How To Break Anything

Innovation + experience-minded design strategy. The pieces of a working model for understanding culture + change in an increasingly complex world.

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      22 Jul 2011

      Data Cake

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      Media_httpepicgraphic_azxvs
      via epicgraphic.com

      The Data->Information->Knowledge->Wisdom model is a common way to illustrate a flavor of levels of abstraction.

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      27 Jun 2011

      Frames and levels of abstraction, from "This Graffiti Is Now Art"

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      Media_httpwwwtreehugg_ymuej
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      There are at least four frames represented here, so at least four levels of abstraction. Beginning with Tox's work, maybe these frames are:

      Tox's work | The reaction to Tox's work and his jailing | Banksy's framing of Tox's work | Passersby photographing and sharing Banksy's work | Photographer capturing the passersby | Treehugger's analysis of the whole bit as a comparison of graffiti and art

      I'm laterally reminded of the expression "nothing lies like a camera," a neutral understanding that the act of framing anything by necessity excludes everything else.

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    • Contributors

      Kyle Cameron Studstill
    • Obox Design
  • How To Break Anything

    Hello friends and collaborators. I deal in innovation, working to build fantastic experiences enabled by the digital world. As part of this I track cultural change, primarily through observations guided by models and filters calibrated over years to sort out the cream.

    These pieces of thoughts here reflect concepts that are elements of those models: ecosystem thinking, long-term value, information filters, and pattern recognition.

    ("How to break anything" is an abstract notion that reflects my background in observation and analysis. Rules are meant to be broken, but only through understanding the rules - observing them with an empathetic eye - can they be broken constructively.

    So how to break anything? Observe everything.

    [You can't observe everything so how do you know what to observe? That's another project that I call Filter Theory - see the About link above.])

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