Data is great for perpetuating stereotypes. Here’s why. We tend to write algorithms to produce results that match our biases. When we didn’t have data right at our fingertips, it took much longer for news to spread. Someone had to pick up a book or read a magazine, then go gossip. Information had a much longer life-cycle.
Digital data affords us the luxury of drive through news, with the same heartburn of fast food burgers. The challenge with having lightning speed access to information, is that our craving for sensationalism is insatiable. Those in the business of data work fastidiously to overcome our desensitization to current events. This creates a conundrum. Do we bend our data points to tell a spicier story? Or do we fall behind as a major news outlet because we’re unwilling to shape our data to the far right or far left? Logic gets painted into the corner. Instant fuel is added to the fire with tweets and posts and live newscasts, 24/7. In the age of digital data, stereotypes easily continue to burn our bridges to peace and global prosperity.
Of course, there’s always the question, which comes first, the data or the egg. Does data reinforce current reality or does data slowly shape an alter-reality that’s based on pre-programmed agendas?
As a reminder, data could be an individual fact or a body of information. In the olden days, before Amazon’s bestseller list, when an author came up with a clever phrase or label for an entire generation, it took a while for that idea to gain popularity and become mainstream, through the slow percolation of facts and figures that weren’t yet digitally spread.
Today, digital data can reinforce stereotypes according to the cycle of data digestion, that now includes a constant feedback loop with the invent of search engines. Not only can trendy ideas organically spread like wildfire, but those who wish to profit off of categorizing an entire generation as “Millennials” with a very specific set of characteristics, begin to write sponsored emotive pieces that resonate with those who relish being a part of a larger community identity. Conversely, they design campaigns to make those outside the classification of “Millennial” feel increasingly proud that they escaped the negative connotation of being born during “those days.”
I’m barely a Millennial and am guilty of googling (searching online) to discover just exactly what that means. Not only does this have the potential to sway me toward believing I am who they say I am, but it also has the potential to make others think I am who they say I am, simply based on an article about Millennials that was served up in a LinkedIn newsfeed, for instance.
So, what would you name your generation and how would you characterize your relationship to data as we know it? Do you think twice about digital stereotyping? Do you stop and consider whether you’re playing into the stereotype or whether the stereotype is playing you? I’ve often had those moments where I think something in my video feed is a God send, when in reality, it’s a feedback loop, perpetuating my own little stereotype about how I think life should be, where I want life to take me, and how I should approach the challenges at hand.
I challenge you to stop doing the data drive-through. Feed your algorithm something different for a few days and observe how that changes the data that gets thrown back at you. Mess with the search engine’s mind. Show Google who’s boss. Intentionally shape your online persona outside of your predicted next clicks. I’m convinced this will demonstrate the power of data we often ignore and challenge the stereotypes we blindly adopt.
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