My proposed contribution focuses on platform-mediated labour, specifically location-based delivery work. It aims to investigate how algorithmic management and coordination reconfigure labour and cooperation through data infrastructures. The proposal draws on my PhD research on platform labour, completed in 2024. Methodologically, it combines ethnographic inquiry into food delivery platforms—conducted in London between 2022 and 2023—with a critical reading of two patents filed by Uber Technologies. The first patent (filed in 2019) describes a service coordination system aimed at optimising delivery times, while the second (2022) outlines a machine learning system for calculating couriers' Estimated Times of Arrival.

The presentation will highlight the role of unremunerated waiting time—including workers' free circulation across urban space—as a key yet unacknowledged productive force within platform economies. I will explore how this force is exploited by the computational infrastructures through which digital platforms broker the supply and demand of labour. This will involve examining the role of computational sensing, statistical inference and mathematical modelling within algorithmic management and coordination. The critical reading of the patents will serve to argue that the technical operations of algorithmic coordination reveal the inherently collective character of labour. For instance, such a reading suggests that, by virtue of computational mediation, delivery workers participate in their own self-management during unremunerated waiting time.

This inquiry offers a critique of the ‘gig' model—the socio-economic arrangement of platform labour—as a discursive device that renders labour individualised and competitive. Through this dissimulation, labour—albeit inherently collective—is selectively remunerated. Thus, the productivity of paid labour time—the ‘gig'—depends on the expropriation of labour's collective productive power.

Drawing from the insights of Autonomist Marxism and feminist critique within digital labour studies, I turn to the notion of data commons to thematise how computation mediates processes of exploitation and dispossession. I argue that computation, through its onto-formative power to qualify the relations it mediates, becomes central to the question of what counts as productive time—and is recognised as labour—and what does not count.

Lastly, the notion of data commons also provides a framework for understanding practices of resistance and counter-use as efforts to reconstruct collective knowledge and contest platform expropriation and individualisation.