This ongoing research investigates the notion of uncertainty in data systems. The work is centered around the confidence score, indicating the estimated accuracy of predictions by machine learning algorithms. A value that is rarely communicated to end-users.

It takes the form of a performative dialogue between the dancer and the motion tracking algorithm, experimenting with different ways the score is represented in the scene.

In an effort to make media art more accessible to new audiences, we have also adapted this research as an interactive installation in a pub, showing footage of the performance but also enabling pubgoers to play around with the motion tracking interface. The first iteration of this format succeeded in inviting personal and in-depth conversations about tracking and data protection among strangers at the table.