In a previous post about data visualization, I discussed how our expectations can distort the data we visualize a lot more than we may realize, causing us to mistake dashboards for magic mirrors reflecting back our own image of what we want our data to show us.

In The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think, Eli Pariser describes how the distorting effect of personalized filters, which create what he calls the filter bubble, can make it difficult for us to see what’s actually going on, like “a funhouse mirror reflecting a funhouse mirror reflecting reality.”

“Like a lens, the filter bubble invisibly transforms the world we experience by controlling what we see and don’t see,” Pariser explained.  “It interferes with the interplay between our mental processes and our external environment. In some ways, it can act like a magnifying glass, helpfully expanding our view of a niche area of knowledge. But at the same time, personalized filters limit what we are exposed to and therefore affect the way we think and learn. They can upset the delicate cognitive balance that helps us make good decisions and come up with new ideas. If we want to know what the world really looks like, we have to understand how filters shape and skew our view of it.”

Clay Shirky, a scholar on the effects of the internet on society, said “it’s not information overload, it’s filter failure.” But the seeming infinity of big data seems destined to force all filters to fail.

Although we build a buttress against big data with bubbles, personalized filters allowing us to pretend that what we see is all there is - that our perception of reality is not a reflection in a funhouse mirror but a visualization in a data warehouse dashboard that helps us make good business decisions - sometimes bursting your filter bubble is the only way to know what the world really looks like.