Data Humanization, Epistemology, and Mystification

On Lightbeam and The Circle

Video: ReForm | Data Becomes Art in Immersive Visualizations

            This 12-minute video about the emergence of “data humanization” and data art was clarifying for me in terms of understanding Lightbeam and The Circle. Terms that stuck out to me were “anxiety” and “intimacy;” From our discussion in class, a main takeaway from the Lightbeam experiment was the disquieting lack of control we have over where our data goes, even with the comforting anonymity and freedom of using the internet. The aestheticized terms that this video utilizes were illuminating for my literarily-oriented brain—Kate Crawford even calls to mind both the sublime and the uncanny, claiming that a dimension of data art is creating “something once familiar becoming strange.” With data humanization projects—like Lightbeam, PastPerfect, and the art featured in the video—attempting to ground the technical into the human, the emotional, the tangible, I’m left questioning what kinds of cultural values this impulse (to humanize data, and to data-fy humans) prioritizes. I think that in Transmission there was a focus on speed, lightness, modernity, and money as being the motivation, but thinking comparatively, I don’t think I would say the same for The Circle. Instead, I’d offer that The Circle is more thematically and symbolically concerned with representation, totality, social conditioning, perfection, and of course, transparency.

            Attached to this anxiety of transparency is, I think, the question of epistemology—the nature of knowledge, or how we know what we know. With Lightbeam, self-doxxing, and the anxiety that came with performing these investigations, my recurring thought was, what am I supposed to do with this information?  What has it taught me? I think that this applies to (to make a generalization) the cultural obsession with self-evaluation and data in general, whether through exercises like these, through online surveys, through follower-counting, Tinder match-message-meeting ratios, ad infinitum. In these masochistic practices, there is a fixation with omniscience and with pattern-seeking, but an anxiety over the inability (or at least, limited ability) to do anything about the numbers we confront. Despite the anxiety that this power deficit creates, people like Mae still compulsively participate in data culture, collection, and production. Data humanization, as an aesthetic project, seems to perform a deconstructionist or post-structural (I can’t decide which) mystification of data, complicating and questioning the supposed revelations and truths of statistics rather than, to evoke Derrida, privileging them.

image: from Giorgia Lupi and Stefanie Posavec’s data humanization project, Dear Data (2016)

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