Defrag Closing: Relevance and Information Overload


Paul Kedrosky, moderator of
the closing panel at Defrag.
Paul Kedrosky, moderator of the closing panel at Defrag.
(click to enlarge)

"Everytime I try to get more personalized information, I end up with more celebrity obituaries in my newsfeed. Why is that?" asks Paul Kedrosky, moderator of the closing panel at Defrag.

At issue: is information overload real, or is it something that people at Defrag (and other's like us) invent so we can have a problem to solve? Is this a problem a relatively few people care about because only a few people are really all that connected or involved?

People are fundamentally lazy. Most people aren't going to tag things, rate them, review them, or anything else. Are the rest of us just information sherpas for the rest of the population? Maybe, but that's not all bad. Tagging is just the editorial process of our day. Editorial efforts are always a few creating meaning for the many.

Pulling structure out of the implicit will make this task easier. There is an interplay between implicit and explicit. Implicit provides a set up and then explicit drives the point home.

Closing panel at Defrag
Closing panel at Defrag
(click to enlarge)

Paul asks the panel: "What are people using now to solve this problem that didn't exist ten years ago?"

  • The emergence of faceting - the navigation of a site like Home Depot. Going through information on lots of products by price, by brand, etc.
  • Search tools and feed filtering
  • Digg - what everyone else thinks is interesting
  • StumbleUpon - a big time-waster or an alternative to search?
  • Twitter

What's interesting about several of these tools is that they lead to discovery, something that's been missing from the Web since the rise of the search engine in 1996. People used to "browse" the Web. Digg, StumbleUpon, and even Twitter lead to serendipitous finds.

Information overload and the stress associated with it is a choice. We choose to focus or not. We choose to pay attention to things.

Still, there's an issue of too much data on things we need to pay attention to. Because the data is available, we feel like we shouldn't miss it and indeed, missing relevant data can be costly. This is no where true than in the capital markets. People make money from having the right information, on time. There's money to be made here.