Finding the Blank Spots in Big Data

How often do we think of data as missing? Data is everywhere—it’s used to decide what products to stock in stores, to determine which diseases we’re most at risk for, to train AI models to think more like humans. It’s collected by our governments and used to make civic decisions. It’s mined by major tech companies and sold to advertisers. As our data becomes an increasingly valuable commodity, for your data to be “missing”—to not be “seen” or counted—can almost seem like a good thing. 

On the other hand, when data is used at such an enormous scale, gaps take on an outsized importance. In her new book, Invisible Women: Exposing Data Bias in a World Designed for Men, Caroline Criado Perez argues that the lack of data collected on women not only naturalizes sex and gender discrimination, it also quite literally endangers women’s health (e.g. when the crash test dummy is only designed for average male proportions). Missing data can also lead to erasure, reinforce bias, and, ultimately, create a distorted view of humanity. As Tea Uglow, director of Google’s Creative Lab, has put it, “If the data does not exist, you do not exist.”

Today, there’s an increasing number of artists, programmers, designers, and technologists that are addressing this problem at a grassroots level. These creatives understand that those most at risk for being excluded from data are also the most marginalized, and they’ve decided to use data as a way to protest and challenge who has access to power and who doesn’t. They also bring idealistic, communal, and at times poetic approaches to the biggest hurdle when dealing with “blank spots”—having to address something that isn’t there.

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