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Link Collection — April 7, 2013

April 7, 2013 By brenda michelson

  • What’s Next in the Techonomy? — Hagel & Seely Brown

    “In the last few decades, we have witnessed a steady doubling in the price performance of digital technologies. However, we are reaching a tipping point of this exponential growth, and it is unclear how the cumulative effects of technology will reshape our economy, political systems, and collective future. One thing is clear: in the hands of existing institutions-firms, schools, non-profits, civic institutions and governments-this awesome technology will achieve only a fraction of its potential.

    Unfortunately, we haven’t seen the same exponential rate of change in institutions as we have in technology (Unlike computer chips, government and business structures don’t predictably get faster and less expensive). Managerial fiefdoms, rigid hierarchies and tightly scripted procedures remain from the industrial revolution era like vestigial structures; they were important at some point, but it’s unclear what purpose they serve now…”

    tags: innovation technology institutions

  • How To Think Like An Engineer ⚙ Co.Labs ⚙ code + community

    Good insights in here. If you already think this way, consider passing it along to folks who “don’t get your thought process”…

     “Excelling in business today means knowing how to think through technological abstraction and ambiguity. Here, we listen in as engineers discuss this very skill–and decode their secrets for how to hone it.”

    tags: thinking engineer

  • Big Data’s Promise and Limitations : The New Yorker

    “Big Data can be especially helpful in systems that are consistent over time, with straightforward and well-characterized properties, little unpredictable variation, and relatively little underlying complexity.

    But not every problem fits those criteria; unpredictability, complexity, and abrupt shifts over time can lead even the largest data astray. Big Data is a powerful tool for inferring correlations, not a magic wand for inferring causality.”

    tags: bigdata

Posted from Diigo. The rest of my favorite links are here.

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Brenda Michelson

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