In keeping with Lisa’s theme, I want to talk a bit about the topic of attention management.

A week ago, I declared information bankruptcy.

Information bankruptcy is a more generalized form of email bankruptcy and RSS bankruptcy. I have too much content to keep up with. I have 96 people I follow on twitter (low by most affluent standards). I have 73 friends on facebook (again, low). I follow the life streams of a dozen people. I’m on livejournal, flickr, yelp, upcoming, eventful, tumblr, delicious, wordie, pownce, linked in, myspace, last.fm…the list goes on.  By declaring information bankruptcy, I stayed away from all of these things for a week with the intention of rethinking how I consume data when I return.

There are usually one or two mechanisms offered to control what comes to our attention: source and keyword. We can control what RSS sources come to our feed readers, and we can control what users we follow on twitter. We can track topics by keywords, or block in the same fashion. The problem with this approach in a web 2.0 world is that every user produces so much content. White listing all of a user’s content or all content of a certain keyword is too much to consume.

Lately, several aggregators have come on the scene attempting to help this. FriendFeed, AlertThingy, and Twhirl come to mind.

Aggregation is not the answer.

Aggregation solves the wrong problem. It operates under the assumption that we can handle attention management just fine if we get all our information on a single page. Really, the problem with these apps is that all information is considered equal. In FriendFeed, a blog post and a tweet have equal standing. Visually, equal space is given to each. No one presumes these two things have equal value. In fact, many would argue that they can’t even be compared; it’s apples and oranges. Yet, since we consume all kinds of information, how do we arrange this content for maximizing consumption?

Really, we’re talking about something Lisa and I choose to call attention management. Arranging data to be consumed when it does us the most good, and limiting our interaction with data that isn’t useful. Thankfully, ranking content is something computers are very good at, as long as you give them the right metrics. Give them the right metrics, and they can identify what I choose to call the two axises of attention management: immediacy/staleness and stickiness/transitiveness.

Using these scales, I can define thresholds for what kinds of content I want to see and how quickly I want to see them. These are also style guidelines. Content needs to be presented differently based on these characteristics.

It all comes back to reducing noise from the signal. There are many approaches to this problem, and Technarium will be competing in this space soon. I want to think Lisa and I have the answer, but the answer will come from anyone who executes properly on this question: how do you prevent information bankruptcy?