Big Data, bigger expectations, predictable failures...
A bit of the speculation surrounding the Eric Snowden and Bradley Manning matters has furthered revealed that it is no longer limited access to data that negatively impacts analysis. To the contrary, it is too much data and developing sifting methods to sample it in a timely and meaningful fashion that is flummoxing leaders of government, education, and industry. While this may enlarge our horizon of the world, I think the hype machine today is worse than ever (e.g. MOOCs) and possibly social media is a reason why.
In an interview on their book, Big Data: A Revolution That Will Transform How We Live, Work, and Think, authors Viktor Mayer-Schonberger and Kenneth Cukier encapsulate a real concern that echo the lyrics of John Perry Barlow, you ain't going to learn what you don't want to know.
"We are very concerned about what we call in our book 'the dark side of big data.' However the real challenge is that the problem is not necessarily where we initially tend to think it is, such as surveillance and privacy. After looking into the potential misuses of big data, we became much more troubled by 'propensity' -- that is, big data predictions being used to police and punish. And by the 'fetishization' of data that may occur, whereby organizations may blindly defer to what the data says without understanding its limitations. "(http://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544002695/ref=sr_1_1?ie=UTF8&qid=1376668263&sr=8-1&keywords=big+data
Big data could have a big impact but only if it is used to uncover the unfathomable as opposed to reify the ideological, expect that we are going to see much more analysis based on it for both purposes.
I wonder if the IBM curriculum people are going to take a critical perspective in developing an authentic and rigorous method of analysis. Fingers crossed.... http://chronicle.com/article/IBMUniversities-Team-Up/141111/?cid=wc&utm_source=wc&utm_medium=en