Five Forms of Filtering « Innovation Leadership Network - 11 views
timkastelle.org/...five-forms-of-filtering
filtering infotention knowledge management information fluency web 2.0
shared by Dennis OConnor on 01 Dec 11
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We create economic value out of information when we figure out an effective strategy that includes aggregating, filtering and connecting.
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So, the real question is, how do we design filters that let us find our way through this particular abundance of information? And, you know, my answer to that question has been: the only group that can catalog everything is everybody. One of the reasons you see this enormous move towards social filters, as with Digg, as with del.icio.us, as with Google Reader, in a way, is simply that the scale of the problem has exceeded what professional catalogers can do. But, you know, you never hear twenty-year-olds talking about information overload because they understand the filters they’re given. You only hear, you know, forty- and fifty-year-olds taking about it, sixty-year-olds talking about because we grew up in the world of card catalogs and TV Guide. And now, all the filters we’re used to are broken and we’d like to blame it on the environment instead of admitting that we’re just, you know, we just don’t understand what’s going on.
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The five forms of filtering break into two categories: judgement-based, or mechanical.
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Judgement-based filtering is what people do.
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As we gain skills and knowledge, the amount of information we can process increases. If we invest enough time in learning something, we can reach filter like an expert.
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However, even experts can’t deal with all of the information available on the subjects that interest them – that’s why they end up specialising.
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There can also be expert networks – in some sense that is what the original search engines were, and what mahalo.com is trying now. The problem that the original search engines encountered is that the amount of information available on the web expanded so quickly that it outstripped the ability of the network to keep up with it. This led to the development of google’s search algorithm – an example of one of the versions of mechanical filtering: algorithmic.
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heingold also provides a pretty good description of the other form of mechanical filtering, heuristic, in his piece on crap detection. Heuristic filtering is based on a set of rules or routines that people can follow to help them sort through the information available to them.
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Filtering by itself is important, but it only creates value when you combine it with aggregating and connecting. As Rheingold puts it:
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The important part, as I stressed at the beginning, is in your head. It really doesn’t do any good to multiply the amount of information flowing in, and even filtering that information so that only the best gets to you, if you don’t have a mental cognitive and social strategy for how you’re going to deploy your attention. (emphasis added)
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I've been seeking a way to explain why I introduce Diigo along with Information fluency skills in the E-Learning for Educators Course. This article quickly draws the big picture. Folks seeking to become online teachers are pursuing a specialized teaching skill that requires an information filtering strategy as well as what Rheingold calls "a mental cognitive and social strategy for how you're going to deploy your attention."
