can’t afford a traditional private education you end up disastrously chipping away at the profits that the venture capitalists backing Coursera and Udacity demand.

And that’s a tail that the snake can’t swallow.

* * *

The New York Times famously dubbed 2012 “The Year of the MOOC.” Coursera and Udacity (both started by Stanford professors) and an MIT-Harvard collaboration called EdX exploded into the popular imagination. But the hype ebbed almost as quickly as it had flowed. In 2013, after a disastrous pilot experiment in which Udacity and San Jose State collaborated to deliver three courses, MOOCs were promptly declared dead — with the harshest schadenfreude coming from academics who saw the rush to MOOCs as an educational travesty.

At the end of 2013, the New York Times had changed its tune: “After Setbacks, Online Courses are Rethought.”

But MOOC supporters have never wavered. In May, Clayton Christensen, the high priest of “disruption” theory, scoffed at the unbelievers: ”[T]heir potential to disrupt — on price, technology, even pedagogy — in a long-stagnant industry,” wrote Christensen, ” is only just beginning to be seen.”

At the end of June, the Economist followed suit with a package of stories touting the inevitable “creative destruction” threatened by MOOCs: “[A] revolution has begun thanks to three forces: rising costs, changing demand and disruptive technology. The result will be the reinvention of the university …” It’s 2012 all over again!

Sure, there have been speed bumps along the way. But as Christensen explained, the same is true for any would-be disruptive start-up. Failures are bound to happen. What makes Silicon Valley so special is its ability to learn from mistakes, tweak its biz model and try something new. It’s called “iteration.”

There is, of course, great merit to the iterative process. And it would be foolish to claim that new technology won’t have an impact on the educational process. If there’s one thing that the Internet and smartphones are insanely good at, it is providing access to information. A teenager with a phone in Uganda has opportunities for learning that most of the world never had through the entire course of human history. That’s great.

But there’s a crucial difference between “access to information” and “education” that explains why the university isn’t about to become obsolete, and why we can’t depend — as Marc Andreessen tells us — on the magic elixir of innovation plus the free market to solve our education quandary.

Nothing better illustrates this point than a closer look at the Udacity-San Jose State collaboration.

* * *

When Gov. Jerry Brown announced the collaboration between Udacity, founded by the Stanford computer science Sebastian Thrun and San Jose State, a publicly funded university in the heart of Silicon Valley, in January 2013, the match seemed perfect. Where else would you want to test out the future of education? The plan was to focus on three courses: elementary statistics, remedial math and college algebra. The target student demographic was notoriously ill-served by the university system: “Students were drawn from a lower-income high school and the underperforming ranks of SJSU’s student body,” reported Fast Company.

The results of the pilot, conducted in the spring of 2013, were a disaster, reported Fast Company:

Among those pupils who took remedial math during the pilot program, just 25 percent passed. And when the online class was compared with the in-person variety, the numbers were even more discouraging. A student taking college algebra in person was 52 percent more likely to pass than one taking a Udacity class, making the $150 price tag–roughly one-third the normal in-state tuition–seem like something less than a bargain.

A second attempt during the summer achieved better results, but with a much less disadvantaged student body; and, even more crucially, with considerably greater resources put into human interaction and oversight. For example, San Jose State reported that the summer courses were improved by “checking in with students more often.”

But the prime takeaway was stark. Inside Higher Education reported that a research report conducted by San Jose State on the experiment concluded that “it may be difficult for the university to deliver online education in this format to the students who need it most.”

In an iterative world, San Jose State and Udacity would have learned from their mistakes. The next version of their collaboration would have incorporated the increased human resources necessary to make it work, to be sure that students didn’t fall through the cracks. But the lesson that Udacity learned from the collaboration turned out be something different: There isn’t going to be much profit to be made attempting to apply the principles of MOOCs to students from a disadvantaged background.

Thrun set off a firestorm of commentary when he told Fast Company’s Max Chafkin this:

“These were students from difficult neighborhoods, without good access to computers, and with all kinds of challenges in their lives,” he says. “It’s a group for which this medium is not a good fit….”

“I’d aspired to give people a profound education–to teach them something substantial… But the data was at odds with this idea.”

Henceforth, Udacity would “pivot” to focusing on vocational training funded by direct corporate support.

Thrun later claimed that his comments were misinterpreted by Fast Company. And in his May Op-Ed Christensen argued that Udacity’s pivot was a boon!

Udacity, for its part, should be applauded for not burning through all of its money in pursuit of the wrong strategy. The company realized — and publicly acknowledged — that its future lay on a different path than it had originally anticipated. Indeed, Udacity’s pivot may have even prevented a MOOC bubble from bursting.

Educating the disadvantaged via MOOCs is the wrong strategy? That’s not a pivot — it’s an abject surrender.

The Economist, meanwhile, brushed off the San Jose State episode by noting that “online learning has its pitfalls.” But the Economist also published a revealing observation: “In some ways MOOCs will reinforce inequality … among students (the talented will be much more comfortable than the weaker outside the structured university environment) …”

But isn’t that exactly the the problem? No one can deny that the access to information facilitated by the Internet is a fantastic thing for talented students — and particularly so for those with secure economic backgrounds and fast Internet connections. But such people are most likely to succeed in a world full of smart robots anyway. The challenge posed by technological transformation and disruption is that the jobs that are being automated away first are the ones that are most suited to the less talented or advantaged. In other words, the population that MOOCs are least suited to serving is the population that technology is putting in the most vulnerable position.

Innovation and the free market aren’t going to fix this problem, for the very simple reason that there is no money in it. There’s no profit to be mined in educating people who not only can’t pay for an education, but also require greater human resources to be educated.

This is why we have public education in the first place.

“College is a public good,” says Jonathan Rees, a professor at Colorado State University who has been critical of MOOCs. “It’s what industrialized democratic society should be providing for students.”

Andrew Leonard Andrew Leonard is a staff writer at Salon. On Twitter, @koxinga21.

Former State Department employee reveals spying on Americans by executive order

http://usofarn.com/wp-content/uploads/2013/08/nsa-prism1.jpg

By Ed Hightower
25 July 2014

In the latest revelation of unconstitutional spying on US citizens by the National Security Agency (NSA), former State Department employee John Napier Tye has given his account of ongoing violations of privacy under cover of a legal fig leaf known as Executive Order 12333.

Last week the Washington Post published Tye’s lengthy criticism of the Obama administration under the title “Meet Executive Order 12333: The Reagan rule that lets the NSA spy on Americans.” The editorial underscores both the immense scope of illegal spying by an unaccountable military-intelligence apparatus and the sham character of the official “reform.”

President Ronald Reagan enacted Executive Order 12333 in 1981. The order was aimed at providing a lax legal standard for the collection of communication content —not just metadata such as call logs—of US citizens, as long as the communication was not obtained within the United States.

While 12333 was legally dubious even in 1981, it was not until the widespread transfer of data over the internet that it could be exploited for the mass collection of communications. Enormous amounts of data and communications generated by Americans in the form of emails, for example, are now routinely routed to servers all over the world, bringing the data within the now much broader reach of 12333.

Tye’s editorial calls attention to 12333, saying that the order is now used to justify possibly more illegal surveillance than Section 215 of the Patriot Act, which sanctions bulk collection of telecommunications records. While Section 215 has garnered more public attention, Tye argues that it “is a small part of the picture and does not include the universe of collection and storage of communications by US persons authorized under Executive Order 12333.”

Referring to “classified facts that I am prohibited by law from publishing,” Tye writes, “I believe that Americans should be even more concerned about the collection and storage of their communications under Executive Order 12333 than under Section 215 [of the Patriot Act].”

Because it is an executive order as opposed to a statute, 12333 is subject to virtually zero oversight. The attorney general, who is part of the executive branch and serves at the pleasure of the president, determines what restraints, if any, apply. Currently, intelligence agencies are permitted to keep data obtained pursuant to 12333 for up to five years.

Nor does 12333 typically require a warrant. Tye explains that the NSA keeps data obtained through 12333 even if it is not directly related to a surveillance target who was subject to a warrant. This so-called “incidental” collection represents the exception that swallows the rule.

As Tye describes it, incidental collection is “a legal loophole that can be stretched very wide. Remember that the NSA is building a data center in Utah five times the size of the U.S. Capitol building, with its own power plant that will reportedly burn $40 million a year in electricity. ‘Incidental collection’ might need its own power plant.”

Tye worked for the State Department from 2011 until this past April. He currently serves as legal director for the nonprofit advocacy group Avaaz. His Post article was reviewed and cleared by the State Department and NSA prior to publication. Before he left his State Department job, Tye filed a complaint about 12333-related spying with the department’s inspector general, and he eventually brought this complaint to the House and Senate intelligence committees, as well as to the inspector general of the NSA.

While Tye did not leak any documents or data to the press, it is clear that what he saw and heard at the State Department deeply troubled him.

He begins his Washington Post piece with this disturbing anecdote:

“In March I received a call from the White House counsel’s office regarding a speech I had prepared for my boss at the State Department… The draft stated that ‘if U.S. citizens disagree with congressional and executive branch determinations about the proper scope of signals intelligence activities, they have the opportunity to change the policy through our democratic process.’”

“But the White House counsel’s office told me that no, that wasn’t true. I was instructed to amend the line, making a general reference to ‘our laws and policies,’ rather than our intelligence practices. I did.”

In other words, Tye was directed to remove from his speech something that might give the misleading impression that the US population has any meaningful oversight where the military-intelligence apparatus is concerned.

In his op-ed comment, Tye also points out the Obama administration’s “reforms” are bogus. Obama’s Review Group on Intelligence and Communications Technologies recommended that data obtained by incidental collection should be purged. Tye writes that an unclassified document he saw while working with the State Department made the White House’s position clear: there were no plans to change the practices around Executive Order 12333.

The terrifying uncertainty of our high-tech future

Our new robot overlords:

Are computers taking our jobs?

Our new robot overlords: The terrifying uncertainty of our high-tech future
(Credit: Ociacia, MaraZe via Shutterstock/Salon)
This article was originally published by Scientific American.

Scientific American Last fall economist Carl Benedikt Frey and information engineer Michael A. Osborne, both at the University of Oxford, published a study estimating the probability that 702 occupations would soon be computerized out of existence. Their findings were startling. Advances in data mining, machine vision, artificial intelligence and other technologies could, they argued, put 47 percent of American jobs at high risk of being automated in the years ahead. Loan officers, tax preparers, cashiers, locomotive engineers, paralegals, roofers, taxi drivers and even animal breeders are all in danger of going the way of the switchboard operator.

Whether or not you buy Frey and Osborne’s analysis, it is undeniable that something strange is happening in the U.S. labor market. Since the end of the Great Recession, job creation has not kept up with population growth. Corporate profits have doubled since 2000, yet median household income (adjusted for inflation) dropped from $55,986 to $51,017. At the same time, after-tax corporate profits as a share of gross domestic product increased from around 5 to 11 percent, while compensation of employees as a share of GDP dropped from around 47 to 43 percent. Somehow businesses are making more profit with fewer workers.

Erik Brynjolfsson and Andrew McAfee, both business researchers at the Massachusetts Institute of Technology, call this divergence the “great decoupling.” In their view, presented in their recent book “The Second Machine Age,” it is a historic shift.

The conventional economic wisdom has long been that as long as productivity is increasing, all is well. Technological innovations foster higher productivity, which leads to higher incomes and greater well-being for all. And for most of the 20th century productivity and incomes did rise in parallel. But in recent decades the two began to diverge. Productivity kept increasing while incomes—which is to say, the welfare of individual workers—stagnated or dropped.

Brynjolfsson and McAfee argue that technological advances are destroying jobs, particularly low-skill jobs, faster than they are creating them. They cite research showing that so-called routine jobs (bank teller, machine operator, dressmaker) began to fade in the 1980s, when computers first made their presence known, but that the rate has accelerated: between 2001 and 2011, 11 percent of routine jobs disappeared.



Plenty of economists disagree, but it is hard to referee this debate, in part because of a lack of data. Our understanding of the relation between technological advances and employment is limited by outdated metrics. At a roundtable discussion on technology and work convened this year by the European Union, the IRL School at Cornell University and the Conference Board (a business research association), a roomful of economists and financiers repeatedly emphasized how many basic economic variables are measured either poorly or not at all. Is productivity declining? Or are we simply measuring it wrong? Experts differ. What kinds of workers are being sidelined, and why? Could they get new jobs with the right retraining? Again, we do not know.

In 2013 Brynjolfsson told Scientific American that the first step in reckoning with the impact of automation on employment is to diagnose it correctly—“to understand why the economy is changing and why people aren’t doing as well as they used to.” If productivity is no longer a good proxy for a vigorous economy, then we need a new way to measure economic health. In a 2009 report economists Joseph Stiglitz of Columbia University, Amartya Sen of Harvard University and Jean-Paul Fitoussi of the Paris Institute of Political Studies made a similar case, writing that “the time is ripe for our measurement system to shift emphasis from measuring economic production to measuring people’s well-being.” An IRL School report last year called for statistical agencies to capture more and better data on job market churn—data that could help us learn which job losses stem from automation.

Without such data, we will never properly understand how technology is changing the nature of work in the 21st century—and what, if anything, should be done about it. As one participant in this year’s roundtable put it, “Even if this is just another industrial revolution, people underestimate how wrenching that is. If it is, what are the changes to the rules of labor markets and businesses that should be made this time? We made a lot last time. What is the elimination of child labor this time? What is the eight-hour workday this time?”

 

The rise of data and the death of politics

Tech pioneers in the US are advocating a new data-based approach to governance – ‘algorithmic regulation’. But if technology provides the answers to society’s problems, what happens to governments?

US president Barack Obama with Facebook founder Mark Zuckerberg

Government by social network? US president Barack Obama with Facebook founder Mark Zuckerberg. Photograph: Mandel Ngan/AFP/Getty Images

On 24 August 1965 Gloria Placente, a 34-year-old resident of Queens, New York, was driving to Orchard Beach in the Bronx. Clad in shorts and sunglasses, the housewife was looking forward to quiet time at the beach. But the moment she crossed the Willis Avenue bridge in her Chevrolet Corvair, Placente was surrounded by a dozen patrolmen. There were also 125 reporters, eager to witness the launch of New York police department’s Operation Corral – an acronym for Computer Oriented Retrieval of Auto Larcenists.

Fifteen months earlier, Placente had driven through a red light and neglected to answer the summons, an offence that Corral was going to punish with a heavy dose of techno-Kafkaesque. It worked as follows: a police car stationed at one end of the bridge radioed the licence plates of oncoming cars to a teletypist miles away, who fed them to a Univac 490 computer, an expensive $500,000 toy ($3.5m in today’s dollars) on loan from the Sperry Rand Corporation. The computer checked the numbers against a database of 110,000 cars that were either stolen or belonged to known offenders. In case of a match the teletypist would alert a second patrol car at the bridge’s other exit. It took, on average, just seven seconds.

Compared with the impressive police gear of today – automatic number plate recognition, CCTV cameras, GPS trackers – Operation Corral looks quaint. And the possibilities for control will only expand. European officials have considered requiring all cars entering the European market to feature a built-in mechanism that allows the police to stop vehicles remotely. Speaking earlier this year, Jim Farley, a senior Ford executive, acknowledged that “we know everyone who breaks the law, we know when you’re doing it. We have GPS in your car, so we know what you’re doing. By the way, we don’t supply that data to anyone.” That last bit didn’t sound very reassuring and Farley retracted his remarks.

As both cars and roads get “smart,” they promise nearly perfect, real-time law enforcement. Instead of waiting for drivers to break the law, authorities can simply prevent the crime. Thus, a 50-mile stretch of the A14 between Felixstowe and Rugby is to be equipped with numerous sensors that would monitor traffic by sending signals to and from mobile phones in moving vehicles. The telecoms watchdog Ofcom envisions that such smart roads connected to a centrally controlled traffic system could automatically impose variable speed limits to smooth the flow of traffic but also direct the cars “along diverted routes to avoid the congestion and even [manage] their speed”.

Other gadgets – from smartphones to smart glasses – promise even more security and safety. In April, Apple patented technology that deploys sensors inside the smartphone to analyse if the car is moving and if the person using the phone is driving; if both conditions are met, it simply blocks the phone’s texting feature. Intel and Ford are working on Project Mobil – a face recognition system that, should it fail to recognise the face of the driver, would not only prevent the car being started but also send the picture to the car’s owner (bad news for teenagers).

The car is emblematic of transformations in many other domains, from smart environments for “ambient assisted living” where carpets and walls detect that someone has fallen, to various masterplans for the smart city, where municipal services dispatch resources only to those areas that need them. Thanks to sensors and internet connectivity, the most banal everyday objects have acquired tremendous power to regulate behaviour. Even public toilets are ripe for sensor-based optimisation: the Safeguard Germ Alarm, a smart soap dispenser developed by Procter & Gamble and used in some public WCs in the Philippines, has sensors monitoring the doors of each stall. Once you leave the stall, the alarm starts ringing – and can only be stopped by a push of the soap-dispensing button.

In this context, Google’s latest plan to push its Android operating system on to smart watches, smart cars, smart thermostats and, one suspects, smart everything, looks rather ominous. In the near future, Google will be the middleman standing between you and your fridge, you and your car, you and your rubbish bin, allowing the National Security Agency to satisfy its data addiction in bulk and via a single window.

This “smartification” of everyday life follows a familiar pattern: there’s primary data – a list of what’s in your smart fridge and your bin – and metadata – a log of how often you open either of these things or when they communicate with one another. Both produce interesting insights: cue smart mattresses – one recent model promises to track respiration and heart rates and how much you move during the night – and smart utensils that provide nutritional advice.

In addition to making our lives more efficient, this smart world also presents us with an exciting political choice. If so much of our everyday behaviour is already captured, analysed and nudged, why stick with unempirical approaches to regulation? Why rely on laws when one has sensors and feedback mechanisms? If policy interventions are to be – to use the buzzwords of the day – “evidence-based” and “results-oriented,” technology is here to help.

This new type of governance has a name: algorithmic regulation. In as much as Silicon Valley has a political programme, this is it. Tim O’Reilly, an influential technology publisher, venture capitalist and ideas man (he is to blame for popularising the term “web 2.0″) has been its most enthusiastic promoter. In a recent essay that lays out his reasoning, O’Reilly makes an intriguing case for the virtues of algorithmic regulation – a case that deserves close scrutiny both for what it promises policymakers and the simplistic assumptions it makes about politics, democracy and power.

To see algorithmic regulation at work, look no further than the spam filter in your email. Instead of confining itself to a narrow definition of spam, the email filter has its users teach it. Even Google can’t write rules to cover all the ingenious innovations of professional spammers. What it can do, though, is teach the system what makes a good rule and spot when it’s time to find another rule for finding a good rule – and so on. An algorithm can do this, but it’s the constant real-time feedback from its users that allows the system to counter threats never envisioned by its designers. And it’s not just spam: your bank uses similar methods to spot credit-card fraud.

In his essay, O’Reilly draws broader philosophical lessons from such technologies, arguing that they work because they rely on “a deep understanding of the desired outcome” (spam is bad!) and periodically check if the algorithms are actually working as expected (are too many legitimate emails ending up marked as spam?).

O’Reilly presents such technologies as novel and unique – we are living through a digital revolution after all – but the principle behind “algorithmic regulation” would be familiar to the founders of cybernetics – a discipline that, even in its name (it means “the science of governance”) hints at its great regulatory ambitions. This principle, which allows the system to maintain its stability by constantly learning and adapting itself to the changing circumstances, is what the British psychiatrist Ross Ashby, one of the founding fathers of cybernetics, called “ultrastability”.

To illustrate it, Ashby designed the homeostat. This clever device consisted of four interconnected RAF bomb control units – mysterious looking black boxes with lots of knobs and switches – that were sensitive to voltage fluctuations. If one unit stopped working properly – say, because of an unexpected external disturbance – the other three would rewire and regroup themselves, compensating for its malfunction and keeping the system’s overall output stable.

Ashby’s homeostat achieved “ultrastability” by always monitoring its internal state and cleverly redeploying its spare resources.

Like the spam filter, it didn’t have to specify all the possible disturbances – only the conditions for how and when it must be updated and redesigned. This is no trivial departure from how the usual technical systems, with their rigid, if-then rules, operate: suddenly, there’s no need to develop procedures for governing every contingency, for – or so one hopes – algorithms and real-time, immediate feedback can do a better job than inflexible rules out of touch with reality.

Algorithmic regulation could certainly make the administration of existing laws more efficient. If it can fight credit-card fraud, why not tax fraud? Italian bureaucrats have experimented with the redditometro, or income meter, a tool for comparing people’s spending patterns – recorded thanks to an arcane Italian law – with their declared income, so that authorities know when you spend more than you earn. Spain has expressed interest in a similar tool.

Such systems, however, are toothless against the real culprits of tax evasion – the super-rich families who profit from various offshoring schemes or simply write outrageous tax exemptions into the law. Algorithmic regulation is perfect for enforcing the austerity agenda while leaving those responsible for the fiscal crisis off the hook. To understand whether such systems are working as expected, we need to modify O’Reilly’s question: for whom are they working? If it’s just the tax-evading plutocrats, the global financial institutions interested in balanced national budgets and the companies developing income-tracking software, then it’s hardly a democratic success.

With his belief that algorithmic regulation is based on “a deep understanding of the desired outcome”, O’Reilly cunningly disconnects the means of doing politics from its ends. But the how of politics is as important as the what of politics – in fact, the former often shapes the latter. Everybody agrees that education, health, and security are all “desired outcomes”, but how do we achieve them? In the past, when we faced the stark political choice of delivering them through the market or the state, the lines of the ideological debate were clear. Today, when the presumed choice is between the digital and the analog or between the dynamic feedback and the static law, that ideological clarity is gone – as if the very choice of how to achieve those “desired outcomes” was apolitical and didn’t force us to choose between different and often incompatible visions of communal living.

By assuming that the utopian world of infinite feedback loops is so efficient that it transcends politics, the proponents of algorithmic regulation fall into the same trap as the technocrats of the past. Yes, these systems are terrifyingly efficient – in the same way that Singapore is terrifyingly efficient (O’Reilly, unsurprisingly, praises Singapore for its embrace of algorithmic regulation). And while Singapore’s leaders might believe that they, too, have transcended politics, it doesn’t mean that their regime cannot be assessed outside the linguistic swamp of efficiency and innovation – by using political, not economic benchmarks.

As Silicon Valley keeps corrupting our language with its endless glorification of disruption and efficiency – concepts at odds with the vocabulary of democracy – our ability to question the “how” of politics is weakened. Silicon Valley’s default answer to the how of politics is what I call solutionism: problems are to be dealt with via apps, sensors, and feedback loops – all provided by startups. Earlier this year Google’s Eric Schmidt even promised that startups would provide the solution to the problem of economic inequality: the latter, it seems, can also be “disrupted”. And where the innovators and the disruptors lead, the bureaucrats follow.

The intelligence services embraced solutionism before other government agencies. Thus, they reduced the topic of terrorism from a subject that had some connection to history and foreign policy to an informational problem of identifying emerging terrorist threats via constant surveillance. They urged citizens to accept that instability is part of the game, that its root causes are neither traceable nor reparable, that the threat can only be pre-empted by out-innovating and out-surveilling the enemy with better communications.

Speaking in Athens last November, the Italian philosopher Giorgio Agamben discussed an epochal transformation in the idea of government, “whereby the traditional hierarchical relation between causes and effects is inverted, so that, instead of governing the causes – a difficult and expensive undertaking – governments simply try to govern the effects”.

Nobel laureate Daniel Kahneman

Governments’ current favourite pyschologist, Daniel Kahneman. Photograph: Richard Saker for the Observer
For Agamben, this shift is emblematic of modernity. It also explains why the liberalisation of the economy can co-exist with the growing proliferation of control – by means of soap dispensers and remotely managed cars – into everyday life. “If government aims for the effects and not the causes, it will be obliged to extend and multiply control. Causes demand to be known, while effects can only be checked and controlled.” Algorithmic regulation is an enactment of this political programme in technological form.The true politics of algorithmic regulation become visible once its logic is applied to the social nets of the welfare state. There are no calls to dismantle them, but citizens are nonetheless encouraged to take responsibility for their own health. Consider how Fred Wilson, an influential US venture capitalist, frames the subject. “Health… is the opposite side of healthcare,” he said at a conference in Paris last December. “It’s what keeps you out of the healthcare system in the first place.” Thus, we are invited to start using self-tracking apps and data-sharing platforms and monitor our vital indicators, symptoms and discrepancies on our own.This goes nicely with recent policy proposals to save troubled public services by encouraging healthier lifestyles. Consider a 2013 report by Westminster council and the Local Government Information Unit, a thinktank, calling for the linking of housing and council benefits to claimants’ visits to the gym – with the help of smartcards. They might not be needed: many smartphones are already tracking how many steps we take every day (Google Now, the company’s virtual assistant, keeps score of such data automatically and periodically presents it to users, nudging them to walk more).

The numerous possibilities that tracking devices offer to health and insurance industries are not lost on O’Reilly. “You know the way that advertising turned out to be the native business model for the internet?” he wondered at a recent conference. “I think that insurance is going to be the native business model for the internet of things.” Things do seem to be heading that way: in June, Microsoft struck a deal with American Family Insurance, the eighth-largest home insurer in the US, in which both companies will fund startups that want to put sensors into smart homes and smart cars for the purposes of “proactive protection”.

An insurance company would gladly subsidise the costs of installing yet another sensor in your house – as long as it can automatically alert the fire department or make front porch lights flash in case your smoke detector goes off. For now, accepting such tracking systems is framed as an extra benefit that can save us some money. But when do we reach a point where not using them is seen as a deviation – or, worse, an act of concealment – that ought to be punished with higher premiums?

Or consider a May 2014 report from 2020health, another thinktank, proposing to extend tax rebates to Britons who give up smoking, stay slim or drink less. “We propose ‘payment by results’, a financial reward for people who become active partners in their health, whereby if you, for example, keep your blood sugar levels down, quit smoking, keep weight off, [or] take on more self-care, there will be a tax rebate or an end-of-year bonus,” they state. Smart gadgets are the natural allies of such schemes: they document the results and can even help achieve them – by constantly nagging us to do what’s expected.

The unstated assumption of most such reports is that the unhealthy are not only a burden to society but that they deserve to be punished (fiscally for now) for failing to be responsible. For what else could possibly explain their health problems but their personal failings? It’s certainly not the power of food companies or class-based differences or various political and economic injustices. One can wear a dozen powerful sensors, own a smart mattress and even do a close daily reading of one’s poop – as some self-tracking aficionados are wont to do – but those injustices would still be nowhere to be seen, for they are not the kind of stuff that can be measured with a sensor. The devil doesn’t wear data. Social injustices are much harder to track than the everyday lives of the individuals whose lives they affect.

In shifting the focus of regulation from reining in institutional and corporate malfeasance to perpetual electronic guidance of individuals, algorithmic regulation offers us a good-old technocratic utopia of politics without politics. Disagreement and conflict, under this model, are seen as unfortunate byproducts of the analog era – to be solved through data collection – and not as inevitable results of economic or ideological conflicts.

However, a politics without politics does not mean a politics without control or administration. As O’Reilly writes in his essay: “New technologies make it possible to reduce the amount of regulation while actually increasing the amount of oversight and production of desirable outcomes.” Thus, it’s a mistake to think that Silicon Valley wants to rid us of government institutions. Its dream state is not the small government of libertarians – a small state, after all, needs neither fancy gadgets nor massive servers to process the data – but the data-obsessed and data-obese state of behavioural economists.

The nudging state is enamoured of feedback technology, for its key founding principle is that while we behave irrationally, our irrationality can be corrected – if only the environment acts upon us, nudging us towards the right option. Unsurprisingly, one of the three lonely references at the end of O’Reilly’s essay is to a 2012 speech entitled “Regulation: Looking Backward, Looking Forward” by Cass Sunstein, the prominent American legal scholar who is the chief theorist of the nudging state.

And while the nudgers have already captured the state by making behavioural psychology the favourite idiom of government bureaucracy –Daniel Kahneman is in, Machiavelli is out – the algorithmic regulation lobby advances in more clandestine ways. They create innocuous non-profit organisations like Code for America which then co-opt the state – under the guise of encouraging talented hackers to tackle civic problems.

Airbnb's homepage.

Airbnb: part of the reputation-driven economy.
Such initiatives aim to reprogramme the state and make it feedback-friendly, crowding out other means of doing politics. For all those tracking apps, algorithms and sensors to work, databases need interoperability – which is what such pseudo-humanitarian organisations, with their ardent belief in open data, demand. And when the government is too slow to move at Silicon Valley’s speed, they simply move inside the government. Thus, Jennifer Pahlka, the founder of Code for America and a protege of O’Reilly, became the deputy chief technology officer of the US government – while pursuing a one-year “innovation fellowship” from the White House.Cash-strapped governments welcome such colonisation by technologists – especially if it helps to identify and clean up datasets that can be profitably sold to companies who need such data for advertising purposes. Recent clashes over the sale of student and health data in the UK are just a precursor of battles to come: after all state assets have been privatised, data is the next target. For O’Reilly, open data is “a key enabler of the measurement revolution”.This “measurement revolution” seeks to quantify the efficiency of various social programmes, as if the rationale behind the social nets that some of them provide was to achieve perfection of delivery. The actual rationale, of course, was to enable a fulfilling life by suppressing certain anxieties, so that citizens can pursue their life projects relatively undisturbed. This vision did spawn a vast bureaucratic apparatus and the critics of the welfare state from the left – most prominently Michel Foucault – were right to question its disciplining inclinations. Nonetheless, neither perfection nor efficiency were the “desired outcome” of this system. Thus, to compare the welfare state with the algorithmic state on those grounds is misleading.

But we can compare their respective visions for human fulfilment – and the role they assign to markets and the state. Silicon Valley’s offer is clear: thanks to ubiquitous feedback loops, we can all become entrepreneurs and take care of our own affairs! As Brian Chesky, the chief executive of Airbnb, told the Atlantic last year, “What happens when everybody is a brand? When everybody has a reputation? Every person can become an entrepreneur.”

Under this vision, we will all code (for America!) in the morning, drive Uber cars in the afternoon, and rent out our kitchens as restaurants – courtesy of Airbnb – in the evening. As O’Reilly writes of Uber and similar companies, “these services ask every passenger to rate their driver (and drivers to rate their passenger). Drivers who provide poor service are eliminated. Reputation does a better job of ensuring a superb customer experience than any amount of government regulation.”

The state behind the “sharing economy” does not wither away; it might be needed to ensure that the reputation accumulated on Uber, Airbnb and other platforms of the “sharing economy” is fully liquid and transferable, creating a world where our every social interaction is recorded and assessed, erasing whatever differences exist between social domains. Someone, somewhere will eventually rate you as a passenger, a house guest, a student, a patient, a customer. Whether this ranking infrastructure will be decentralised, provided by a giant like Google or rest with the state is not yet clear but the overarching objective is: to make reputation into a feedback-friendly social net that could protect the truly responsible citizens from the vicissitudes of deregulation.

Admiring the reputation models of Uber and Airbnb, O’Reilly wants governments to be “adopting them where there are no demonstrable ill effects”. But what counts as an “ill effect” and how to demonstrate it is a key question that belongs to the how of politics that algorithmic regulation wants to suppress. It’s easy to demonstrate “ill effects” if the goal of regulation is efficiency but what if it is something else? Surely, there are some benefits – fewer visits to the psychoanalyst, perhaps – in not having your every social interaction ranked?

The imperative to evaluate and demonstrate “results” and “effects” already presupposes that the goal of policy is the optimisation of efficiency. However, as long as democracy is irreducible to a formula, its composite values will always lose this battle: they are much harder to quantify.

For Silicon Valley, though, the reputation-obsessed algorithmic state of the sharing economy is the new welfare state. If you are honest and hardworking, your online reputation would reflect this, producing a highly personalised social net. It is “ultrastable” in Ashby’s sense: while the welfare state assumes the existence of specific social evils it tries to fight, the algorithmic state makes no such assumptions. The future threats can remain fully unknowable and fully addressable – on the individual level.

Silicon Valley, of course, is not alone in touting such ultrastable individual solutions. Nassim Taleb, in his best-selling 2012 book Antifragile, makes a similar, if more philosophical, plea for maximising our individual resourcefulness and resilience: don’t get one job but many, don’t take on debt, count on your own expertise. It’s all about resilience, risk-taking and, as Taleb puts it, “having skin in the game”. As Julian Reid and Brad Evans write in their new book, Resilient Life: The Art of Living Dangerously, this growing cult of resilience masks a tacit acknowledgement that no collective project could even aspire to tame the proliferating threats to human existence – we can only hope to equip ourselves to tackle them individually. “When policy-makers engage in the discourse of resilience,” write Reid and Evans, “they do so in terms which aim explicitly at preventing humans from conceiving of danger as a phenomenon from which they might seek freedom and even, in contrast, as that to which they must now expose themselves.”

What, then, is the progressive alternative? “The enemy of my enemy is my friend” doesn’t work here: just because Silicon Valley is attacking the welfare state doesn’t mean that progressives should defend it to the very last bullet (or tweet). First, even leftist governments have limited space for fiscal manoeuvres, as the kind of discretionary spending required to modernise the welfare state would never be approved by the global financial markets. And it’s the ratings agencies and bond markets – not the voters – who are in charge today.

Second, the leftist critique of the welfare state has become only more relevant today when the exact borderlines between welfare and security are so blurry. When Google’s Android powers so much of our everyday life, the government’s temptation to govern us through remotely controlled cars and alarm-operated soap dispensers will be all too great. This will expand government’s hold over areas of life previously free from regulation.

With so much data, the government’s favourite argument in fighting terror – if only the citizens knew as much as we do, they too would impose all these legal exceptions – easily extends to other domains, from health to climate change. Consider a recent academic paper that used Google search data to study obesity patterns in the US, finding significant correlation between search keywords and body mass index levels. “Results suggest great promise of the idea of obesity monitoring through real-time Google Trends data”, note the authors, which would be “particularly attractive for government health institutions and private businesses such as insurance companies.”

If Google senses a flu epidemic somewhere, it’s hard to challenge its hunch – we simply lack the infrastructure to process so much data at this scale. Google can be proven wrong after the fact – as has recently been the case with its flu trends data, which was shown to overestimate the number of infections, possibly because of its failure to account for the intense media coverage of flu – but so is the case with most terrorist alerts. It’s the immediate, real-time nature of computer systems that makes them perfect allies of an infinitely expanding and pre-emption‑obsessed state.

Perhaps, the case of Gloria Placente and her failed trip to the beach was not just a historical oddity but an early omen of how real-time computing, combined with ubiquitous communication technologies, would transform the state. One of the few people to have heeded that omen was a little-known American advertising executive called Robert MacBride, who pushed the logic behind Operation Corral to its ultimate conclusions in his unjustly neglected 1967 book, The Automated State.

At the time, America was debating the merits of establishing a national data centre to aggregate various national statistics and make it available to government agencies. MacBride attacked his contemporaries’ inability to see how the state would exploit the metadata accrued as everything was being computerised. Instead of “a large scale, up-to-date Austro-Hungarian empire”, modern computer systems would produce “a bureaucracy of almost celestial capacity” that can “discern and define relationships in a manner which no human bureaucracy could ever hope to do”.

“Whether one bowls on a Sunday or visits a library instead is [of] no consequence since no one checks those things,” he wrote. Not so when computer systems can aggregate data from different domains and spot correlations. “Our individual behaviour in buying and selling an automobile, a house, or a security, in paying our debts and acquiring new ones, and in earning money and being paid, will be noted meticulously and studied exhaustively,” warned MacBride. Thus, a citizen will soon discover that “his choice of magazine subscriptions… can be found to indicate accurately the probability of his maintaining his property or his interest in the education of his children.” This sounds eerily similar to the recent case of a hapless father who found that his daughter was pregnant from a coupon that Target, a retailer, sent to their house. Target’s hunch was based on its analysis of products – for example, unscented lotion – usually bought by other pregnant women.

For MacBride the conclusion was obvious. “Political rights won’t be violated but will resemble those of a small stockholder in a giant enterprise,” he wrote. “The mark of sophistication and savoir-faire in this future will be the grace and flexibility with which one accepts one’s role and makes the most of what it offers.” In other words, since we are all entrepreneurs first – and citizens second, we might as well make the most of it.

What, then, is to be done? Technophobia is no solution. Progressives need technologies that would stick with the spirit, if not the institutional form, of the welfare state, preserving its commitment to creating ideal conditions for human flourishing. Even some ultrastability is welcome. Stability was a laudable goal of the welfare state before it had encountered a trap: in specifying the exact protections that the state was to offer against the excesses of capitalism, it could not easily deflect new, previously unspecified forms of exploitation.

How do we build welfarism that is both decentralised and ultrastable? A form of guaranteed basic income – whereby some welfare services are replaced by direct cash transfers to citizens – fits the two criteria.

Creating the right conditions for the emergence of political communities around causes and issues they deem relevant would be another good step. Full compliance with the principle of ultrastability dictates that such issues cannot be anticipated or dictated from above – by political parties or trade unions – and must be left unspecified.

What can be specified is the kind of communications infrastructure needed to abet this cause: it should be free to use, hard to track, and open to new, subversive uses. Silicon Valley’s existing infrastructure is great for fulfilling the needs of the state, not of self-organising citizens. It can, of course, be redeployed for activist causes – and it often is – but there’s no reason to accept the status quo as either ideal or inevitable.

Why, after all, appropriate what should belong to the people in the first place? While many of the creators of the internet bemoan how low their creature has fallen, their anger is misdirected. The fault is not with that amorphous entity but, first of all, with the absence of robust technology policy on the left – a policy that can counter the pro-innovation, pro-disruption, pro-privatisation agenda of Silicon Valley. In its absence, all these emerging political communities will operate with their wings clipped. Whether the next Occupy Wall Street would be able to occupy anything in a truly smart city remains to be seen: most likely, they would be out-censored and out-droned.

To his credit, MacBride understood all of this in 1967. “Given the resources of modern technology and planning techniques,” he warned, “it is really no great trick to transform even a country like ours into a smoothly running corporation where every detail of life is a mechanical function to be taken care of.” MacBride’s fear is O’Reilly’s master plan: the government, he writes, ought to be modelled on the “lean startup” approach of Silicon Valley, which is “using data to constantly revise and tune its approach to the market”. It’s this very approach that Facebook has recently deployed to maximise user engagement on the site: if showing users more happy stories does the trick, so be it.

Algorithmic regulation, whatever its immediate benefits, will give us a political regime where technology corporations and government bureaucrats call all the shots. The Polish science fiction writer Stanislaw Lem, in a pointed critique of cybernetics published, as it happens, roughly at the same time as The Automated State, put it best: “Society cannot give up the burden of having to decide about its own fate by sacrificing this freedom for the sake of the cybernetic regulator.”

 

Could you “free” yourself of Facebook?

A 99-day challenge offers a new kind of social media experiment

Could you "free" yourself of Facebook?
(Credit: LoloStock via Shutterstock)

Let’s try a new experiment now, Facebook. And this time, you’re the subject.

Remember just last month, when the monolithic social network revealed that it had been messing with its users’ minds as part of an experiment? Writing in PNAS, Facebook researchers disclosed the results of a study that showed it had tinkered with the news feeds of nearly 700,000 users, highlighting either more positive or more negative content, to learn if “emotional contagion occurs without direct interaction between people.” What they found was that “When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred.” More significantly, after the news of the study broke, they discovered that people get pretty creeped out when they feel like their personal online space is being screwed with, and that their reading and posting activity is being silently monitored and collected – even when the terms of service they agreed to grant permission to do just that. And they learned that lawmakers in the U.S. and around the world question the ethics of Facebook’s intrusion.

Now, a new campaign out of Europe is aiming to do another experiment involving Facebook, its users and their feelings. But this time Facebook users aren’t unwitting participants but willing volunteers. And the first step involves quitting Facebook. The 99 Days of Freedom campaign started as an office joke at Just, a creative agency in the Netherlands. But the company’s art director Merijn Straathof says it quickly evolved into a bona fide cause. “As we discussed it internally, we noted an interesting tendency: Everyone had at least a ‘complicated’ relationship with Facebook. Whether it was being tagged in unflattering photos, getting into arguments with other users or simply regretting time lost through excessive use, there was a surprising degree of negative sentiment.” When the staff learned that Facebook’s 1.2 billion users “spend an average of 17 minutes per day on the site, reading updates, following links or browsing photos,” they began to wonder what that time might be differently applied to – and whether users would find it “more emotionally fulfilling.”



The challenge – one that close to 9,000 people have already taken – is simple. Change your FB avatar to the “99 Days of Freedom” one to let friends know you’re not checking in for the next few months. Create a countdown. Opt in, if you wish, to be contacted after 33, 66 and 99 days to report on your satisfaction with life without Facebook. Straathof says everyone at Just is also participating, to “test that one firsthand.”

Straathof and company say the goal isn’t to knock Facebook, but to show users the “obvious emotional benefits to moderation.” And, he adds, “Our prediction is that the experiment will yield a lot of positive personal experiences and, 99 days from now, we’ll know whether that theory has legs.” The anecdotal data certainly seems to support it. Seductive as FB, with its constant flow of news and pet photos, may be, you’d be hard-pressed to find a story about quitting it that doesn’t make getting away from it sound pretty great. It’s true that grand experiments, especially of a permanent nature, have never gotten off the ground. Four years ago, a group of disgruntled users tried to gather momentum for a Quit Facebook Day that quietly went nowhere. But individual tales certainly make a compelling case for, if not going cold turkey, at least scaling back. Elizabeth Lopatto recently wrote in Forbes of spending the past eight years Facebook free and learning that “If you really are interested in catching up with your friends, catch up with your friends. You don’t need Facebook to do it.” And writing on EliteDaily this past winter, Rudolpho Sanchez questioned why “We allow our successes to be measured in little blue thumbs” and declared, “I won’t relapse; I’ve been liberated. It’s nice not knowing what my fake friends are up to.” Writing a few weeks later in Business Insider, Dylan Love, who’d been on FB since he was an incoming college student 10 years ago, gave it up and reported his life, if not improved, remarkably unchanged, “except I’m no longer devoting mental energy to reading about acquaintances from high school getting married or scrolling through lots of pictures of friends’ vacation meals.” And if you want a truly persuasive argument, try this: My teenager has not only never joined Facebook, she dismissively asserts that she doesn’t want to because “It’s for old people.”

Facebook, of course, doesn’t want you to consider that you might be able to maintain your relationships or your sense of delight in the world without it. When my mate and I went away for a full week recently, we didn’t check in on social media once the whole time. Every day, with increasing urgency, we received emails from Facebook alerting us to activity in our feeds that we surely wanted to check. And since I recently gutted my friend list, I’ve been receiving a bevy of suggested people I might know. Why so few friends, lonely lady? Why so few check-ins? Don’t you want more, more, more?

I don’t know if I need to abandon Facebook entirely – I like seeing what people I know personally and care about are up to, especially those I don’t get to see in the real world that often. That connection has often been valuable, especially through our shared adventures in love, illness and grief, and I will always be glad for it. But a few months ago I deleted the FB app, which makes avoiding Facebook when I’m not at my desk a no-brainer. No more stealth checking my feed from the ladies’ room. No more spending time expressing my “like” of someone’s recent baking success when I’m walking down the street. No more “one more status update before bed” time sucks. And definitely no more exasperation when FB insistently twiddles with my news feed to show “top stories” when I prefer “most recent.” It was never a huge part of my life, but it’s an even smaller part of it now, and yeah, it does feel good. I recommend it. Take Just’s 99-day challenge or just a tech Sabbath or just scale back a little. Consider it an experiment. One in which the user, this time, is the winner.

Mary Elizabeth Williams Mary Elizabeth Williams is a staff writer for Salon and the author of “Gimme Shelter: My Three Years Searching for the American Dream.” Follow her on Twitter: @embeedub.

http://www.salon.com/2014/07/11/could_you_free_yourself_of_facebook/?source=newsletter

Facebook Is Studying You

 …Your Mom, Your Makeout Buddy, and Your 9/11 Conspiracy Theories

| Thu Jul. 10, 2014 6:00 AM ED

Facebook users and privacy advocates erupted in anger recently after New Scientist drew attention to a 2012 study in which Facebook researchers had attempted to manipulate users’ moods. “The company purposefully messed with people’s minds,” one privacy group complained to the Federal Trade Commission.

But the mood study is far from the only example of Facebook scrutinizing its users—the company has been doing that for years, examining users’ ethnicities, political views, romantic partners, and even how they talk to their children. (Unlike the mood study, the Facebook studies listed below are observational; they don’t attempt to change users’ behavior.) Although it’s unlikely Facebook users have heard about most of these studies, they’ve consented to them; the social network’s Data Use Policy states: “We may use the information we receive about you…for internal operations, including troubleshooting, data analysis, testing, research and service improvement.”

Below are five things Facebook researchers have been studying about Facebook users in recent years. (Note that in each of these studies, data was analyzed in aggregate and steps were taken to hide personally identifiable information.)

1. Your significant others (and whether the relationship will last): In October 2013, Facebook published a study in which researchers tried to guess who users were in a relationship with by looking at the users’ Facebook friends. For the study, Facebook researchers randomly chose 1.3 million users who had between 50 and 2,000 friends, were older than 20, and described themselves as married, engaged, or in a relationship. To guess whom these users were dating, the researchers analyzed which of the users’ friends knew each other—and which ones didn’t. You might share a ton of college friends with your old college roommate on Facebook, for example. But your boyfriend might be Facebook friends with your college friends, your coworkers, and your mom—people who definitely don’t know each other. Hence, he’s special.

Using this method, researchers were able to determine a person’s romantic partner with “high accuracy”—they were able to guess married users’ spouses 60 percent of the time by just looking at users’ friend networks. The researchers also looked at a subset of same-sex couples, to see whether that changed the results. (It didn’t.)

Facebook then decided to see whether it could use this method to predict whether a relationship is likely to last. For this part of the experiment, researchers looked at about 400,000 users who said that they were “in a relationship” and watched to see whether those users said they were single 60 days later. The researchers concluded that relationships in which Facebook’s model correctly identified the partner were less likely to break up, noting that the results were especially accurate when the two people had been together less than a year. (So basically, if you’re only introducing your boyfriend to your friends, and not your mom, your relationship might be less likely to last.)

2. How your mom talks to you: For this study, Facebook looked at how parents and their kids talk to each other Facebook. (Fun fact: On average, parent-child pairs wait 371 days after joining Facebook before becoming “friends.” Tell your little sister to stop ignoring your mom’s friend request.) The researchers examined three months of communication data pulled from September 2012. This data included comments, posts, and links shared on other users’ timelines, but not chat messages. According to the researchers, that wasn’t a privacy decision—chats are simply “too short and noisy for substantive language analysis.” Here are some of the top phrases that researchers noticed parents using in messages to their young children:

And here’s what parents are writing to their adult children, after they’ve developed filthy minds and drinking problems:

Facebook also noted that “what parents say when they’re not talking to their children is just as revealing; they use higher levels of ideology (agree but, obama, our government, policies, people need to, ethics), swearing and slang (ctfu, lmao, fucker, idk), and alcohol and sex terms (tequila, glass of wine, that ass, sexy). Ew.

3. Your ethnicity: In this older study, from 2010, researchers wrote that “the ethnicity of a user base is an important demographic indicator that can be used for marketing, compliance, and analytics as well as a scientific tool for understanding social behavior,” but lamented that “unfortunately, ethnic information is often unavailable for practical, legal, or political reasons.” So researchers came up with a solution: They determined the ethnic breakdown of US Facebook users by using people’s names and data provided by the Census. Tested on Facebook, the researchers’ proposed model “learned” that Latoya is more likely to be a black name and Barb is more likely to be white name. “Using both first and last names further improves estimates, largely by making better distinctions between White and Black,” the researchers wrote.

Once researchers had that data set, they started doing other studies. For example, the researchers examined pairs of people in romantic relationships on Facebook, as broken down by ethnicity. They also noted that their research suggested that “individuals’ ethnicity can be predicted through their social ties” and tried to predict users’ ethnicity based on the average ethnicity of their friends. (You should definitely not play this game at your next dinner party.) The researchers also compared users’ self-identified political views with their ethnicities, noting that “whites are more frequent in the Libertarian, Conservative, and Very Conservative categories.” The researchers did note that their research method comes with a caveat, “While ethnicity is an important factor in understanding user behavior, it is often only a proxy for other variables, such as socioeconomic status, or education. A complete analysis should control for all such factors.”

4. How you respond to conspiracy theories: In the spring of 2014, Facebook published a study on how rumors spread on the social network. The researchers looked at rumors identified by the rumor-debunking website Snopes.com that fall into a number of different categories, including politics, medicine, horror, “glurge” (i.e., sentimental stories that usually aren’t true), and 9/11. Then, the researchers found rumors posted on Facebook as photos, and gathered 249,035 comments in which people commented on the rumor with a valid link to Snopes.Ultimately, the researchers found reshared posts that received a comment that linked to Snopes were more likely to be deleted. So, feel free to keep telling your friends that the Russian sleep experiment story is BS.

5. If you’re deleting posts before you publish them: For this 2013 study, Facebook looked at how often users start typing a post or comment, and then at the last minute, decide not to publish it, which they called “self-censorship.” The researchers collected data from 3.9 million users over 17 days. They noted when someone started typing more than five characters in status update or comment box. The researchers recorded only whether text was entered, not the keystrokes or content. (This is the same way Gmail automatically saves drafts of your email, except that Facebook logs the presence of text, not actual content.) If the user didn’t share the post within 10 minutes, it was marked as self-censored. Researchers found that 71 percent of all users censored content at least once. The researchers also noted that women were less likely to self-censor, as were people with a more politically diverse set of friends.

How Modern Houses Can Watch You

http://homedesignlover.com/wp-content/uploads/2011/11/best-modern-house-design.jpg
Presto Vivace (882157) links to a critical look in Time Magazine at the creepy side of connected household technology. An excerpt:
A modern surveillance state isn’t so much being forced on us, as it is sold to us device by device, with the idea that it is for our benefit. … … Nest sucks up data on how warm your home is. As Mocana CEO James Isaacs explained to me in early May, a detailed footprint of your comings and goings can be inferred from this information. Nest just bought Dropcam, a company that markets itself as a security tool allowing you to put cameras in your home and view them remotely, but brings with it a raft of disquieting implications about surveillance. Automatic wants you to monitor how far you drive and do things for you like talk to your your house when you’re on your way home from work and turn on lights when you pull into your garage. Tied into the new SmartThings platform, a Jawbone UP band becomes a tool for remotely monitoring someone else’s activity. The SmartThings hubs and sensors themselves put any switch or door in play. Companies like AT&T want to build a digital home that monitors your security and energy use. … … Withings Smart Body Analyzer monitors your weight and pulse. Teddy the Guardian is a soft toy for children that spies on their vital signs. Parrot Flower Power looks at the moisture in your home under the guise of helping you grow plants. The Beam Brush checks up on your teeth-brushing technique.
Presto Vivaci adds, “Enough to make the Stasi blush. What I cannot understand is how politicians fail to understand what a future Kenneth Starr is going to do with data like this.”
~Slashdot~

Let’s nationalize Amazon and Google

Publicly funded technology built Big Tech

They’re huge and ruthless and define our lives. They’re close to monopolies. Let’s make them public utilities

Let's nationalize Amazon and Google: Publicly funded technology built Big Tech
Jeff Bezos (Credit: AP/Reed Saxon/Pakhnyushcha via Shutterstock/Salon)

They’re huge, they’re ruthless, and they touch every aspect of our daily lives. Corporations like Amazon and Google keep expanding their reach and their power. Despite a history of abuses, so far the Justice Department has declined to take antitrust actions against them. But there’s another solution.

Is it time to manage and regulate these companies as public utilities?

That argument’s already been made about broadband access. In her book “Captive Justice,” law professor Susan Crawford argues that “high-speed wired Internet access is as basic to innovation, economic growth, social communication, and the country’s competitiveness as electricity was a century ago.”

Broadband as a public utility? If not for corporate corruption of our political process, that would seem like an obvious solution. Instead, our nation’s wireless access is the slowest and costliest in the world.

But why stop there? Policymakers have traditionally considered three elements when evaluating the need for a public utility: production, transmission, and distribution. Broadband is transmission. What about production and distribution?

The Big Tech mega-corporations have developed what Al Gore calls the “Stalker Economy,” manipulating and monitoring as they go. But consider: They were created with publicly funded technologies, and prospered as the result of indulgent policies and lax oversight. They’ve achieved monopoly or near-monopoly status, are spying on us to an extent that’s unprecedented in human history, and have the potential to alter each and every one of our economic, political, social and cultural transactions.

In fact, they’re already doing it.

Public utilities? It’s a thought experiment worth conducting.

Big Tech was created with publicly developed technology.

No matter how they spin it, these corporations were not created in garages or by inventive entrepreneurs. The core technology behind them is the Internet, a publicly funded platform for which they pay no users’ fee. In fact, they do everything they can to avoid paying their taxes.



Big Tech’s use of public technology means that it operates in a technological “commons,” which they are using solely for its own gain, without regard for the public interest. Meanwhile the United States government devotes considerable taxpayer resource to protecting them – from patent infringement, cyberterrorism and other external threats.

Big Tech’s services have become a necessity in modern society.

Businesses would be unable to participate in modern society without access to the services companies like Amazon, Google and Facebook provide. These services have become public marketplaces.

For individuals, these entities have become the public square where social interactions take place, as well as the marketplace where they purchase goods.

They’re at or near monopoly status – and moving fast.

Google has 80 percent of the search market in the United States, and an even larger share of key overseas markets. Google’s browsers have now surpassed Microsoft’s in usage across all devices. It has monopoly-like influence over online news, as William Baker noted in the Nation. Its YouTube subsidiary dominates the U.S. online-video market, with nearly double the views of its closest competitor. (Roughly 83 percent of the Americans who watched a video online in April went to YouTube.)

Even Microsoft’s Steve Ballmer argued that Google is a “monopoly” whose activities were “worthy of discussion with competition authority.” He should know.

As a social platform, Facebook has no real competitors. Amazon’s book business dominates the market. E-books are now 30 percent of the total book market, and its Kindle e-books account for 65 percent of e-book sales.  Nearly one book in five is an Amazon product – and that’s not counting Amazon’s sales of physical books. It has become such a behemoth that it is able to command discounts of more than 50 percent from major publishers like Random House.

They abuse their power.

The bluntness with which Big Tech firms abuse their monopoly power is striking. Google has said that it will soon begin blocking YouTube videos from popular artists like Radiohead and Adele unless independent record labels sign deals with its upcoming music streaming service (at what are presumably disadvantageous rates).   Amazon’s war on publishers like Hachette is another sign of Big Tech arrogance.

But what is equally striking about these moves is the corporations’ disregard for basic customer service. Because YouTube’s dominance of the video market is so large, Google is confident that even frustrated music fans have nowhere to go. Amazon is so confident of its dominance that it retaliated against Hachette by removing order buttons when a Hachette book came up (which users must find maddening) and lied about the availability of Hachette books when a customer attempts to order one. It also altered its search process for recommendations to freeze out Hachette books and direct users to non-Hachette authors.

Amazon even suggested its customers use other vendors if they’re unhappy, a move that my Salon colleague Andrew Leonard described as “nothing short of amazing – and troubling.”

David Stratfield of the New York Times asked, “When does discouragement become misrepresentation?” One logical answer: When you tell customers a product isn’t available, even though it is, or rig your sales mechanism to prevent customers from choosing the item they want.

And now Amazon’s using some of the same tactics against Warner Home Video.

They got there with our help.

As we’ve already noted, Internet companies are using taxpayer-funded technology to make billions of dollars from the taxpayers – without paying a licensing fee. As we reported earlier, Amazon was the beneficiary of tax exemptions that allowed it to reach its current monopolistic size.

Google and the other technology companies have also benefited from tax policies and other forms of government indulgence. Contrary to popular misconception, Big Tech corporations aren’t solely the products of ingenuity and grit. Each has received, and continues to receive, a lot of government largess.

The real “commodity” is us.

Most of Big Tech’s revenues come from the use of our personal information in its advertising business. Social media entries, Web-surfing patterns, purchases, even our private and personal communications add value to these corporations. They don’t make money by selling us a product. We are the product, and we are sold to third parties for profit.

Public utilities are often created when the resource being consumed isn’t a “commodity” in the traditional sense. “We” aren’t an ordinary resource. Like air and water, the value of our information is something that should be publicly shared – or, at a minimum, publicly managed.

Our privacy is dying … or already dead.

“We know where you are,” says Google CEO Eric Schmidt. “We know where you’ve been. We can more or less know what you’re thinking about.”

Facebook tracks your visits to the website of any corporate Facebook “partner,” stores that information, and uses it to track and manipulate the ads you see. Its mobile app also has a new, “creepy” feature that turns on your phone’s microphone, analyzes what you’re listening to or watching, and is capable of posting updates to your status like “Listening to Albert King” or “Watching ‘Orphan Black.’

Google tracks your search activity, an activity with a number of disturbing implications. (A competing browser that does not track searches called DuckDuckGo offers an illustrated guide to its competitors’ practices.)  If you use its Chrome browser, Google tracks your website visits too (unless you’re in “private” mode.)

Yasha Levine, who is tracking corporate data spying in his “Surveillance Valley” series, notes that “True end-to-end encryption would make our data inaccessible to Google, and grind its intel extraction apparatus to a screeching halt.” As the ACLU’s Christopher Soghoian points out: “It’s very, very difficult to deploy privacy protective policies with the current business model of ad supported services.”

As Levine notes, the widely publicized revelation that Big Data companies track rape victims was just the tip of the iceberg. They also track “anorexia, substance abuse, AIDS and HIV … Bedwetting (Enuresis), Binge Eating Disorder, Depression, Fetal Alcohol Syndrome, Genital Herpes, Genital Warts, Gonorrhea, Homelessness, Infertility, Syphilis … the list goes on and on and on and on.”

Given its recent hardball tactics, here’s a little-known development that should concern more people: Amazon also hosts 37 percent of the nation’s cloud computing services, which means it has access to the inner workings of the software that runs all sorts of businesses – including ones that handle your personal data.

For all its protestations, Microsoft is no different when it comes to privacy. The camera and microphone on its Xbox One devices were initially designed to be left on at all times, and it refused to change that policy until purchasers protested.

Privacy, like water or energy, is a public resource. As the Snowden revelations have taught us, all such resources are at constant risk of government abuse.  The Supreme Court just banned warrantless searches of smartphones – by law enforcement. Will we be granted similar protections from Big Tech corporations?

Freedom of information is at risk.

Google tracks your activity and customizes search results, a process that can filter or distort your perception of the world around you.  What’s more, this “personalized search results” feature leads you back to information sources you’ve used before, which potentially narrows our ability to discover new perspectives or resources.  Over time this creates an increasingly narrow view of the world.

What’s more, Google’s shopping tools have begun using “paid inclusion,” a pay-for-play search feature it once condemned as “evil.” Its response is to say it prefers not to call this practice “paid inclusion,” even though its practices appear to meet the Federal Trade Commission’s definition of the term.

As for Amazon, it has even manipulated its recommendation searches in order to retaliate against other businesses, as we’ll see in the next section.

The free market could become even less free.

Could Big Tech and its data be used to set user-specific pricing, based on what is known about an individual’s willingness to pay more for the same product? Benjamin Schiller of Brandeis University wrote a working paper last year that showed how Netflix could do exactly that. Grocery stores and other retailers are already implementing technology that offers different pricing to different shoppers based on their data profile.

For its part, Amazon is introducing a phone that will also tag the items around you, as well as the music and programs you hear, for you to purchase – from Amazon, of course. Who will be purchasing the data those phones collect about you?

They could hijack the future.

The power and knowledge they have accumulated is frightening. But the Big Tech corporations are just getting started. Google has photographically mapped the entire world. It intends to put the world’s books into a privately owned online library. It’s launching balloons around the globe that will bring Internet access to remote areas – on its terms. It’s attempting to create artificial intelligence and extend the human lifespan.

Amazon hopes to deliver its products by drone within the next few years, an idea that would seem preposterous if not for its undeniable lobbying clout. Each of these Big Tech corporations has the ability to filter – and alter – our very perceptions of the world around us. And each of them has already shown a willingness to abuse it for their own ends.

These aren’t just the portraits of futuristic corporations that have become drunk on unchecked power. It’s a sign that things are likely to get worse – perhaps a lot worse – unless something is done. The solution may lie with an old concept. It may be time to declare Big Tech a public utility.

 

Richard (RJ) Eskow is a writer and policy analyst. He is a Senior Fellow with the Campaign for America’s Future and is host and managing editor of The Zero Hour on We Act Radio.

http://www.salon.com/2014/07/08/lets_nationalize_amazon_and_google_publicly_funded_technology_built_big_tech/?source=newsletter

Net neutrality is dying, Uber is waging a war on regulations, and Amazon grows stronger by the day

Why 2014 could be the year we lose the Internet

Why 2014 could be the year we lose the Internet
Jeff Bezos, Tim Cook (Credit: Reuters/Gus Ruelas/Robert Galbraith/Photo collage by Salon)

Halfway through 2014, and the influence of technology and Silicon Valley on culture, politics and the economy is arguably bigger than ever — and certainly more hotly debated. Here are Salon’s choices for the five biggest stories of the year.

1) Net neutrality is on the ropes.

So far, 2014 has been nothing but grim for the principle known as “net neutrality” — the idea that the suppliers of Internet bandwidth should not give preferential access (so-called fast lanes) to the providers of Internet services who are willing and able to pay for it. In January, the D.C. Court of Appeals struck down the FCC’s preliminary plan to enforce a weak form of net neutrality. Less than a month later, Comcast, the nation’s largest cable company and broadband Internet service provider, announced its plans to buy Time-Warner — and inadvertently gave us a compelling explanation for why net neutrality is so important. A single company with a dominant position in broadband will simply have too much power, something that could have enormous implications for our culture.

The situation continued to degenerate from there. Tom Wheeler, President Obama’s new pick to run the FCC, a former top cable industry lobbyist, unveiled a new plan for net neutrality that was immediately slammed as toothless. In May, ATT announced plans to merge with DirecTV. Consolidation proceeds apace, and our government appears incapable of managing the consequences.

2) Uber takes over.

After completing its most recent round of financing, Uber is now valued at $18.2 billion. Along with Airbnb, the Silicon Valley start-up has become a standard bearer for the Valley’s cherished allegiance to “disruption.” The established taxi industry is under sustained assault, but Uber has made it clear that the company’s ultimate ambitions go far beyond simply connecting people with rides. Uber has designs on becoming the premier logistics connection platform for getting anything to anyone. What Google is to search, Uber wants to be for moving objects from Point A to Point B. And Google, of course, has a significant financial stake in Uber.



Uber’s path has been bumpy. The company is fighting regulatory battles with municipalities across the world, and its own drivers are increasingly angry at fare cuts, and making sporadic attempts to organize. But the smart money sees Uber as one of the major players of the near future. The “sharing” economy is here to stay.

3) The year of the stream.

Apple bought Beats by Dre. Amazon launched its own streaming music service. Google is planning a new paid streaming offering. Spotify claimed 10 million paying customers and Pandora boasts 75 million listeners every month.

We may end up remembering 2014 as the year that streaming established itself as the dominant way people consume music. The numbers are stark. Streaming is surging, while paid downloads are in free fall.

For consumers, all-you-can-eat services like Spotify are generally marvelous. But it remains astonishing that a full 20 years after the Internet threw the music industry into turmoil, it is still completely unclear how artists and songwriters will make a decent living in an era when music is essentially free.

We also face unanswered questions about the potential implications for what kinds of music get made in an environment where every listen is tracked and every tweet or Facebook like observed. What will Big Data mean for music?

4) Amazon shows its true colors.

What a busy six months for Jeff Bezos! Amazon introduced its own set-top box for TV watching, its own smartphone for insta-shopping, anywhere, any time, and started abusing its near monopoly power to win better terms with publishing companies.

For years, consumer adoration of Amazon’s convenience and low prices fueled the company’s rise. It’s hard, at the midpoint of 2014, to avoid the conclusion that we’ve created a monster. This year, Amazon started getting sustained bad press at the very highest levels. And you know what? Jeff Bezos deserves it.

5) The tech culture wars boil over.

In the first six months of 2014, the San Francisco Bay Area witnessed emotional public hearings about Google shuttle buses, direct action by radicals against technology company executives, bar fights centering on Google Glass wearers, and a steady rise in political heat focused on tech economy-driven gentrification.

As I wrote in April

Just as the Luddites, despite their failure, spurred the creation of worker-class consciousness, the current Bay Area tech protests have had a pronounced political effect. While the tactics range from savvy, well-organized protest marches to juvenile acts of violence, the impact is clear. The attention of political leaders and the media has been engaged. Everyone is watching.

Ultimately, maybe this will be the biggest story of 2014. This year, numerous voices started challenging the transformative claims of Silicon Valley hype and began grappling with the nitty-gritty details of how all this “disruption” is changing our economy and culture. Don’t expect the second half of 2014 to be any different.

Wealthy venture capitalist Tom Perkins is nostalgic for the old Silicon Valley

 — whorehouses and all

The venture capitalist was made infamous for warning of a “progressive” Kristallnacht

Wealthy venture capitalist Tom Perkins is nostalgic for the old Silicon Valley -- whorehouses and all
Tom Perkins (Credit: Bloomberg TV)

Tensions between the wealthy tone-deaf tech world and folks being priced out of San Francisco have been mounting — protests, evictions, Google glass altercations — and they’re the subject of a feature in this week’s New Yorker.

In it writer Nathan Heller interviews a man who has spouted infamous and offensive opinions about these issues: venture capitalist Tom Perkins.

Perkins, as you may recall, wrote a letter to the editor published in the Wall Street Journal, saying this:

“Writing from the epicenter of progressive thought, San Francisco, I would call attention to the parallels of fascist Nazi Germany to its war on its “one percent,” namely its Jews, to the progressive war on the American one percent, namely the “rich.”

“From the Occupy movement to the demonization of the rich embedded in virtually every word of our local newspaper, the San Francisco Chronicle, I perceive a rising tide of hatred of the successful one percent. There is outraged public reaction to the Google buses carrying technology workers from the city to the peninsula high-tech companies which employ them. We have outrage over the rising real-estate prices which these “techno geeks” can pay. We have, for example, libelous and cruel attacks in the Chronicle on our number-one celebrity, the author Danielle Steel, alleging that she is a “snob” despite the millions she has spent on our city’s homeless and mentally ill over the past decades.

“This is a very dangerous drift in our American thinking. Kristallnacht was unthinkable in 1930; is its descendent “progressive” radicalism unthinkable now?”

In the New Yorker piece, titled “California Screaming,” Perkins seems to have changed his tune a bit. He reminisced about the artists, the Beats, the jazz, the spirit, and yes, the whorehouses of the Silicon Valley he first knew. Here it is below via ValleyWag:



“Perkins considers Ron Conway a friend, and admires the pro-business policies that Conway and Sf.Citi have pushed through [in San Francisco]. He also admires the country of Australia, which he believes approaches the free-wheeling, entrepreneurial bliss of Northern California at the time he arrived, in 1957. ‘I was twenty-two, twenty-three,’ he explained. ‘I lived in Sausalito, which back then had a functioning whorehouse—one of the last ones in the Bay Area. It was a loose town where anything went, and I loved it. San Francisco was that way. It was artistic, outrageous. The gays had a lot to do with that.’ Perkins had brought his forehead to rest on his fingertips and closed his eyes, smiling. ‘I knew writers and artists. North Beach. The Beats. The jazz. It’s still a great city, but I think it was better then.’”

While it’s still not a full admission of understanding why people are so outraged by the rising inequality in the city, he does seem to miss some of the aspects that protesters are trying to keep from disappearing in a city known for its beautiful counterculture. ValleyWag points out that both Perkins and the protesters see the importance of “artistsmusicians, and, yes, sex workers” that the tech world is pricing out of the city.

Though he may long for days gone by, Perkins doesn’t think the culture can be saved. (Thus, revealing his bias: He may love the olden days, but still he makes his massive earnings from the tech world):

“I asked Perkins whether he saw a way to preserve communities of writers and artists in town. He sighed and thought for several long moments. ‘I don’t see how,’ he said at last.”

 

http://www.salon.com/2014/07/02/tom_perkins_is_nostalgic_for_the_old_silicon_valley_whorehouses_and_all/?source=newsletter