Last night I delivered the Gillard Lecture at the St. John’s University Graduate Division of Library and Information Science. My presention was titled “Has the Librarian-ship Sailed?  Redefining the Profession in a Post Google World.”  I want to thank the program director Professor James Vorbach  for the wonderful reception. It was great to see a contingent of my LLAGNY friends who made the trek out to the Queens campus in the driving rain.  And then there was the inevitable technology glitch. An encrypted flash drive that would not run part of my presentation.

So Here it Is….The Missing “Wow Moment” of My Presentation

This Ted Institute video of Dario Gil on cognitive computing provides a jaw dropping scenario in which  a Watson enabled computer is responding to the types of complex business research questions which are fairly routine in a “big law” research environment.  In this video two business analysts are asking Watson to pinpoint companies matching specific criteria, industry, revenue, size. Watson can automatically populate a table with data after digesting a policy document.   But there is one major difference… between Watson and research specialist.

What About the Contextualizing Questions?
I intended to use the video to launch a discussion about how Watson’s performance compared to a live researcher? What would the future role be for Watson? A replacement for the research team or an adjunct “member” of the research team?

Complex research is a dialog. Researchers not only answer questions.. they ask them! This “socratic dialog” helps focus the requester on issues which provide important context for narrowing and focusing the research.

Without Big Data Skillsets – Big Data Could Generate Big Noise

Large data sets will play an increasingly important role in making new strategic insights available to law firms. As illustrated in the video augmented intelligence will speed the analysis once the data is identified. But someone has to select and vet the data. Information professionals possess the skillset required for making sure that “big data” is also “good data.”

Here is a short list of those skills:

• The ability to locate the best and most appropriate data at the lowest cost
• The ability to assess the quality of external data sources. All
  information is not of equal quality. The temptation to harvest free open
  source data could put a firm at risk especially if the data were to use
  used in advising clients.
• The ability to assess the provenance of the data.  Is the data from a
  primary source? Or has it been handled and altered? By whom and how?
• Expert knowledge of or ability to determine the reputation of the data source.  Is it known to be a reliable source? 
• The ability to interview the requester and help them to define the scope and limits of their need.
• The ability to query the data and uncover patterns which suggest
  the need to ask more questions or pursue additional lines of inquiry.