MS in Data Science Seminar Series: Why "Data for Good" is Imprecise

Friday, August 24, 12:30 PM - 2:00 PM

On-Campus Event - 101 Howard St., Room 150

'Data for good' is a term that is exciting in its use and general appeal but lacks precision from the perspective of technical practitioners. 'Data for Good' says little about the tools being used, the goals of the endeavor, or who we are serving. In this talk, I will navigate the multiple definitions that are often inconsistently applied to define an initiative as "data for good." By being more precise about what we mean, we can also identify where we can do better.

Sara Hooker is an AI Resident at Google Brain doing deep learning research on reliable explanations of model predictions for black-box models. Her main research interests gravitate towards interpretability, model compression, and security. In 2014, she founded Delta Analytics, a non-profit dedicated to bringing technical capacity to help non-profits across the world use machine learning for good. She spent her childhood in Africa, growing up in South Africa, Swaziland, Mozambique, Lesotho, and Kenya. Her family now lives in Monrovia, Liberia.