The exhibition’s title Machine Teaching Commons / Teaching Machine Commons conveys two perspectives, two sides of the same coin. The first perspective conveyed by the first part of the title, Machine Teaching Commons, refers to a design exploration around how protocols, regulations, and rituals of commoning change or emerge when we introduce Machine Teaching* to it. Machine Teaching Commons refers to imagining and rehearsing ways of community-driven data provision, machine teaching including manual data labelling.

The second perspective, conveyed by the second part of the title, Teaching Machine Commons, emphasizes the issue of maintaining autonomy in the face of the machine when a resource-sharing community delegates decision-making to a machine. Teaching Machine Commons investigates moments when the spirit of commoning impinges on the setup and operation of the machine. And it probes venues of hardwiring commoning into the algorithmic infrastructures. (Teaching Machine Commons sounds a bit like teaching the Machine manners, and that is not too bad).

The role of technology in humane

The exhibition's approach to exploring the role of technology in humane, just and sometimes more-than-human urban futures is a critical but hopeful one. The theory of change underlying the curation is that we not only have to make visible the invisible, such as the concealed labour conditions behind a pizza delivery or extractivism of AI systems but we also have to find ways to imagine otherwise. This exhibition and the accompanying MTC/TMC Symposium bring together perspectives – cautionary voices, hopeful voices and ones that help us think of machine teaching as a boundary object.

Pathways toward just algoritmic governance of urban resources

The MTC/TMC Exhibition emerged from the critical making project Scaling Material Urban Commons (SMUC, 2021-2024). In a time of extractivist and biased algorithms, SMUC explored pathways towards just algorithmic governance of urban resources. Hosted by the Critical Media Lab Basel, the project rehearsed collective machine teaching and community-based data practices to distribute rescued food.

*Machine Teaching is another word for Machine Learning, but instead of emphasizing the machine's capacity to learn and concealing human decisions and labour, machine teaching emphasises the agency of the people or communities training the algorithm.

To SMUC Archive Website →