Mimi Onuoha is a Brooklyn-based artist and researcher examining the implications of data collection and computational categorization. Her work uses code, writing, and sculptures to explore missing data and the ways in which people are abstracted, represented, and classified.

Onuoha has been in residence at Eyebeam Art & Technology Center, the Data & Society Research Institute, Columbia’s Tow Center, and the Royal College of Art. She has spoken and exhibited in festivals internationally, and in 2014 she was selected to be in the inaugural class of Fulbright-National Geographic Digital Storytelling Fellows. She is also a contributor at Quartz, where she uses code and data to tell stories about the implications of emerging technologies.
How We Became Machine Readable

What if the structure of information reveals more than the information itself? What if the most crucial aspect of a dataset is the moment before it becomes one? This talk is about the messy spaces between categorization and collection, as explored through a series of projects that aim to reveal the ways in which we are being and have always been abstracted, represented, classified, and forgotten.