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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.

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?

So even at an order of magnitude smaller than the experimental effect, VMP could have serious consequences. “Four to 8 percent would get any campaign manager excited,” says Brian Keegan, a computational social scientist at Harvard Business School. “At the end of the day, the fact is that in a lot of races it only takes a swing of 3 or 4 percent. If the search engine is one or two percent, that’s still really persuasive.”

as Harvard Law professor Jonathan Zittrain has proposed—Facebook didn’t push the “vote” message to a random 61 million users? Instead, using the extensive information the social network maintains on all its subscribers, it could hypothetically push specific messaging to supporters or foes of specific legislation or candidates. Facebook could flip an election; Zittrain calls this “digital gerrymandering.” And if you think that companies like the social media giants would never do such a thing, consider the way that Google mobilized its users against the Secure Online Privacy Act and PROTECT IP Act, or “SOPA-PIPA.

tempting to think of algorithms as the very definition of objective, they’re not. “It’s not really possible to have a completely neutral algorithm,” says Jonathan Bright, a research fellow at the Oxford Internet Institute who studies elections.

All a hacker has to do is use personal information that’s publicly available on one service to gain entry into another.

Since that awful day, I’ve devoted myself to researching the world of online security. And what I have found is utterly terrifying. Our digital lives are simply too easy to crack.

The common weakness in these hacks is the password. It’s an artifact from a time when our computers were not hyper-connected. Today, nothing you do, no precaution you take, no long or random string of characters can stop a truly dedicated and devious individual from cracking your account. The age of the password has come to an end; we just haven’t realized it yet.

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Encouraged by Watson Sr. and his executive team, employees often formed their own study groups. One, known as the Owl Club, allowed employees to study any subject they wanted at company expense. Such programs evolved into adult learning classes, and eventually into grants for employees to pursue college credits and degrees

Today, industry specialists around the world in IBM Global Business Services use an array of e-learning tools—including podcasts and Twitter—customer on-site classes, and IBM conferences and classrooms to educate customers on everything from the use of social media and cloud computing, to how to build a smarter rail system. And IBM employees worldwide take advantage of their networked community to draw upon each other’s skills day and night to solve customer problems and develop the capabilities clients value most.

Although there is no single definition of active learning approaches, they include asking students to answer questions by using handheld clickers, calling on individuals or groups randomly, or having students clarify concepts to each other and reach a consensus on an issue.

But I don’t think there should be a monolithic stance about lecture or no lecture. There are still times when lectures will be needed, but the traditional mode of stand-and-deliver is being demonstrated as less effective at promoting student learning and preparing future teachers.”

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