Whether we are discussing measures in order to ‘flatten the curve’ in a pandemic, or what to wear given the most recent weather forecast, we base arguments on patterns observed in data. With this teaching research project, we propose an approach to practicing ethics when working with large datasets and designing data representations. We use and continuously re-programme web-based interfaces to sort, organize and explore a community-ran archive of radio signals. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that one can navigate machine learning models in a multi-narrative manner. We hold that the main challenge to digital ethics comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. Countering both the unbased narratives of techno-optimism, and the universalizing critique of technology, this approach to data and networks enables a situated critique of datafication and correlationism from within.

The project ist funded by FHNW Lehrfonds, Hochschullehre 2025 (49'378 CHF)