book review | Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization

book review | Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization
August 24, 2013 by José Luis Cordeiro<http://www.kurzweilai.net/jose-luis-cordeiro>

[http://www.kurzweilai.net/images/Radical-Abundance.png]Eric Drexler, popularly known as "the founding father of nanotechnology," introduced the concept in his seminal 1981 paper in Proceedings of the National Academy of Sciences.

This paper established fundamental principles of molecular engineering and outlined development paths to advanced nanotechnologies.

He popularized the idea of nanotechnology in his 1986 book, Engines of Creation: The Coming Era of Nanotechnology, where he introduced a broad audience to a fundamental technology objective: using machines that work at the molecular scale to structure matter from the bottom up.

He went on to continue his PhD thesis at MIT, under the guidance of AI-pioneer Marvin Minsky, and published it in a modified form as a book in 1992 as Nanosystems: Molecular Machinery, Manufacturing, and Computation<http://e-drexler.com/p/idx04/00/0411nanosystems.html>.

Drexler's new book, Radical Abundance: How a Revolution in Nanotechnology Will Change Civilization<http://www.kurzweilai.net/radical-abundance-how-a-revolution-in-nanotechnology-will-change-civilization>, tells the story of nanotechnology from its small beginnings, then moves quickly towards a big future, explaining what it is and what it is not, and enlightening about what we can do with it for the benefit of humanity.

In his pioneering 1986 book, Engines of Creation, he defined nanotechnology as a potential technology with these features: "manufacturing using machinery based on nanoscale devices, and products built with atomic precision."

In his 2013 sequel, Radical Abundance, Drexler expands on his prior thinking, corrects many of the misconceptions about nanotechnology, and dismisses fears of dystopian futures replete with malevolent nanobots and gray goo.

In 1986 he talked about nanotechnology as the engine of abundance, but now he talks about radical abundance:

Imagine what the world might be like if we were really good at making things — better things — cleanly, inexpensively, and on a global scale. … The global prospect would be, not scarcity, but unprecedented abundance — radical, transformative, and sustainable abundance. We would be able to produce radically more of what people want and at a radically lower cost — in every sense of the word, both economic and environmental.

What if industrial production as we know it can be changed beyond recognition? The consequences would change almost everything else, and this new industrial revolution is visible on the horizon. Imagine a world where the gadgets and goods that run our society are produced not in a far-flung supply chain of industrial facilities, but in compact, even desktop-scale machines.

Imagine replacing an enormous automobile factory and all of its multi-million dollar equipment with a garage-sized facility that can assemble cars from inexpensive, microscopic parts, with production times measured in minutes. Then imagine that the technologies that can make these visions real are emerging — under many names, behind the scenes, with a long road still ahead, yet moving surprisingly fast.

The new nanotech: atomically precise manufacturing

His new book clearly identifies nanotechnology with atomically precise manufacturing (APM). He shows that APM rests on well-understood scientific and engineering principles that will support large-scale, low-cost production of advanced products, enable solutions to seemingly intractable global problems, and facilitate rapid draw-down of atmospheric CO2 levels.

Drexler describes how APM will radically reduce materials and energy costs, since most future devices will be manufactured using very abundant and common elements like carbon, hydrogen, nitrogen, oxygen and silicon, and at a very low cost of less than one dollar per kilogram. He argues that photovoltaic systems using nanotechnology will allow us to power human civilization using only 0.2% of the Earth's land surface, without using any more fossil fuels and helping to improve the environment.

Consider that a "one-gram platform built with advanced technologies could provide teraflops of computational power (and much more, in bursts), together with a million-terabyte data storage capacity and better-than-human sensors, all with a power demand comparable to that of cell phone on standby," he suggests.

He argues that new devices produced with APM will radically use less resources and energy, and will be radically more efficient and stronger. Instead of using milliwatts, future devices will use nanowatts of power. We will produce much more for much less, while preserving the environment and improving it.

Drexler makes many comparisons between the information revolution and what he now calls the "APM revolution." What the first did with bits, the second will do with atoms: "Image files today will be joined by product files tomorrow. Today one can produce an image of the Mona Lisa without being able to draw a good circle; tomorrow one will be able to produce a display screen without knowing how to manufacture a wire."

Civilization, he says, is advancing from a world of scarcity toward a world of abundance — indeed, radical abundance.

José Cordeiro is Director, Venezuela Node of The Millennium Project and Energy Advisor/Faculty, Singularity University

Data Monetization in the Age of Big Data

Data Monetization in the Age of Big Data

Source: Accenture

The volume and richness of the data now uniquely accessible to mobile providers—whether in the form of transactions, inquiries, text messages or tweets, GPS locations or live video feeds—offers a veritable gold mine of insights and applications. And even as mobile phones have become the primary device through which consumers get their information, those very same devices have begun to facilitate new types of information, including extremely precise, real-time, geolocation information.

Not surprisingly, operators today are talking about when and how to tap into this data and what to do with it. In particular, they want to know how to monetize it: how to sort, analyze and manipulate the data and put it to use. This holds true not only for internal applications, but increasingly for building new revenue streams or collaborating on external applications with third parties as well.

How can mobile operators best approach this new territory? What are the opportunities and challenges? And how can operators shape new business models to monetize their Big Data?

Direct link to document (PDF; 4.6 MB)

A Guardian guide to your Metadata

A Guardian guide to your Metadata
http://www.theguardian.com/technology/interactive/2013/jun/12/what-is-metadata-nsa-surveillance#meta=0000100

Metadata is information generated as you use technology, and its use has been the subject of controversy since NSA's secret surveillance program<http://www.guardian.co.uk/world/the-nsa-files> was revealed. Examples include the date and time you called somebody or the location from which you last accessed your email. The data collected generally does not contain personal or content-specific details, but rather transactional information about the user, the device and activities taking place. In some cases you can limit the information that is collected – by turning off location services on your cell phone for instance – but many times you cannot. Below, explore some of the data collected through activities you do every day. On Thursday, June 13 The Guardian's data editor James Ball will answer your questions about the NSA data collection program<http://q-and-a.guardian.co.uk/qanda/859036> in the US from 3pm-4pm EST | 8pm-9pm BST
Choose the services you use in a day

Email
Phone
Camera
Facebook
Twitter
Search
Web browser
Tweet<https://twitter.com/intent/tweet?url=http%3A%2F%2Fwww.theguardian.com%2Ftechnology%2Finteractive%2F2013%2Fjun%2F12%2Fwhat-is-metadata-nsa-surveillance%23meta%3D0000100&text=How%20much%20metadata%20do%20you%20reveal%20every%20day%3F%20Find%20out%20via%20%40GuardianUS%20%23NSAfiles%20INTERACTIVE%3A> Share Reset
Twitter

* your name, location, language, profile bio information and url
* when you created your account
* your username and unique identifier
* tweet's location, date, time and timezone

* tweet's unique ID and ID of tweet replied to
* contributor IDs
* your follower, following and favorite count
* your verification status
* application sending the tweet

What metadata looks like

Below is a tweet from @GuardianUS (right) and a truncated version of its metadata (left). Accessing metadata is often possible through services offered by the provider and can be retrieved in a structured format that could include raw text, XML, or in this example, JSON. An easy way to see some of your own metadata is by looking at your browser's history which provides information about what websites you visited and when

What you can tell using metadata:
A case study of the Petraeus scandal

1. To communicate, Paula Broadwell and David Petraeus shared an anonymous email account

[http://gia.guim.co.uk/2013/06/metadata/img/broadwell_patreaus_frames01.png]

2. Instead of sending emails, both would login to the account, edit and save drafts

[http://gia.guim.co.uk/2013/06/metadata/img/broadwell_patreaus_frames02.png]

3. Broadwell logged in from various hotels' public Wi-Fi, leaving a trail of metadata that included times and locations

[http://gia.guim.co.uk/2013/06/metadata/img/broadwell_patreaus_frames03.png]

4. The FBI crossed-referenced hotel guests with login times and locations leading to the identification of Broadwell

[http://gia.guim.co.uk/2013/06/metadata/img/broadwell_patreaus_frames04.png]
Sources: Microsoft<http://msdn.microsoft.com/en-us/library/gg309512.aspx>, IPTC<http://www.iptc.org/std/photometadata/0.0/documentation/IPTC-PhotoMetadataWhitePaper2007_11.pdf>, Verizon telephone data court order<http://www.guardian.co.uk/world/interactive/2013/jun/06/verizon-telephone-data-court-order>, Photo Metadata<http://www.photometadata.org/meta-tutorials-adobe-photoshop>, Facebook<https://developers.facebook.com/docs/reference/login/extended-profile-properties>, Beyond the Wire<http://blog.newswire.ca/wordpress-mu/2011/06/28/uncovering-the-metadata-in-a-tweet>, Google<https://support.google.com/accounts/answer/54068?hl=en>, ACLU<http://www.aclu.org/blog/technology-and-liberty-national-security/surveillance-and-security-lessons-petraeus-scandal>

August 17, 2013

Is Big Data an Economic Big Dud?

By JAMES GLANZ

http://www.nytimes.com/2013/08/18/sunday-review/is-big-data-an-economic-big-dud.html?ref=opinion

IF pencil marks on some colossal doorjamb could measure the growth of the Internet, they would probably be tracking the amount of data sloshing through the public network that spans the planet. Christened by the World Economic Forum as “the new oil” and “a new asset class,” these vast loads of data have been likened to transformative innovations like the steam locomotive, electricity grids, steel, air-conditioning and the radio.

The astounding rate of growth would make any parent proud. There were 30 billion gigabytes of video, e-mails, Web transactions and business-to-business analytics in 2005. The total is expected to reach more than 20 times that figure in 2013, with off-the-charts increases to follow in the years ahead, according to Cisco, the networking giant.

How much data is that? Cisco estimates that in 2012, some two trillion minutes of video alone traversed the Internet every month. That translates to over a million years per week of everything from video selfies and nannycams to Netflix downloads and “Battlestar Galactica” episodes.

What is sometimes referred to as the Internet’s first wave — say, from the 1990s until around 2005 — brought completely new services like e-mail, the Web, online search and eventually broadband. For its next act, the industry has pinned its hopes, and its colossal public relations machine, on the power of Big Data itself to supercharge the economy.

There is just one tiny problem: the economy is, at best, in the doldrums and has stayed there during the latest surge in Web traffic. The rate of productivity growth, whose steady rise from the 1970s well into the 2000s has been credited to earlier phases in the computer and Internet revolutions, has actually fallen. The overall economic trends are complex, but an argument could be made that the slowdown began around 2005 — just when Big Data began to make its appearance.

Those factors have some economists questioning whether Big Data will ever have the impact of the first Internet wave, let alone the industrial revolutions of past centuries. One theory holds that the Big Data industry is thriving more by cannibalizing existing businesses in the competition for customers than by creating fundamentally new opportunities.

In some cases, online companies like Amazon and eBay are fighting among themselves for customers. But in others — here is where the cannibals enter — the companies are eating up traditional advertising, media, music and retailing businesses, said Joel Waldfogel, an economist at the University of Minnesota who has studied the phenomenon.

“One falls, one rises — it’s pretty clear the digital kind is a substitute to the physical kind,” he said. “So it would be crazy to count the whole rise in digital as a net addition to the economy.”

Robert J. Gordon, a professor of economics at Northwestern University, said comparing Big Data to oil was promotional nonsense. “Gasoline made from oil made possible a transportation revolution as cars replaced horses and as commercial air transportation replaced railroads,” he said. “If anybody thinks that personal data are comparable to real oil and real vehicles, they don’t appreciate the realities of the last century.”

Other economists believe that Big Data’s economic punch is just a few years away, as engineers trained in data manipulation make their way through college and as data-driven start-ups begin hiring. And of course the recession could be masking the impact of the data revolution in ways economists don’t yet grasp. Still, some suspect that in the end our current framework for understanding Big Data and “the cloud” could be a mirage.

“I think it’s conceivable that the data era will be a bust for the things people expect it to be useful for,” said Scott Wallsten, a senior fellow at the Technology Policy Institute and the Georgetown Center for Business and Public Policy. Some entirely new use will have to turn up for data to fulfill its economic potential, he added.

There is no disputing that a wide spectrum of businesses, from e-marketers to pharmaceutical companies, are now using huge amounts of data as part of their everyday business.

Josh Marks is the chief executive of one such company, masFlight, which helps airlines use enormous data sets to reduce fuel consumption and improve overall performance. Although his first mission is to help clients compete with other airlines for customers, Mr. Marks believes that efficiencies like those his company is chasing should eventually expand the global economy.

For now, though, he acknowledges that most of the raw data flowing across the Web has limited economic value: far more useful is specialized data in the hands of analysts with a deep understanding of specific industries. “The promises that are made around the ability to manipulate these very large data sets in real time are overselling what they can do today,” Mr. Marks said.

Some economists argue that it is often difficult to estimate the true value of new technologies, and that Big Data may already be delivering benefits that are uncounted in official economic statistics. Cat videos and television programs on Hulu, for example, produce pleasure for Web surfers — so shouldn’t economists find a way to value such intangible activity, whether or not it moves the needle of the gross domestic product?

In addition, infrastructure investments often take years to pay off in a big way, said Shane Greenstein, an economist at Northwestern University. He cited high-speed Internet connections laid down in the late 1990s that have driven profits only recently. But he noted that in contrast to the Internet’s first wave, which created services like the Web and e-mail, the impact of the second wave — the Big Data revolution — is harder to discern above the noise of broader economic activity.

“It could be just time delay, or it could be that the value just isn’t there,” said Mr. Greenstein, who has studied the competitive success of online businesses in media, advertising and retailing.

Perhaps surprisingly, the parallel most tightly embraced by digital futurists — the rise of the electricity grid — is largely dismissed by those who have studied the history of the subject. The idea is that a ubiquitous Internet will make data and “cloud” computing available anywhere, like electricity through a socket.

The numerical comparisons are tantalizing. As illustrated in “The Electric City,” by Harold L. Platt, the booming quantity and adoption rates of electricity flowing on the Chicago grid in the late 19th and early 20th centuries instantly bring to mind those charts showing data growth today.

Despite those similarities, Mr. Platt, a professor emeritus of history at Loyola University Chicago, said it was unlikely that the revolutions unleashed in manufacturing, domestic life, transportation and high and low society by electricity could ever be matched by the data era. “I’d be hard pressed to quickly draw comparisons,” he said.

But even as Mr. Platt, 68, spoke by cellphone from Chicago, fragments of today’s inescapable data flood found him as he received messages from his grown children. “I have to text them or else they won’t answer me back,” Mr. Platt said gamely. “I’m going with the flow.”

James Glanz is an investigative reporter for The New York Times.

Five myths about big data

By Samuel Arbesman, Friday, August 16, 11:29 AM

http://www.washingtonpost.com/opinions/five-myths-about-big-data/2013/08/15/64a0dd0a-e044-11e2-963a-72d740e88c12_print.html

Samuel Arbesman, an applied mathematician and network scientist, is a senior scholar at the Ewing Marion Kauffman Foundation and the author of “The Half-Life of Facts.” Follow him on Twitter: @Arbesman.

by Samuel Arbesman Big data holds the promise of harnessing huge amounts of information to help us better understand the world. But when talking about big data, there’s a tendency to fall into hyperbole. It is what compels contrarians to write such tweets as “Big Data, n.: the belief that any sufficiently large pile of s--- contains a pony.” Let’s deflate the hype.

1. “Big data” has a clear definition.

The term “big data” has been in circulation since at least the 1990s, when it is believed to have originated in Silicon Valley. IBM offers a seemingly simple definition: Big data is characterized by the four V’s of volume, variety, velocity and veracity. But the term is thrown around so often, in so many contexts — science, marketing, politics, sports — that its meaning has become vague and ambiguous.

There’s general agreement that ranking every page on the Internet according to relevance and searching the phone records of every Verizon customer in the United States qualify as applications of big data. Beyond that, there’s much debate. Does big data need to involve more information than can be processed by a single home computer? If so, marketing analytics wouldn’t qualify, and neither would most of the work done by Facebook. Is it still big data if it doesn’t use certain tools from the fields of artificial intelligence and machine learning? Probably.

Should narrowly focused industry efforts to glean consumer insight from large datasets be grouped under the same term used to describe the sophisticated and varied things scientists are trying to do? There’s a lot of confusion, and industry experts and scientists often end up talking past one another.

2. Big data is new.

By many accounts, big data exploded onto the scene quite recently. “If wonks were fashionistas, big data would be this season’s hot new color,” a Reuters report quipped last year. In a May 2011 report, the McKinsey Global Institute declared big data “the next frontier for innovation, competition, and productivity.”

It’s true that today we can mine massive amounts of data — textual, social, scientific and otherwise — using complex algorithms and computer power. But big data has been around for a long time. It’s just that exhaustive datasets were more exhausting to compile and study in the days when “computer” meant a person who performed calculations.

Vast linguistic datasets, for example, go back nearly 800 years. Early biblical concordances — alphabetical indexes of words in the Bible, along with their context — allowed for some of the same types of analyses found in modern-day textual data-crunching.

The sciences also have been using big data for some time. In the early 1600s, Johannes Kepler used Tycho Brahe’s detailed astronomical dataset to elucidate certain laws of planetary motion. Astronomy in the age of the Sloan Digital Sky Survey is certainly different and more awesome, but it’s still astronomy.

Ask statisticians, and they will tell you that they have been analyzing big data — or “data,” as they less redundantly call it — for centuries. As they like to argue, big data isn’t much more than a sexier version of statistics, with a few new tools that allow us to think more broadly about what data can be and how we generate it.

3. Big data is revolutionary.

In their new book, “Big Data: A Revolution That Will Transform How We Live, Work, and Think,”Viktor Mayer-Schonberger and Kenneth Cukier compare “the current data deluge” to the transformation brought about by the Gutenberg printing press.

If you want more precise advertising directed toward you, then yes, big data is revolutionary. Generally, though, it’s likely to have a modest and gradual impact on our lives.

When a phenomenon or an effect is large, we usually don’t need huge amounts of data to recognize it (and science has traditionally focused on these large effects). As things become more subtle, bigger data helps. It can lead us to smaller pieces of knowledge: how to tailor a product or how to treat a disease a little bit better. If those bits can help lots of people, the effect may be large. But revolutionary for an individual? Probably not.

4. Bigger data is better.

In science, some admittedly mind-blowing big-data analyses are being done. In business, companies are being told to “embrace big data before your competitors do.” But big data is not automatically better.

Really big datasets can be a mess. Unless researchers and analysts can reduce the number of variables and make the data more manageable, they get quantity without a whole lot of quality. Give me some quality medium data over bad big data any day.

And let’s not forget about bias. There’s a common misconception that throwing more data at a problem makes it easier to solve. But if there’s an inherent bias in how the data are collected or examined, a bigger dataset doesn’t help. For example, if you’re trying to understand how people interact based on mobile phone data, a year of data rather than a month’s worth doesn’t address the limitation that certain populations don’t use mobile phones.

Many interesting questions can be explored with little datasets. Big data has refined our idea of six degrees of separation: Facebook has shown that it’s actually closer to four degrees. But the first six-degrees study was done by psychologist Stanley Milgram using a lot of cleverness and a small number of postcards.

Furthermore, although it’s exciting to have massive datasets with incredible breadth, too often they lack much in the way of a temporal dimension. To really understand a phenomenon, such as a social one, we need datasets with large historical sweep. We need long data, not just big data.

5. Big data means the end of scientific theories.

Chris Anderson argued in a 2008 Wired essay that big data renders the scientific method obsolete: Throw enough data at an advanced machine-learning technique, and all the correlations and relationships will simply jump out. We’ll understand everything.

But you can’t just go fishing for correlations and hope they will explain the world. If you’re not careful, you’ll end up with spurious correlations. Even more important, to contend with the “why” of things, we still need ideas, hypotheses and theories. If you don’t have good questions, your results can be silly and meaningless.

Having more data won’t substitute for thinking hard, recognizing anomalies and exploring deep truths.

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Too much information

<http://www.aeonmagazine.com/about/>

Our instincts for privacy evolved in tribal societies where walls didn't exist. No wonder we are hopeless oversharers

by Ian Leslie<http://www.aeonmagazine.com/author/ian-leslie/> 2,000 words

http://www.aeonmagazine.com/living-together/do-we-have-a-privacy-instinct-or-are-we-wired-to-share/

inShare20
<mailto:?subject=Too%20much%20information&body=Too%20much%20information%0AOur%20instincts%20for%20privacy%20evolved%20in%20tribal%20societies%20where%20walls%20didn%27t%20exist.%20No%20wonder%20we%20are%20hopeless%20oversharers%0A%0ARead%20now:%20http://www.aeonmagazine.com/living-together/do-we-have-a-privacy-instinct-or-are-we-wired-to-share/>

In October 2012 a woman from Massachusetts called Lindsey Stone went on a work trip to Washington DC, and paid a visit to Arlington National Cemetery, where American war heroes are buried. Crouching next to a sign that said 'Silence and Respect', she raised a middle finger and pretended to shout while a colleague took her photo. It was the kind of puerile clowning that most of us (well me, anyway) have indulged in at some point, and once upon a time, the resulting image would have been noticed only by the few friends or family to whom the owner of the camera showed it. However, this being the era of sharing, Stone posted the photo to her Facebook profile.

Within weeks, a 'Fire Lindsey Stone' page had materialised, populated by commentators frothing with outrage at a desecration of hallowed ground. Anger rained down on Stone's employer, a non-profit that helps adults with special needs. Her employers decided, reluctantly, that Stone and her colleague would have to leave.

More recently, Edward Snowden's revelations about the panoptic scope of government surveillance have raised the hoary spectre of 'Big Brother'. But what Prism's fancy PowerPoint decks and self-aggrandising logo suggest to me is not so much an implacable, omniscient overseer as a bunch of suits in shabby cubicles trying to persuade each other they're still relevant. After all, there's little need for state surveillance when we're doing such a good job of spying on ourselves. Big Brother isn't watching us; he's taking selfies and posting them on Instagram like everyone else. And he probably hasn't given a second thought to what might happen to that picture of him posing with a joint.

Walls are a relatively recent innovation. Members of pre-modern societies happily coexisted while carrying out almost all of their lives in public view

Stone's story is hardly unique. Earlier this year, an Aeroflot air hostess was fired from her job after a picture she had taken of herself giving the finger to a cabin full of passengers circulated on Twitter. She had originally posted it to her profile on a Russian social networking site without, presumably, envisaging it becoming a global news story. Every day, embarrassments are endured, jobs lost and individuals endangered because of unforeseen consequences triggered by a tweet or a status update. Despite the many anxious articles about the latest change to Facebook's privacy settings, we just don't seem to be able to get our heads around the idea that when we post our private life, we publish it.

At the beginning of this year, Facebook launched the drably named 'Graph Search', a search engine that allows you to crawl through the data in everyone else's profiles. Days after it went live, a tech-savvy Londoner called Tom Scott started a blog in which he posted details of searches that he had performed using the new service. By putting together imaginative combinations of 'likes' and profile settings he managed to turn up 'Married people who like prostitutes', 'Single women nearby who like to get drunk', and 'Islamic men who are interested in other men and live in Tehran' (where homosexuality is illegal).

Scott was careful to erase names from the screenshots he posted online: he didn't want to land anyone in trouble with employers, or predatory sociopaths, or agents of repressive regimes, or all three at once. But his findings served as a reminder that many Facebook users are standing in their bedroom naked without realising there's a crowd outside the window. Facebook says that as long as users are given the full range of privacy options, they can be relied on to figure them out. Privacy campaigners want Facebook and others to be clearer and more upfront with users about who can view their personal data. Both agree that users deserve to be given control over their choices.

But what if the problem isn't Facebook's privacy settings, but our own?

A few years ago George Loewenstein, professor of behavioural economics at Carnegie Mellon University in Pittsburgh, set out to investigate how people think about the consequences of their privacy choices on the internet. He soon concluded that they don't.

In one study, Loewenstein and his collaborators asked two groups of students to fill out an online survey about their lives. Everyone received the same questions, ranging from the innocuous to the embarrassing or potentially incriminating. One group was presented with an official-looking website that bore the imprimatur of their university, and were assured that their answers would remain anonymous. The other group filled out the questions on a garishly coloured website on which the question 'How BAD Are U???' was accompanied by a grinning devil. It featured no assurance of anonymity.

Bizarrely, the 'How BAD Are U???' website was much more likely to elicit revealing confessions, like whether a student had copied someone else's homework or tried cocaine. The first set of respondents reacted cautiously to the institutional feel of the first website and its obscurely concerning assurances about anonymity. The second group fell under the sway of the perennial youthful imperative to be cool, and opened up, in a way that could have got them into serious trouble in the real world. The students were using their instincts about privacy, and their instincts proved to be deeply wayward. 'Thinking about online privacy doesn't come naturally to us,' Loewenstein told me when I spoke to him on the phone. 'Nothing in our evolution or culture has equipped us to deal with it.'

When a boy hit puberty, he disappeared into the jungle, returning a man. In today's digital culture this is precisely the stage at which we make our lives most exposed to the public gaze

We might be particularly prone to disclosing private information to a well-designed digital interface, making an unconscious and often unwise association between ease-of-use and safety. For example, a now-defunct website called Grouphug.us solicited anonymous confessions. The original format of the site was a masterpiece of bad font design: it used light grey text on a dark grey background, making it very hard to read. Then, in 2008, the site had a revamp, and a new, easier-to-read black font against a white background was adopted. The cognitive scientists Adam Alter and Danny Oppenheimer gathered a random sample of 500 confessions from either side of the change. They found that the confessions submitted after the redesign were generally far more revealing than those submitted before: instead of minor peccadilloes, people admitted to major crimes. (Facebook employs some of the best web designers in the world.)

This is not the only way our deeply embedded real-world instincts can backfire online. Take our rather noble instinct for reciprocity: returning a favour. If I reveal personal information to you, you're more likely to reveal something to me. This works reasonably well when you can see my face and make a judgment about how likely I am to betray your confidence, but on Facebook it's harder to tell if I'm trustworthy. Loewenstein found that people were much readier to answer probing questions if they were told that others had already answered them. This kind of rule-of-thumb — when in doubt, do what everyone else is doing — works pretty well when it comes to things such as what foods to avoid, but it's not so reliable on the internet. As James Grimmelmann, director of the intellectual property programme at the University of Maryland, puts it in his article 'Facebook and the Social Dynamics of Privacy' (2008): 'When our friends all jump off the Facebook privacy bridge, we do too.'

Giving people more control over their privacy choices won't solve these deeper problems. Indeed, Loewenstein found evidence for a 'control paradox'. Just as many people mistakenly think that driving is safer than flying because they feel they have more control over it, so giving people more privacy settings to fiddle with makes them worry less about what they actually divulge.

Then again, perhaps none of this matters. Facebook's founder Mark Zuckerberg is not the only tech person to suggest that privacy is an anachronistic social convention about which younger generations care little. And it's certainly true that for most of human existence, most people have got by with very little private space, as I found when I spoke to John L Locke, professor of linguistics at Ohio University and the author of Eavesdropping: An Intimate History (2010). Locke told me that internal walls are a relatively recent innovation. There are many anthropological reports of pre-modern societies whose members happily coexisted while carrying out almost all of their lives in public view.

You might argue, then, that the internet is simply taking us back to something like a state of nature. However, hunter-gatherer societies never had to worry about invisible strangers; not to mention nosy governments, rapacious corporations or HR bosses. And even in the most open cultures, there are usually rituals of withdrawal from the arena. 'People have always sought refuge from the public gaze,' Locke said, citing the work of Paul Fejos, a Hungarian-born anthropologist who, in the 1940s, studied the Yagua people of Northern Peru, who lived in houses of up to 50 people. There were no partitions, but inhabitants could achieve privacy any time they wanted by simply turning away. 'No one in the house,' wrote Fejos, 'will look upon, or observe, one who is in private facing the wall, no matter how urgently he may wish to talk to him.'

The need for privacy remains, but the means to meet it — our privacy instincts — are no longer fit for purpose

From the 1960s onwards, Thomas Gregor, professor of anthropology at Vanderbilt University in Nashville, studied an indigenous Brazilian tribe called the Mehinaku, who lived in oval huts with no internal walls, each housing a family of 10 or 12. Mehinaku villagers were expected to remove themselves altogether from the life of the village at important stages of life, such as adolescence. When a boy hit puberty, he disappeared into the jungle, returning a man. In today's digital culture, of course, this is precisely the stage at which we make our lives most exposed to the public gaze.

Grimmelmann thinks the suggestion that we are voluntarily waving goodbye to privacy is nonsense: 'The way we think about privacy might change, but the instinct for it runs deep.' He points out that today's teenagers retain as fierce a sense of their own private space as previous generations. But it's much easier to shut the bedroom door than it is to prevent the spread of your texts or photos through an online network. The need for privacy remains, but the means to meet it — our privacy instincts — are no longer fit for purpose.

Over time, we will probably get smarter about online sharing. But right now, we're pretty stupid about it. Perhaps this is because, at some primal level, we don't really believe in the internet. Humans evolved their instinct for privacy in a world where words and acts disappeared the moment they were spoken or made. Our brains are barely getting used to the idea that our thoughts or actions can be written down or photographed, let alone take on a free-floating, indestructible life of their own. Until we catch up, we'll continue to overshare.

A long-serving New York Times journalist who recently left his post was clearing his desk when he came across an internal memo from 1983 on computer policy. It said that while computers could be used to communicate, they should never be used for indiscreet or potentially embarrassing messages: 'We have typewriters for that.' Thirty years later, and the Kremlin's security agency has concluded that The New York Times IT department was on to something: it recently put in an order for electric typewriters. An agency source told Russia's Izvestiya newspaper that, following the WikiLeaks and Snowden scandals, and the bugging of the Russian prime minister Dmitry Medvedev at the G20 summit in London, 'it has been decided to expand the practice of creating paper documents'.

Its invention enabled us to capture and store our thoughts and memories but, today, the best thing about paper is that it can be shredded.

Published on 7 August 2013

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