Mike Pepi and Marvin Jordan asked me to contribute to their issue of DIS Magazine on The Data Issue: Too Big To Scale, which is great so far and I'm looking forward to reading more over the next month. I had been thinking about metaphors for data for a long time, and always wanted to write something expanding upon a section of my thesis on the Quantified Self, arguing for more embodied metaphors for understanding our relationship to data. Here's an excerpt:
Though metaphors reveal truths by association, metaphors can just as easily obscure and misrepresent. Metaphors prime us to take for granted the ways we think about things. Most of the metaphors we use to talk about data in popular culture make sense to technocratic corporations and their leaders, those building and disseminating information technologies, but they are fundamentally dehumanizing. It is no wonder individuals continue to believe that they have “nothing to hide” in the face of big data, because we do not have the cognitive context to grasp how behemoth corporations use data. The dominant industrial metaphors for data do not privilege the position of the individual. Instead, they take power away from the person to which the data refers and give it to those who have the tools to analyze and interpret data. Data then becomes obscured, specialized, and distanced.
We need a new framing of a personal, embodied relationship to data. Embodied metaphors have the potential to bring big data back down to a human scale and ground data in lived experience, which in turn, will help to advance the public’s investment, interpretation, and understanding of our relationship to our data.