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Extracto de apertura:
“”It’s not information overload. It’s filter failure.” That was the main theme of a thoughtful and influential talk that Clay Shirky gave at a technology conference back in 2008. It’s an idea that’s easy to like both because it feels intuitively correct and because it’s reassuring: better filters will help reduce information overload, and better filters are things we can actually build. Information overload isn’t an inevitable side effect of information abundance. It’s a problem that has a solution. So let’s roll up our sleeves and start coding.
There was one thing that bugged me, though, about Shirky’s idea, and it was this paradox: The quality and speed of our information filters have been improving steadily for a few centuries, and have been improving extraordinarily quickly for the last two decades, and yet our sense of being overloaded with information is stronger than ever. If, as Shirky argues, improved filters will reduce overload, then why haven’t they done so up until now? Why don’t we feel that information overload is subsiding as a problem rather than getting worse? The reason, I’ve come to believe, is that Shirky’s formulation gets it precisely backwards. Better filters don’t mitigate information overload; they intensify it. It would be more accurate to say: “It’s not information overload. It’s filter success.”
But let me back up a little, because it’s actually more complicated than that. One of the traps we fall into when we talk about information overload is that we’re usually talking about two very different things as if they were one thing. Information overload actually takes two forms, which I’ll call situational overload and ambient overload, and they need to be treated separately.”