Monday, December 17, 2007

Reducing day-to-day information noise

Here's a concept I'm trying to apply to my life: reducing signal to noise ratio involved on day-to-day activities (those little things that when summed up suck a lot of time/energy up), like reading newspapers, RSS feed agregattors, actually paying attention to some stuff people around you babble about etc. In summary, where to invest your precious "micro" attention to.

A good argument on the danger lurking under day-to-day noise comes from a passage I found at Fooled by Randomness by Nassim Nicholas Taleb: He makes up the story of an amateur stock investor (a dentist) who checks up his profits online every single minute, thus he's exposed to all the noise on markets, suffering many unnecessary setbacks. Given the fictional portfolio for this dentist, the probability of success at a scale of 1 minute is around 50.17%. At a quarter it goes up to 77% and at 1 year his odds of success are at 93%.

To understand what I mean by noise, take a look at this graph:
and think of the dotted line as the market and the other colored lines as a filtered (de-noised) long term perception of it.

So take news feeds and collectively selected (supposedly high-quality) content from reddit.com, digg.com, news.ycombinator.com and others for example. Look at what you see day after day: What if you simply ignored them and stopped reading. Following them day-by-day (which is something I've been doing for the past several months if not years) is analogue with the dentist investor checking his profits every minute and suffering all those negative setbacks. What if you could reduce it and only catch up on tech news every two weeks? Every month? How much would you really miss?

After some time, those news items that would seem relevant that day or week may actually show up to be irrelevant and just noise and have no real implications when you look at all the developments for this month or semester, so you actually saved some time by not even becoming aware of them in the first place.

There is also the other side of this argument: information noise also has it's advantages, for instance, the sea of unexpected opportunities hidden behind your thousands of unread items on your RSS reader.

So I leave some open questions. What would be the best way for catching up and increasing the signal/noise ratio? That is, what is the best way for sampling from last month tech and software developments history?

4 comments:

Daniel Lemire said...

I do not subscribe to these feeds. Any feed that has more than 1 post a day gets deleted from my subscription list.

This means that I do not follow A-bloggers except for Stephen Downes who organizes his post better than some.

Anonymous said...

How would you like it if there was some service that pointed out the best posts/articles from a particular
feed? Would your problem be solved then?
I asked as I am working on such a service currently and am not sure if many people do indeed face this problem. Kindly mail me your reply at
kalpeshk[at]gmail.com
~ Kalpesh

Ricardo N. Cabral said...

Something like http://www.particls.com/filterthenoise/ ?

I'm pretty sure many people have this very same problem. Information overload is everywhere.

Such a service would definitely help but I wonder how well will it filter noise and present only what's relevant. Just filtering out what's not popular won't work since noise may be really popular and yet irrelevant two weeks after the hype is gone.

Ricardo N. Cabral said...

and it turns out that Seth Godin is starting (!!!) to suffer from the same problem: http://sethgodin.typepad.com/seths_blog/2008/04/signal-to-noise.html