IST Lunch Bunch

Tuesday October 15, 2019 12:00 PM

Measuring Economic Development from Space

Speaker: Stefano Ermon, Computer Science, Stanford University
Location: Annenberg 105


Recent technological developments are creating new spatio-temporal data streams that contain a wealth of information relevant to sustainable development goals. Modern AI techniques have the potential to yield accurate, inexpensive, and highly scalable models to inform research and policy. A key challenge, however, is the lack of large quantities of labeled data that often characterize successful machine learning applications. In this talk, I will present new approaches for learning useful spatio-temporal models in contexts where labeled training data is scarce or not available at all. I will show applications to predict and map poverty in developing countries, monitor  agricultural productivity and food security outcomes, and map infrastructure access in Africa. Finally, I will discuss opportunities and challenges for using these predictions to support decision making, including techniques calibration and for inferring human preferences from data.

Series IST Lunch Bunch

Contact: Diane Goodfellow diane@cms.caltech.edu