Saved by Sarah Drinkwater and
Datasets as Imagination
This begs the question: What might it mean to reimagine the form of these datasets in a world unconstrained by pressures like speed, scale, and universality? By looking to artists like Anna Ridler and others for their rejection of “off-the-shelf” datasets, we can imagine what it would be like to curate datasets with much deeper intention and... See more
Where AI differs is its interaction with data and rights. Unlike coding assistants trained on open-source software, most commercial image generation tools are trained on copyrighted work. It’s a non-consensual, extractive practice in an already-precarious industry. It’s always hard to put the tech genie back in the box, but I think this is a case... See more
The Lab’s primary focus is on the ways in which artists and designers are adopting, adapting and remaking AI processes, building their own datasets and reaching into the ‘grey box’ of AI technologies.