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Published: December 2, 2013
 / Winter 2013 / Issue 73

Business Literature: Best Business Books 2013

Best Business Books 2013: Digitization

Third, big data is messy and imprecise: “We don’t give up on exactitude entirely,” the authors write, “we only give up our devotion to it.” Theoretic understanding and precision might not be needed to profit from knowing just in time about the right messy, unexplained correlations.

Much of big data starts out as a side effect of human activity, without much intrinsic perceived value. This is so-called data exhaust: the amount of time our cursors hover over icons on Web pages, the daily price of butter in a million grocery stores, or the locations of legions of mobile phones minute by minute. The authors of Big Data regard this as data ore: a store of potential value that can be transformed into tangible value (only) through the extraction of useful knowledge and its application, whether that is to sell more units of a commercial product or to more effectively deal with natural disasters.

Mayer-Schönberger and Cukier aren’t uncritical cheerleaders for big data. They know that processing some of this data ore—the data connected to what we previously thought of as privacy or anonymity—may have toxic results. Consider AOL’s release of anonymized data about millions of its users’ behaviors for legitimate social science research in 2006. By applying big-data analysis, a journalist was able to lift the veil of anonymity and identify specific people—akin to the way Iranian revolutionaries pieced together shredded documents when they invaded the U.S. embassy in 1979. So although the NSA’s leaked PRISM program did not purport to collect the contents of citizens’ communications, the metadata gathered could inevitably reveal an enormous amount about them.

If “dataveillance” on this scale doesn’t give you the willies, consider that algorithms similar to those used to analyze flu trends could be used to predict which individuals are likely to commit crimes. A society that stops crimes before they occur? There was a movie about that flavor of police state called Minority Report. The authors of Big Data caution that the dangers of pervasive data-veillance are as real as the opportunities they foresee.

Harnessing Collective Action

Big data involves computers and networks slicing and dicing the artifacts of human and machine behavior in new ways, while socialstructing concerns a similar form of reuse through rearrangement. Socialstructing (the word, in its various forms, was coined by Marina Gorbis, the executive director of the Institute for the Future [IFTF], a venerable nonprofit think tank located in Silicon Valley) is a way to use connective and computational technologies to bring people together so they can restructure old ways of doing things and invent new ones.

The word socialstructing might or might not enter the public vocabulary the way big data has, but the phenomenon is already a significant enabler of collective action. The power of collective action—the force that brought us agriculture, cities, science, capitalism, and democracy, as well as slavery, fascism, and organized warfare—is determined in part by how human beings do or do not collaborate. Now that the Internet has lowered nearly to zero the transaction costs for large numbers of people to communicate, coordinate, and engage in collective action, a wide variety of socialstructed institutions are emerging in diverse fields: citizen science (Foldit), collaborative consumption (Airbnb), crowdsourcing (Genomera), crowdfunding (Kickstarter), co-working (the League of Extraordinary Coworking Spaces), microventure funding (, and peer-to-peer online learning (P2PU).

Socialstructing provides a name for a trend that some of us have been watching emerge for more than a decade. I’ve written about “technologies of cooperation.” Yochai Benkler described a new nonmarket form of economic production. Clay Shirky focused on how digital networks lower the barriers to coordinating collective action. Rachel Botsman extended the trend into what is now being called “the sharing economy.” Michael Nielsen described how this then-unnamed phenomenon was changing the way science is done. Now Marina Gorbis has pulled these strands together in The Nature of the Future: Dispatches from the Socialstructed World, by pointing out how diverse signals of social production are transforming a wide variety of institutions. (Disclaimer: I was a contractor for IFTF, and the book cites my work on online co-learning.)

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