BIG DATA : THREATENING PERSONAL LIBERTY
I was traveling to Bozeman last fortnight, while waiting to board I saw latest issue of Newsweek magazine. The lead story was about how the big data tilted results in recent elections held in many democracy.
It is very difficult for a layman to understand or believe it but it is possible.
Not only elections, it is possible to predict and answer some of the questions like : which paint color is most likely to tell you that a used car is in good shape, how can officials identify the most dangerous Mumbai City manholes before they explode, how google searches predict the spread of H1N1 out break.
First, let us understand Big Data, it refers to our newfound ability to crunch the vast quantity of information , analyze it instantly and draw conclusions which on many times astonishing one. this is a revolution on par with the printing press and internet. Big data is going to change the way we think about business, health, politics, education, and innovation. But it is also going to poses fresh threats, from the end of privacy as we know it to the prospect of being penalized for the things we have not even done yet, based on Big data's ability to predict our future behavior. if proper checks and balances are not in place, the state will become autocrat.
Data Revolution Is Already In Place
Our digital spectrum is already expanding. In the tear 2003, the scientists first decoded the human genome, it took them a decade of intensive work to sequence the three billion base pairs. A decade later, a single facility can sequence that much data in a single day. In the field of finance, about seven billion shares change hands every day in US Equity market alone, of which around two thirds is traded by computer algorithms based on mathematical models that crunch mountains of data to predict gains while trying to reduce risk. Think about the data generated by internet companies. Google processes more than 24 petabytes of data per day, a volume that is thousands times the quantity of all printed material in the US Library of Congress. Facebook, a company which even did not exit a decade ago, generate astronomical volume of data :
Darker Side of Big DataAs we that if someone knows things about us has some measure of control over us, and someone who knows everything about us has a lot of control over us. Surveillance facilitates control. Bad news is that Big Data knows everything about us.
Manipulation doesn’t have to involve overt advertising. It can be product placement that makes sure you see pictures that have a certain brand of car in the background. Or just increasing how often you see those cars. This is, essentially, the business model of search engines. In their early days, there was talk about how an advertiser could pay for better placement in search results. After public outcry and subsequent guidance from the FTC, search engines visually differentiated between “natural” results by algorithm and paid results. So now you get paid search results in Google framed in yellow and paid search results in Bing framed in pale blue. This worked for a while, but recently the trend has shifted back.
A truly sinister social networking platform could manipulate public opinion even more effectively. By amplifying the voices of people it agrees with, and dampening those of people it disagrees with, it could profoundly distort public discourse. China does this with its 50 Cent Party: people hired by the government to post comments on social networking sites supporting, and challenge comments opposing, party positions. Samsung has done much the same thing.
Many companies manipulate what you see based on your user profile: Google search, Yahoo News, even online newspapers like The New York Times. This is a big deal. The first listing in a Google search result gets a third of the clicks, and if you’re not on the first page, you might as well not exist. The result is that the Internet you see is increasingly tailored to what your profile indicates your interests are. This leads to a phenomenon that political activist Eli Pariser has called the “filter bubble”: an Internet optimized to your preferences, where you never have to encounter an opinion you don’t agree with. You might think that’s not too bad, but on a large scale it’s harmful. We don’t want to live in a society where everybody only ever reads things that reinforce their existing opinions, where we never have spontaneous encounters that enliven, confound, confront, and teach us.
In 2012, Facebook ran an experiment in control. It selectively manipulated the newsfeeds of 680,000 users, showing them either happier or sadder status updates. Because Facebook constantly monitors its users—that’s how it turns its users into advertising revenue—it was easy to monitor the experimental subjects and collect the results. It found that people who saw happier posts tended to write happier posts, and vice versa. Facebook only did this for a week that too with a small database, and the effect was small. But once sites like Facebook figure out how to do this effectively, the effects will be profitable. Not only do women feel less attractive on Mondays, they also feel less attractive when they feel lonely, fat, or depressed. We’re already seeing the beginnings of systems that analyze people’s voices and body language to determine mood; companies want to better determine when customers are getting frustrated and when they can be most profitably upsold. Manipulating those emotions to better market products is the sort of thing that’s acceptable in the advertising world, even if it sounds pretty horrible to us.This is all made easier because of the centralized architecture of so many of our systems. Companies like Google and Facebook sit at the center of our communications. This gives them enormous power to manipulate and control.
There are unique harms that come from using surveillance data in politics. Election politics is very much a type of marketing, and politicians are starting to use personalized marketing’s capability to discriminate as a way to track voting patterns and better “sell” a candidate or policy position. Candidates and advocacy groups can create ads and fundraising appeals targeted to particular categories: people who earn more than say Rs.8,00,000 a year, car owners, people who have read news articles on one side of a particular issue, unemployed ex-servicemen... anything you can think of. They can target outraged ads to one group of people, and thoughtful policy-based ads to another. They can also finely tune their get-out-the-vote campaigns on Election Day and more efficiently gerrymander districts between elections. This will likely have fundamental effects on democracy and voting.
Psychological manipulation—based both on personal information and control of the underlying systems—will get better and better. Even worse, it will become so good that we won’t know we’re being manipulated !
This way Big Data allows for more surveillance of our lives while it makes some of the legal means for protecting privacy largely obsolete. It also renders ineffective the core technical method of preserving anonymity. Just as unsettling, Big Data's predictions about individuals may be used to, in effect, punish people for their propensities not their actions. This denies free will and erode human dignity. Another threat is luring the people into applying the techniques where they do not perfectly fit, or into feeling overly confident in the results of the analyses.
Catch Bull By Horn
From nuclear technology to bio-engineering, we first build tools that we discover can harm us and only later set out to devise the safety mechanisms, to protect us from those new tools. Big Data also takes place alongside other areas of concern that present challenges with no absolute solutions, just ongoing questions about how we order our world. Every generation has responsibility to address these issues anew. So our collective responsibility is to understand the darker side of this powerful technology, support its development-and seize its rewards.We have to ensure that people and their personal liberties are well protected at the same time the technology is promoted. Keep in mind, the society must not let Big Data develop beyond the reach of human ability to shape the technology.
It is very difficult for a layman to understand or believe it but it is possible.
Not only elections, it is possible to predict and answer some of the questions like : which paint color is most likely to tell you that a used car is in good shape, how can officials identify the most dangerous Mumbai City manholes before they explode, how google searches predict the spread of H1N1 out break.
First, let us understand Big Data, it refers to our newfound ability to crunch the vast quantity of information , analyze it instantly and draw conclusions which on many times astonishing one. this is a revolution on par with the printing press and internet. Big data is going to change the way we think about business, health, politics, education, and innovation. But it is also going to poses fresh threats, from the end of privacy as we know it to the prospect of being penalized for the things we have not even done yet, based on Big data's ability to predict our future behavior. if proper checks and balances are not in place, the state will become autocrat.
Data Revolution Is Already In Place
Our digital spectrum is already expanding. In the tear 2003, the scientists first decoded the human genome, it took them a decade of intensive work to sequence the three billion base pairs. A decade later, a single facility can sequence that much data in a single day. In the field of finance, about seven billion shares change hands every day in US Equity market alone, of which around two thirds is traded by computer algorithms based on mathematical models that crunch mountains of data to predict gains while trying to reduce risk. Think about the data generated by internet companies. Google processes more than 24 petabytes of data per day, a volume that is thousands times the quantity of all printed material in the US Library of Congress. Facebook, a company which even did not exit a decade ago, generate astronomical volume of data :
- Hive is Facebook’s data warehouse, with 300 petabytes of data
- Facebook generates 4 new petabytes of data per day
- Facebook now sees 100 million hours of daily video watch time
- Users generate 4 million likes every minute
- More than 250 billion pictures have been uploaded to Facebook
- This equates to 350 million photos per day
Interesting facts about Google's YouTube service :
- 300 hours of video are uploaded to YouTube every minute !
- Almost 5 billion videos are watched on YouTube every single day.
- YouTube gets over 30 million visitors per day
By Hilbert's reckoning, more than 300 exabytes of stored data existed in 2007, to understand what this means in slightly more human terms, think of like this : a full length bollywood movie in digital form can be compressed into one gigabyte file. One exabyte is equal to one billion gigabytes and one petabyte is equal to 1000000 gigabytes. And by the way in the year 2007 only 7 per cent data was analog (i.e. paper, books, photographic prints etc.) and remaining 93 per cent was digital.
Big Data is about applying math to huge quantities of data in order to infer probabilities : the likelihood that an email message is spam; that a typed letter 'tech' are supposed to be 'the'; that the trajectory and velocity of a person jay-walking mean he will make it across the street in time-self driving car need only slow slightly, The key is that these systems perform well because they are fed with lots of data on which to base their predictions.Moreover, the systems are built to improve themselves over time, by keeping a tab on what are the best signals and patterns to look for as more data fed in.
In the coming time, many aspects of our world will be augmented or replaced by computer systems that today are the sole purview of the human judgement. Not just that driving or match making, even more complex tasks. After all, Google can rank the most relevant web-site, Facebook knows our likes, LinkedIn divines whom we know, Amazon recommend the most suitable product or ideal book. In future, same technology based on more complex algorithms will be applied to diagnosing illness, recommending treatments, identifying 'criminals' before one actually commit 'crime' possibilities are endless. Just as the internet radically changed the world by adding communication to the computers and other similar devices, Big Data may transform fundamental aspects of life by giving it a quantitative dimension it never had before.
Interactions Now Become Data
The next frontiers of datafication are more personal : our relationships, experiences, and moods. The idea of datafication is now the bread and butter of web's social media companies. Social networking platforms do not offer us a way to find out and stay in touch with friends, colleagues and relatives, they take intangible elements of our everyday life and transform them into data that can be used to do new things. Facebook datafied relationships; they always existed and constituted information, but they were never formally defined as data until Facebook made it 'social graph'. Twitter enabled the datafication of sentiment by creating an easy way for people to record and share their stray thoughts, which had previously been lost to the winds of time. LinkedIn datafied our long past professional experiences, just as Maur transformed old logbooks, turning that information into predictions about our present and future: whom we may know, or a job we may want.
The potential uses of this datafication are extraordinary. Any startup needs to look. into adopting the social graph to use as signals for establishing credit scores.
Darker Side of Big DataAs we that if someone knows things about us has some measure of control over us, and someone who knows everything about us has a lot of control over us. Surveillance facilitates control. Bad news is that Big Data knows everything about us.
Manipulation doesn’t have to involve overt advertising. It can be product placement that makes sure you see pictures that have a certain brand of car in the background. Or just increasing how often you see those cars. This is, essentially, the business model of search engines. In their early days, there was talk about how an advertiser could pay for better placement in search results. After public outcry and subsequent guidance from the FTC, search engines visually differentiated between “natural” results by algorithm and paid results. So now you get paid search results in Google framed in yellow and paid search results in Bing framed in pale blue. This worked for a while, but recently the trend has shifted back.
Last month, European Union slapped Google with a record-breaking $2.7 billion fine , charging that it had manipulated search results in a way that gives an “illegal advantage” to its own services while harming the company’s rivals. The Union follows a seven-year investigation into Google and requires the company to change its practices within 90 days or face additional penalties. At issue for EU regulators is Google's Comparision Shopping Service, which EU believes the company had boosted unfairly by giving it “prominent placement” in search results — all the while having “demoted rival comparison shopping services.” It is just small example how the Big Data can manipulate results or tilts towards 'x' or 'y'.When you scrol through your Facebook feed, you don’t see every post by every friend; what you see has been selected by an automatic algorithm that’s not made public. But someone can pay to increase the likelihood that their friends or fans will see their posts. Corporations paying for placement is a big part of how Facebook makes big moolah. Similarly, a lot of those links to additional articles at the bottom of news pages are paid placements.
The potential for manipulation here is enormous. Here’s one example. During 2012 election in US, Facebook users had the opportunity to post an “I Voted” icon, much like the real stickers many of us get at polling places after voting. There is a documented bandwagon effect with respect to voting; you are more likely to vote if you believe your friends are voting, too. This manipulation had the effect of increasing voter turnout 0.4% nationwide. So far, so good. But now imagine if Facebook manipulated the visibility of the “I Voted” icon based on either party affiliation or some decent proxy of it: ZIP code of residence, blogs linked to, URLs liked, and so on. It didn’t, but if it did, it would have had the effect of increasing voter turnout in one direction. It would be hard to detect, and it wouldn’t even be illegal. Facebook could easily tilt a close election by selectively manipulating what posts its users see. Google might do something similar with its search results.A truly sinister social networking platform could manipulate public opinion even more effectively. By amplifying the voices of people it agrees with, and dampening those of people it disagrees with, it could profoundly distort public discourse. China does this with its 50 Cent Party: people hired by the government to post comments on social networking sites supporting, and challenge comments opposing, party positions. Samsung has done much the same thing.
Many companies manipulate what you see based on your user profile: Google search, Yahoo News, even online newspapers like The New York Times. This is a big deal. The first listing in a Google search result gets a third of the clicks, and if you’re not on the first page, you might as well not exist. The result is that the Internet you see is increasingly tailored to what your profile indicates your interests are. This leads to a phenomenon that political activist Eli Pariser has called the “filter bubble”: an Internet optimized to your preferences, where you never have to encounter an opinion you don’t agree with. You might think that’s not too bad, but on a large scale it’s harmful. We don’t want to live in a society where everybody only ever reads things that reinforce their existing opinions, where we never have spontaneous encounters that enliven, confound, confront, and teach us.
In 2012, Facebook ran an experiment in control. It selectively manipulated the newsfeeds of 680,000 users, showing them either happier or sadder status updates. Because Facebook constantly monitors its users—that’s how it turns its users into advertising revenue—it was easy to monitor the experimental subjects and collect the results. It found that people who saw happier posts tended to write happier posts, and vice versa. Facebook only did this for a week that too with a small database, and the effect was small. But once sites like Facebook figure out how to do this effectively, the effects will be profitable. Not only do women feel less attractive on Mondays, they also feel less attractive when they feel lonely, fat, or depressed. We’re already seeing the beginnings of systems that analyze people’s voices and body language to determine mood; companies want to better determine when customers are getting frustrated and when they can be most profitably upsold. Manipulating those emotions to better market products is the sort of thing that’s acceptable in the advertising world, even if it sounds pretty horrible to us.This is all made easier because of the centralized architecture of so many of our systems. Companies like Google and Facebook sit at the center of our communications. This gives them enormous power to manipulate and control.
There are unique harms that come from using surveillance data in politics. Election politics is very much a type of marketing, and politicians are starting to use personalized marketing’s capability to discriminate as a way to track voting patterns and better “sell” a candidate or policy position. Candidates and advocacy groups can create ads and fundraising appeals targeted to particular categories: people who earn more than say Rs.8,00,000 a year, car owners, people who have read news articles on one side of a particular issue, unemployed ex-servicemen... anything you can think of. They can target outraged ads to one group of people, and thoughtful policy-based ads to another. They can also finely tune their get-out-the-vote campaigns on Election Day and more efficiently gerrymander districts between elections. This will likely have fundamental effects on democracy and voting.
Psychological manipulation—based both on personal information and control of the underlying systems—will get better and better. Even worse, it will become so good that we won’t know we’re being manipulated !
This way Big Data allows for more surveillance of our lives while it makes some of the legal means for protecting privacy largely obsolete. It also renders ineffective the core technical method of preserving anonymity. Just as unsettling, Big Data's predictions about individuals may be used to, in effect, punish people for their propensities not their actions. This denies free will and erode human dignity. Another threat is luring the people into applying the techniques where they do not perfectly fit, or into feeling overly confident in the results of the analyses.
Catch Bull By Horn
From nuclear technology to bio-engineering, we first build tools that we discover can harm us and only later set out to devise the safety mechanisms, to protect us from those new tools. Big Data also takes place alongside other areas of concern that present challenges with no absolute solutions, just ongoing questions about how we order our world. Every generation has responsibility to address these issues anew. So our collective responsibility is to understand the darker side of this powerful technology, support its development-and seize its rewards.We have to ensure that people and their personal liberties are well protected at the same time the technology is promoted. Keep in mind, the society must not let Big Data develop beyond the reach of human ability to shape the technology.
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