In recent years, methods of collecting data have become more accurate than ever, and it is increasingly sought after as a means of understanding our current age contextually. With such vast amounts of personal information being stored, the issue of privacy and validity of interpretation becomes increasingly prevalent.
As Paul Edwards outlines in the opening to his book, Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming, new information allows us to consider how past conclusions may be rendered inaccurate by present understandings. It also gives us insight into how our past knowledge inevitably shapes our present assumptions. He refers to the tension between information and context as ‘data friction’.
Data friction carries across into many more fields than just that of climate change. With the prevalence of metadata collection, this friction becomes increasingly important not just to the online lives of individuals, but also to online businesses. To put this into a more specific context, consider Google. Google functions as a meeting place for many parts of a person’s online identity, keeping a record of searches, videos watched, and contacts (among other things). Google’s targeted advertising is a particularly clear example of what data friction looks like in practice: a collection of metadata used to assume certain knowledge of the individual.
The tension between statistics and assumed understanding is clearly at stake with these advances in data collection, and is certainly an issue that is being addressed globally – as Edwards makes clear. The internet is a kind of theoretical nation that connects the globe and so, not surprisingly, the politics of negotiating this landscape are complex. Edwards discusses the idea of ‘infrastructural globalism’, which, in the context of the online sphere, means much the same as it does to climate change: “gathering global data helped to create global institutions and ways of thinking globally” (xviii).
When viewed alongside data friction, we can begin to see how so many conflicting opinions have been raised regarding data retention. On one hand, such insights allow us to think globally, and to better understand human interactions through emerging patterns. On the other, there is the question of whether, with a lack of contextual information, metadata is providing accurate information. I believe that in spite of the obvious pitfalls of such information, the patterns that emerge from data are incredibly important for furthering our understanding in many contexts. The problem lies less with the collection of information, and more with the lack of a holistic approach to interpretation and appropriate representations of the data.
[study kit] Edwards, Paul N. (2010) ‘Introduction’ in A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming Cambridge, MA: MIT Press: xiii-xviii
[First published 20 October 2015]