Exploring Social Disparities in Machine Learning and Human Data Labeling

Today we’re joined by Vinodkumar Prabhakaran, a Senior Research Scientist at Google Research. In our conversation with Vinod, we discuss his two main areas of research, using ML, specifically NLP, to explore these social disparities, and how these same social disparities are captured and propagated within machine learning tools. We explore a few specific projects, the first using NLP to analyze interactions between police officers and community members, determining factors like level of respect or politeness and how they play out across a spectrum of community members. We also discuss his work on understanding how bias creeps into the pipeline of building ML models, whether it be from the data or the person building the model. Finally, for those working with human annotators, Vinod shares his thoughts on how to incorporate principles of fairness to help build more robust models. 

The complete show notes for this episode can be found at https://twimlai.com/go/617.