The social side of discovery

Research, and its cyber tool "online search", is on a roll. From the analytics developed for digital consumer media, to the myriad applications of GPS technology, to the sober business of data mining used by large enterprises, we can do so much more -- cheaper, better and faster -- than ever before.

One example at hand is a story in The New York Times about the emergence of "e-discovery" software now coming into use that is dramatically improving the productivity of one of the most time intensive, aggravating and costly activities in the legal trade. In a nutshell, one of these algorithms can do the work of hundreds of lawyers in large-dollar litigation.

Without getting into the potential impacts of such software on the legal profession itself, it is interesting to note some the things it can do.

For starters, there is what is called the "sociological" branch of e-discovery that  is discussed in the Times article:

"Engineers and linguists at Cataphora, an information-sifting company based in Silicon Valley, have their software mine documents for the activities and interactions of people — who did what when, and who talks to whom. The software seeks to visualize chains of events. It identifies discussions that might have taken place across e-mail, instant messages and telephone calls. "

While sifting through available data, the software can look for "call me" moments in e-mail, when an individual is shifting media, possibly to cover up some sensitive information. It can also detect shifts in tone in someone's communications that may raise a red flag. New tools are being developed that help researchers understand how language is used and how social networks operate.

However advanced its methodology, though, research does have its limitations, as the advertising legend William Bernbach pointed out: "There is no such thing as a good or bad ad in isolation. What is good at one moment is bad at another. Research can trap you into the past."

And that's the catch. The data gathered by all this research is history. For leaders making bets for the future, algorithms are not likely to replace judgement any time soon. Once again, Mr. Bernbach put it simply:

"We don't ask research to do what it was never meant to do, and that is to get an idea."