The term data set implies something discrete, complete, and portable, but it is none of those things.
we live in the gaps, to widen the cracks we must: A.) be intentional in our use of technologies B.) aim our intentioanlity towards active deconstruction and reconstruction of spatial data in our lives. We must explore and better know our data to make them ours, respurposing to build solidairty.
the metadata collected about online behavior feeds profile-mapping algorithms that are designed to guess things about you that you haven’t revealed publicly. Because this data is more useful in aggregate than in isolation, “what the machines think of you” hinges on the lingering cloud of digital pollution that you’ve accumulated over time more than the exhaust you produce in real time at any given moment.
In The Age of Surveillance Capitalism, Shoshana Zuboff writes that accurate predictions of future actions generate revenue, and that “the surest way to predict behavior is to intervene at its source and shape it … machine processes are configured to intervene in the state of play in the real world. These interventions are designed to enhance certainty by doing things: they nudge, tune, herd, manipulate, and modify behavior in specific directions by executing actions as subtle as inserting a specific phrase into your Facebook newsfeed, timing the appearance of a BUY button on your phone.”
“Sweat literalizes porosity: It seeps out at times and in contexts that we may wish it did not.… Sweat leaves a trace of how we pass through the world and how we are touched by it in return. It is the classic means by which the body signals its capacity to ‘affect and be affected.’” Data sweat is a residue of feelings that we might not be able to name but that still circulate within us; it can reflect our intimate inner lives as much as a carefully written confessional.
data sweat emphasizes the ways in which it leaks messily out of our pores as opposed to emerging directly from our machines as a kind of industrial waste product.