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I should be thinking about hierarchically nanostructured materials, but instead I’m thinking about ways to make our world a little better.  The following post might be a little unstructured, but I wanted to put it out there for your thoughts.

Erik and I started the umbrella movement a few years back as an experiment in social good.  The concept was straightforward: we bought a ton of umbrellas, labeled them with a sticker that read “you’ve got the movement, pass it on”, and handed out these umbrellas in the pouring Boston rain.  Our working thesis was that everyone appreciates a little good will, especially when a sudden unexpected turn for the worse arrives, and that this good will could be passed on with a multiplicative effect.  Sort of like “Pay it forward” the movie, but not Haley Joel Osment.  In addition to encouraging good will we were curious to see the network effect and how far these umbrellas would be distributed.

It didn’t work very well.  The umbrellas tended to fall apart and extra ones were cumbersome to carry around.   Maybe our optimism was misplaced and people really thought “Hey sweet free umbrella.  Now I don’t have to spend $10 for a $1.95 umbrella that the guy on the corner is selling them for.”  I don’t think this is true.  I believe people are generally altruistic and desire to aid their fellows.

So what was the problem?  There were too many obstacles in the way; high friction slowing down the network of good will.  That and maybe the umbrella recipients weren’t primed to be altruistic.  Maybe they had to be home for dinner.

Thinking about twitter recently, I’m increasingly buying into the fact that as a platform, it has a serious potential to change the way we communicate.  It’s social, viral, and it addresses our decreasing attention spans.  I think buried within the network is an enormous opportunity to create social good and I’m trying to think of the best way to exploit this.

A simple concept is the idea of “doing a good twit daily” (borrowed from the Scout’s phrase “Do a good turn daily”).  Needy groups or people could send twits to a twit-bot requesting volunteer help, some extra food, etc. and indicating location and time.   Recipients of the twit could then reply indicating how they can help.  It’s simple, it primes people for altruism, and it leverages a huge network.  You could build a bunch of add-ons: AI to allow for twits which are local or within a certain type of volunteering or a database to help groups manage their volunteers.

I’ve been messing around with twitter for the past couple of months.  My network is relatively small, keeping small updates on my brother and twit-stalking a few of the VC guys that are big believers in this stuff.  So for me, I use it relatively infrequently.  For others though it’s huge, completely viral, and informative.

Fred Wilson, a VC at Union Square Ventures, has been a big proponent of twit-bots.   For example you can create a twit-bot on wine recommendation (@winetweets) .   This allows everyone interested in wine recommendations to post to the twit-bot and the bot published the recommendation to everyone who follows the twit-bot.  There is some real power of the masses at work here: if you get enough people, surely the wisdom of crowds should allow you to find the cream of the crop recommendations based on number of recommendations alone.  However there is oversaturation of information here as well: what happens when you get 1000, 10000, 1 million recommendations a month from the twitbot?  There is just no way of handling this information.

This leads me to the idea of ‘data-mining’ information from twitter (I’m sure someone is working on this already) . Because of the format, twits are limited to 140 characters, necessitating brevity.  In a comparison with yelp.com, there is no opportunity to supply context for the recommendation that a full review on yelp can provide.  Thus I think it will take some sweet statistical analysis along with some meta-data (some metric for how ‘good’ the recommender is) to really extract some value from this.