Simons Institute Workshop Wrong at the Root: Racial Bias and the Tension Between Numbers and Words in Non-Internet Data
Workshop: Theory of Computing: CS: Data Science | June 5 – 7, 2019 every day | 9 a.m.-5 p.m. | Calvin Laboratory (Simons Institute for the Theory of Computing)
Artificially intelligent systems extrapolate from historical training data. While the training process is robust to noisy data, systematically biased data will inexorably lead to biased systems. The emerging field of algorithmic fairness seeks interventions to blunt the downstream effects of data bias. Initial work has focused on classification and prediction algorithms.
This cross-cutting workshop will examine the sources and nature of racial bias in a range of settings such as genomics, medicine, credit systems, bail and probate calculations, and automated surveillance. We will survey state-of-the-art algorithmic literature, and lay a more comprehensive intellectual foundation for advancing algorithmic fairness.
All events take place at the Simons Institute, UC Berkeley. Registration is required to attend this workshop. Space may be limited, and you are advised to register early. To submit your name for consideration, please register online and await confirmation: https://simons.berkeley.edu/workshops/fairness-workshop-1