Trust, But Verify

How we think about things has been persistently changed by technology since we started using rocks instead of teeth to grind dinner.

However, the more technology synthesizes for us, the more it has the tendency to de-value or re-frame our knowledge.

I’ve had the great good fortune to shepherd the formal knowledge management activities of several large organizations. What I see happening today leaves me pleasantly breathless and a bit worried. I’m concerned we are becoming instantly informed and less learned. If one’s province is the triangular kingdom of futon, kitchen and loo, this is likely inconsequential in survival terms…statistically speaking.  If, instead, one adventures afloat, I think, perhaps, it can get one killed.

Context encompasses. There is a context for data, for information and for knowledge, and like Matryoshka dolls, each higher context embraces all lower ones. Data and information accepted and absorbed without the meta-context of  knowledge are  frequently more dangerous than none at all. With less and less emphasis on how to manage a life-time of self learning being provided by schools, instantly delivered, un-challenged data and information become even more dangerous.

  • Data are observed/derived and measurable and can exist independent of the human mind. It’s 20 deg C, the temperature is dropping at x deg/min and the wind is shifting x deg /min and accelerating y kph/min [ignoring 20, x, y, deg, min, and kph are human contextual references]
  • Information is derived/synthesized and measurable and can exist independent of the human mind. A micro, meso or macro cold front is arriving. It’s summer in the Bahamas.
  • Knowledge is derived/synthesized and testable and cannot exist independent of the human mind. (The instant knowledge is recorded outside the human mind, it reverts to information.). Based on the above, I should have already shortened sail.

What is happening today is:

  • We are being presented data from a context we may not understand or share. [I recently wondered why the weather reported for our area was always at such odds with what we were experiencing at our location. I located the reporting station on Google Maps using satellite imagery. I drove to the location and seeing the siting of the weather instruments, wiped that site from my list. In another instance some years ago, I wondered why the local lighthouse always presented wind information at odds with what I was experience while within sight of it. Building the wind-roses for 12 months of data (now available for download as graphics files) I discovered the winds at the light house were dominated by a highly localized set of geographic features that made the reported directions and velocities useless.]
  • We are losing touch with underlying data in favor of information synthesized in ways we aren’t privy to. [There are more than six models used for assessing hurricane behavior, there are more than three for blizzards . In both these cases, the models are regionally constrained but are often tossed in the forecasting mix for inappropriate regions. In a year’s tracking I have found the three weather services I use most frequently, the seven-day convergence is 20-30%. At four days they are about 50%, and in 24 hours they still only run about 70%. (That’s convergence not accuracy.) Recently, I discovered one site purporting to have a new set of analytical tools was simply layering GRIB data into a format that obscured its source (out of business now, but for data rights violations, not bad information synthesis).]
  • We are forgoing knowledge in favor of quasi-instant information from digital devices optimized for socializing, advertising and entertaining.

What we, as an evolving, increasingly technologically dependent community need to be doing might include:

  • Demanding to know the context for the data we use.
  • Demanding to know what is being synthesized into information and how.
  • Sitting down to a meal of learning—developing our meta-context—to critically assess the data and information we receive versus snacking on information served up for purposes increasingly divergent from the central one.

What I have seen in three years of blogging (for professional purposes) is a technology trust divide. We need to remember technology can seldom make bad data into good information. It can very frequently make good data into bad information.

There was a phrase in the 1980’s, that in my skeptical opinion, should be engraved on every data, information, knowledge centric device.

2 responses to “Trust, But Verify

  1. Very good article Chris, I must add a label saying “trust but verify” to the front of my GPS, calculater etc

    In reality that is kind of how I use technology, Ie My calculater gets a “does this answer make sense?” question after evey use. Its scary how often I have pushed a wrong button…

    Thanks for articulating this, and adding a great quote to my vocabulary.

    • Ben, I should point out the phrase came from the Reagan White House with regards to Nuclear Disarmament activities. The Russian version (which predates it) is doveryai, no proveryai.(Доверяй, но проверяй). Chris

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