Radio Explorations: Data Observatories of Environmental Radio Tranismissions
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25.03.2021
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06 - Presentation
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Lausanne
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The way we order things informs the way we understand and interact with the world, or attempt to design it. A data-driven approach promises to treat the world with computational objectivity. Taken at face value, it rationalizes fairness and adequacy in ways inaccessible to humans; it also implies a certain loss of agency in deciding what matters and how. I propose to invert these concerns and engage with a data-driven approach to providing avenues for recognition of the entanglement of nature and culture, of order and disorder, of energy and matter. In the SNF-funded project Radio Explorations, I examine the capacity of machine learning techniques to support characterizing and identifying environmental radio transmissions. I work with a digital archive (Radio Signal Identification Guide Wiki, maintained by radio enthusiasts) reorganized as a 'digital observatory' that orders data on radio signals based on computable similarity. Through artificial neural networks (ANN) of the self-organising map (SOM), I expose ambient milieus of data as clusters that are found in the dataset. I use the observatory as a way finding tool, to navigate the vast landscape of radio signals, difficult to differentiate and identify even to signal processing experts. By rendering signals commensurable in this way, I articulate ways to study similarity between them, the implications of their discretization as digital audio recordings, and the difference between naturally occurring (atmospheric lightning discharges) and culturally encoded (telecommunications) signals. 'Data observatory' activates interests, reorganizes the archive so that we can decide where to go. While it remains clear that SOM is always only sorting high dimensional data in the space of possibilities that are always/already encoded, I am interested in identifying and characterizing radio signals as technical, cultural and natural phenomena all at once. With this project I hope to contribute to contemporary efforts in promoting digital literacy and seizing more democratic control over digital tools, while acknowledging their political implications.
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Deep City: Climate change, democracy and the digital
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English
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SAVIC, Selena, 2021. Radio Explorations: Data Observatories of Environmental Radio Tranismissions. Deep City: Climate change, democracy and the digital. Lausanne. 25 März 2021. Verfügbar unter: https://doi.org/10.26041/fhnw-3721