Process

Initially, I had a direction of finding ways to subvert some of these forms of machine perception and algorithmic data collection and began with looking at existing projects and tools in this space. My first foray turned up projects like Unique Machine, Cover Your Tracks, and Am I Unique, which reveal the data collection that happens to uniquely identify someone online. Data Selfie (RIP) is a project that is most similar to Data Decoder in that it provides users a window into how their online presence is being perceived, but it relies on regenerating that data through tracking someone’s activity rather than using data provided by the platforms. With the aim to subvert, I spent time googling the ways in which someone could request a copy of their data from some of the big companies. Some of my requests were more successful than others, with a disclaimer from most that it could take up to 30 days to receive the data after my request. Browsing some of the data I received in the form of JSON, HTML, and CSV files, spurred the idea of a tool that would make it easier to interpret this. Funnily enough, the initial thought was, “My mom wouldn’t know how to open these in VS Code.” From there, it was a matter of conceiving of a basic mockup of what a Data Decoder web app might look like.