“For the most part we do not first see, and then define, we define first and then see. In the great blooming, buzzing confusion of the outer world we pick out what our culture has already defined for us, and we tend to perceive that which we have picked out in the form stereotyped for us by our culture.”--Walter Lippmann (American Journalist--Sept. 23, 1889—Dec. 14, 1974)
The basis for teaching data fluency stems from our very own heuristics. Mine too. None of us are above debate regarding our intentions or assumptions.
Allow me to share a specifically non-instagramy moment. Due to a confluence of events--apparently rodent friendly weather, living on a park with a creek, and a lively chicken coop--we became infested. Mainly the yard and coop but who knows? If truth is indeed "poisoned at its source" according to Walter Lippmann, we attacked with gusto.
After all, we defined the problem therefore the solution appeared to be quite straightforward.
Well let's think this through carefully. If the goal was a systemic ridding of the rodent population from the yard--we were advised by professionals to follow the protocol.
But often, in pursuit of an outcome we forget about the stench. In this case I am referring to fetid carcasses decaying just about everywhere you can imagine. Out of sight but definitely not out of olfactory range.
The unpleasant imagery may cloud your ability to see the data adjacent similarities but stay with me here. A good data question often requires the holding of tensions. The pursuit of a complete data set to indeed be empowered to curate empathy or insights. Culturally defined norms often make it unavoidably tempting to believe low hanging fruit and reinforce pre-existing assumptions.
We might ignore relevant information out of fear, repulsion, or conscious bias.
But eventually the stench of bad data will win. And we will need to clean up the mess and start over.
Where to connect--click on images for links to more info!