Latent Spaces. Performing Ambiguous Data, 2021-2024


Central to our arts-based research project on the datafied contemporary are notions of the latent space – the (technical/conceptual) realm in which different possibilities co-exist before one (or more) is then realized – and of ambiguity – the state in which different valid readings co-exist within a system of meaning. The performing of data in the project’s subtitle refers to the fact that we are developing this perspective not just through critical reflection but also through artistic interventions/creations.

Value of ambiguity

In this project, we take data to be inherently ambiguous, that is, full of meaning to be decided upon, with an array of valid possibilities co-existing within “latent spaces”. This ambiguity is produced and processed in every segment of the data pipeline, from the moment of data collection (or better, data creation), to the output of data-analytical processes, and everything in between. Drawing on the strength of artistic practices, we take this ambiguity as something productive because by understanding meaning in data as open, by exploring how technical issues are unavoidably also social and cultural ones, which always also includes values and interests, we can begin to think about ways of negotiating this complexity.

Artistic field studies and transversal approaches

The research unfolds through four artistic field studies and two transversal approaches. The first two studies probe what is usually called “raw data”, here location data as it is emitted from beacon signals and from GPS systems, the latter two probe black boxes of data processing in social media. What all four have in common is that they use performative means to engage with and articulate the particular type of ambiguity of data in their respective field settings. The transversal approaches are data science and media theory. Both collaborate closely with the artistic field studies by providing their specific tools but they also learn from the artists’ ability to articulate ambiguity for their respective fields.

The project is structured into four artistic field studies:

– Data beacons. An exploration of the latent space of ephemeral data in movement (Gordan Savičić)

Unreal Data (!Mediengruppe Bitnik)

Queering the Influence Industry (Cornelia Sollfrank, #purplenoise)

Data User Practice (Shusha Niederberger, as a PHD project)

and two transversal approaches working with and across the artistic field studies:

Media Theory (Felix Stalder, project lead)

Data Science and Machine Learning (Alexandre Puttick)

This research project is funded by Swiss National Science Fund (SNF), and hostet at IFCAR (Institute for Contemporary Art Research) at ZHDK Zurich University of the Arts.

More info on the project website