Are Artificial Intelligence and Machine Learning really the right metaphors to address training sets that feed into automated processes? Kate Crawford and Trevor Paglen look into the production of training data and uncover the historical origins, labor practices, infrastructures, and epistemological assumptions, with biases and skews built into them from the outset.

Programming descriptions are generated by participants and do not necessarily reflect the opinions of SXSW.