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This may be oversimplifying, but the nuance with privacy is that it’s not just about securing personally identifiable information (PII), it’s also about considering what other related pieces of information could be used together to infer PII. Therefore, you need to be very careful about the information you share, and the intentions of the people who collect it.

but the nuance with privacy is that it’s not just about securing personally identifiable information (PII), it’s also about considering what other related pieces of information could be used together to infer PII. Therefore, you need to be very careful about the information you share, and the intentions of the people who collect it.

As we train people to become Data Scientists and design sophisticated algorithms, I encourage practitioners and leaders to consider the trade offs between utility and privacy. This is a new, emerging and complex area, and I’ll explore it further in future posts.

The expression "Big Brother" has become dated. Experts would seem to have reached consensus on the term "Big Data" to describe the new favorite topic of discussion in boardrooms, at conventions like Berlin's re:publica last week, and in a number of new books. Big Data promises both total control and the logical management of our future in all aspects of life.

New is the way companies, government agencies and scientists are now beginning to interpret and analyze their data resources. Because storage space costs almost nothing nowadays, computers, which are getting faster and faster, can link and correlate a wide variety of data around the clock. Algorithms are what create order from this chaos. They dig through, discovering previously unknown patterns and promptly revealing new relationships, insights and business models. Though the term Big Data means very little to most people, the power of algorithms is already everywhere. Credit card companies can quickly recognize unusual usage patterns, and hence automatically warn cardholders when large sums are suddenly being charged to their cards in places where they have never been. Energy companies use weather

According to official figures, since the Swedish capital Stockholm began using algorithms to manage traffic, drive times through the city's downtown area have been cut in half and emissions reduced by 10 percent. Online merchants have recently started using the analyses to optimize their selling strategies. The widespread phrase "Customers who bought this item also bought …" is only one example of the approach.

Princeton's Arvind Narayanan and Ed Felten have published a stinging rebuttal, pointing out the massive holes in Cavoukian and Castro's arguments -- cherry picking studies, improperly generalizing, ignoring the existence of multiple re-identification techniques, and so on.

Cavoukian and Castro are rightly excited by Big Data and the new ways that scientists are discovering to make use of data collected for one purpose in the service of another. But they do not admit that the same theoretical advances that unlock new meaning in big datasets also unlock new ways of re-identifying the people whose data is collected in the set.

Re-identification is part of the Big Data revolution: among the new meanings we are learning to extract from huge corpuses of data is the identity of the people in that dataset. And since we're commodifying and sharing these huge datasets, they will still be around in ten, twenty and fifty years, when those same Big Data advancements open up new ways of re-identifying -- and harming -- their subjects.

Two professors, computer scientist George Mohler and anthropologist Jeffrey Brantingham, who specializes in crime scenarios, were instrumental in developing the predictive method of fighting crime. Their program is based on models for predicting the aftershocks of earthquakes.

The two data experts, Mohler and Brantingham, have since started a company and are marketing their product, Predictive Policing, worldwide

"Security is one of the biggest growth areas for Big Data applications," says Schröder. In addition to crime and terrorism, Splunk focuses on the growing number of attacks in, and by means of, the Internet and its software can detect hacker attacks or other cyber attacks. "We are positioning ourselves for an expanding cyber war," Schröder says. But the data hunters' new war also has many civilian aspects.

but we do know that third-party data brokers sell all manner of information to businesses, including “police officers’ home addresses, rape sufferers, and genetic disease sufferers” as well as suspected alcoholics and cancer and HIV/AIDS patients.

The first is that almost everything is personal. In the words of computer scientists Arvind Narayanan (Princeton

this model simply doesn’t reflect the reality of the deeply unequal situation we now face. Those who wield the tools of data tracking and analytics have far more power than those who don’t.

The problem, of course, is that those students represent the precise group MOOCs are meant to serve. “MOOCs were supposed to be the device that would bring higher education to the masses,” Jonathan Rees noted. “However, the masses at San Jose State don’t appear to be ready for the commodified, impersonal higher education that MOOCs offer.” Thrun’s cavalier disregard for the SJSU students reveals his true vision of the target audience for MOOCs: students from the posh suburbs, with 10 tablets apiece and no challenges whatsoever—that is, the exact people who already have access to expensive higher education. It is more than galling that Thrun blames students for the failure of a medium that was invented to serve them, instead of blaming the medium that, in the storied history of the “correspondence” course (“TV/VCR repair”!), has never worked. For him, MOOCs don’t fail to educate the less privileged because the massive online model is itself a poor tool. No, apparently students fail MOOCs because those students have the gall to be poor, so let’s give up on them and move on to the corporate world, where we don’t have to be accountable to the hoi polloi anymore, or even have to look at them, because gross.

SG_Debug && SG_Debug.pagedebug && window.console && console.log && console.log('[' + (new Date()-SG_Debug.initialTime)/1000 + ']' + ' Bottom of header.jsp'); SlateEducationGetting schooled.Nov. 19 2013 11:43 AM The King of MOOCs Abdicates the Throne 7.3k 1.2k 101 Sebastian Thrun and Udacity’s “pivot” toward corporate training. By Rebecca Schuman &nbsp; Sebastian Thrun speaks during the Digital Life Design conference on Jan. 23, 2012, in Munich. Photo by Johannes Simon/Getty Images requirejs(["jquery"], function($) { if ($(window).width() < 640) { $(".slate_image figure").width("100%"); } }); Sebastian Thrun, godfather of the massive open online course, has quietly spread a plastic tarp on the floor, nudged his most famous educational invention into the center, and is about to pull the trigger. Thrun—former Stanford superprofessor, Silicon Valley demigod, and now CEO of online-course purveyor Udacity—just admitted to Fast Company’s openly smitten Max Chafkin that his company’s courses are often a “lousy product.” Rebecca Schuman Rebecca Schuman is an education columnist for Slate. Follow This is quite a “pivot” from the Sebastian Thrun, who less than two years ago crowed to Wired that the unstemmable tide of free online education would leave a mere 10 purveyors of higher learning in its wake, one of which would be Udacity. However, on the heels of the embarrassing failure of a loudly hyped partnership with San Jose State University, the “lousiness” of the product seems to have become apparent. The failures of massive online education come as no shock to those of us who actually educate students by being in the same room wit

nd why the answer is not the MOOC, but the tiny, for-credit, in-person seminar that has neither a sexy acronym nor a potential for huge corporate partnerships.

HP won't be&nbsp;the first company to host a completely virtual shareholder meeting, but it may very well&nbsp;be&nbsp;the largest.

In 2011, just 21 companies used Broadridge Financial Solutions, a primary provider of online shareholder meeting technology, to hold&nbsp;virtual-only meetings. By 2014, that number had grown to 53.

Big companies, including Intel and Microsoft,&nbsp;have hosted what's known as hybrid meetings, in which a physical event&nbsp;is held but&nbsp;investors can also "attend" online.

So far, many companies have tried to dispel such fears by noting that the data they gather, store and analyze remains "anonymous." But that, as it turns out, is not entirely accurate, in that it sells the power of data analysis radically short. Take the analysis of anonymous movement profiles, for example. According to a current study by the online journal Scientific Reports, our mobility patterns are so different that that they can be used to "uniquely identify 95 percent of the individuals." The more data is in circulation and available for analysis, the more likely it is that anonymity becomes "algorithmically impossible," says Princeton computer scientist Arvind Narayanan. In his blog, Narayanan writes that only 33 bits of information are sufficient to identify a person.

A study by New York advertising agency Ogilvy One concludes that 75 percent of respondents don't want companies to store their personal data, while almost 90 percent were opposed to companies tracking their surfing behavior on the Internet.

Is it truly desirable for cultural assets like TV series or music albums to be tailored to our predicted tastes by means of data-driven analyses? What happens to creativity, intuition and the element of surprise in this totally calculated world?

The self-confident founders of Kreditech lend money through the Internet: short-term mini-loans of up to €500, with the average customer receiving €109. Instead of requiring credit information from their customers, they determine the probability of default on their own, using a social scoring method that consists of high-speed data analysis. "Ideally, the money should be in customers' accounts within 15 minutes of approval.

Kreditech also requires access to Facebook profiles, so that it can verify whether a user's photo and location match information on other social networking sites, like Xing and LinkedIn -- and whether his or her friends include many with similar education levels or many colleagues working in the same company.

All of this increases the likelihood that Kreditech is dealing with a real person.