Designing societally beneficial Reinforcement Learning (RL) systems
In this post, we aim to illustrate the different modalities harms can take when augmented with the temporal axis of RL. To combat these novel societal risks, we also propose a new kind of documentation for dynamic Machine Learning systems which aims to assess and monitor these risks both before and after deployment.
15 May 2022, by
BAIR Blog