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article imageOp-Ed: Privacy is not dead, it is crowd-sourced

By Edgar Wilson     Apr 6, 2015 in Internet
Which is the biggest threat to privacy: spying or sharing?
Outrage at government programs may miss the real culprit responsible for killing privacy as we once knew it.
Activists have made a modern pastime out of railing against government spying programs — from America’s National Security Administration (NSA) conducting mass-surveillance programs, to international eavesdropping co-ops. As digital spying technology improves, and is adopted by government (and extra-governmental) agencies to better monitor the world’s citizens, experts and alarmists alike warn that a frightening new authoritarianism is not only possible, but already inevitable.
Like it or hate it, privacy is dead — or so many observers try to claim.
But for all the noise about data breaches, government snooping, and the breakdown of traditional notions of information privilege, the vast collection of information online called “Big Data” is at least as great a threat to old-fashioned “privacy” as any deliberate hack.
For one thing, participation in everything from social media to downloading updates and software involves signing-off on marathon-length legal documents; the tendency for users to skip the text and click “Agree” has bound them to share virtually anything and everything an app provider could care to ask for.
Crying foul when government institutions skip the “User Agreement” and go straight to monitoring electronic chatter suggests that, on principle, people are more comfortable exposing their personal lives to marketers than to bureaucrats.
But the creative (if disingenuous) reapplication of social data goes even further. The increasing sophistication of Big Data algorithms means that spies don’t need to spy to gain personal info—they just need you to keep broadcasting seemingly banal information.
It all started with efforts to use public information — the stuff of social media — to create better targeted advertising. This is, after all, how Facebook was able to make one of the highest-valued IPOs of all time; sophisticated knowledge of the preferences, interests, and especially shopping habits of its users could be translated into online ads designed especially for those most likely to click and buy a given item.
The algorithms that manage these vast swaths of volunteered personal information turned the innocuous (Americans like watching Kevin Spacey movies, and tend to binge view TV series) into the lucrative (“House of Cards,” the first Netflix Original Series).
The size of the data means effective algorithms can look for virtually any correlation — it was only a matter of time before, instead of better marketing, data analysts turned their trade to finding more personal messages behind the noise.
Add in the GPS-guided precision of mobile applications, streaming feeds by the megabyte every minute from billions of users around the world, and the challenge is less about gaining access, and more about finding ways to sort through all the free, voluntary data.
And this trove of data, with a little creative research, yields a much clearer, personal profile than what is simple visible on a given profile page. Likes and dislikes, movement patterns, relationships — the things we broadcast about ourselves most willingly are the things that actually make us the most vulnerable; or, in certain hands, the most useful.
Broad associations can lead to powerful correlations, and more data will only lead to more such systems of deriving intimate meaning, predictions, and conclusions from basic online behavior. Spies (and the governments backing them) can, effectively, use voluntary information to achieve the same ends as the ‘private’ data they are accused of snooping to collect.
What this all amounts to, is that spies didn’t kill privacy—we did, voluntarily and en masse.
Maybe it is worth redefining “privacy” as “the mystery of others.” That is, nothing is hidden, except what we choose not to look for. Privacy, in effect, has been crowd-sourced: an individual can no longer hide what he or she chooses to hide, but the collective public can ignore — and lend privacy to — what they choose to ignore.
Even the supposed anonymity of chat rooms can be undermined by the simplest, stereotypical features that inform how people communicate can reveal personal details. As Rutgers professor Sharon Stoerger explained in her review of the subject, the most telling features of a person’s communication style are often not even recognizable to that person — much less within his or her capacity to change or disguise. For all the publicity ‘catfishing’ gets, basic personality traits are subconsciously communicated all the time — if anyone cares to look and listen for them.
Algorithms can tell us virtually anything: who to marry, where to live, what job to take, who to hire, where crime will occur, how diseases move, who is cheating on welfare. This information has always existed, but now there are more devices to collect and broadcast it, alongside more dynamic ways to derive practical interpretations of it; and more of both are on the way.
Much is made of protecting “sensitive data” like Social Security numbers, bank accounts, and credit card data. Security walls spring up around what we presume are the most sensitive or valuable targets (banks, hospitals). This may be useful for ascribing blame in the wake of an attack (at least, an attack that we eventually discover) but it has no bearing on actual security.
So the only question now is, how much do you want to know? Privacy, understood as a shield we can carry to cover ourselves from the world, no longer exists. We can only lend privacy to others, by choosing the mystery of others instead of looking at all the information that has already been compiled.
This opinion article was written by an independent writer. The opinions and views expressed herein are those of the author and are not necessarily intended to reflect those of
More about Cybersecurity, big data, Social media, NSA spying, Privacy
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