Ah, design is becoming so democratic! Free market! Even your grandma can do it!

Google’s solution to a “certain problem” is to have the user answer some math questions within a time limit at certain hours of the night, on Friday and Saturday.

But me, I get drunk and send inappropriate emails at all hours of the day.

Google proposes that “surely if you can do basic math problems then you have a solid command of what is and is not socially appropriate when it comes to late night email.” However, some question the initiative’s effectiveness:

Not really. Drinking seems to lower inhibitions more than it lowers other abilities such as math skills, and at least for me it never lowers my math skills enough that I would fail this.

Yeah, I had a friend in college who, when drunk, would only ever talk about two things: Thomas Aquinas’s epistemology… and his fiancee’s hymen.

This movie is a farce. Somehow it has managed 14% on Rotten Tomatoes. And somehow it has 2.3/10 stars on IMDB, where one user rightly called the movie the “World’s Most Expensive After-School Special”. But it is a farce. Right? It has to be. Otherwise it is the world’s longest commercial; another disgusting, disturbing attempt by corporate America to leverage patriotism into consumerism.

Why do I eerily foresee this film making its ways into classrooms, shown right beside those lame school videos during social studies?

Fun fact: “Opening in 750 theaters, Proud American managed to earn only $96,076, or $128 per venue — the worst for any wide release in the United States since at least 1982.”

Yes, I think any Star Wars jokes instantly qualify for the “nerd alert!” tag.

Basically, Shirky proposes that consequences we normally attribute to an explosion of available information thanks to the internet is actually attributable to a failure of the filters in place to deal with an already abundant amount of information. Since the invention of the printing press, he says, we have lived amidst “information overload”, such that we can no longer look at the phenomenon as a problem, but as a fact. An appropriate response, then, is to build better filters.

Notice that the solution is to build, not to fix. An overload of information has been our oxygen for centuries, but the type and amount of data we deal with now is vastly different than whatever has come before. Shirky ends by separating the types of filters needed into two categories: programming and social. The latter category is pretty nebulous, but “programming” is much more concrete, and already in use today. Digg, Netflix, Google, and every other website run on extrapolating from its users’ actions is utilizing so-called collaborative filters, and these are a pivotal part of the internet’s future.

Collaborative filtering works by ranking content according to prior users’ actions (e.g., Google looks at links, the paragraphs surrounding search terms, other mysterious data), then analyzing your own actions to serve up relevant content. With sites like Digg and Reddit, this involves users upvoting or downvoting submitted sites, and then you seeing the best sites in descending order (with maybe some specializing depending on if you’re at a subpage). With sites like Netflix and Amazon, your own consumption is compared to other consumers in order to serve up recommendations.

As we approach the singularity and the web becomes more ubiquitous, collaborative filtering will become increasingly sophisticated (and accurate). As Jay Adelson mentions, Google’s search rankings have become more powerful simply because of the diversity of its users has increased. Collaborative filtering thrives on multifarious data, and this will come quickly with a larger number of netizens, and more slowly through the growing number of connections between web services. Adelson points to the economic advantages of shared data (read: better advertising targeting), but this is of course of huge value to users and developers as well.

Low-level web curation, from Metafilter to Undress Me Robot, will always have its place online, but the future is definitely in these automated processes which leverage what each user is already doing to provide a highly personalized and more effective experience. However, obviously, collaborative filtering is simply an update of the sort of filter that has been around since the 1500s, moving from the editorial eye of a single person to the gaze of millions. The next big jump in information overload might break down even these strong filters, taking a paradigm shift to get back on top. And who knows where that will take us?

I have no idea if this is real, but Gawker makes some convincing arguments. This is pretty amazing.