Stanford Using Artificial Intelligence to Meet the United Nations’ #1 Sustainability Goal

The elimination of poverty worldwide is the first of 17 UN Sustainable Development Goals for the year 2030. Stanford is mapping distribution of poverty using artificial intelligence to gain valuable real-time insights into progress against the goal to end poverty. This initiative combines machine learning with high-resolution satellite imagery to leverage fascinating new data on socioeconomic indicators of poverty and wealth.

Visit the project and help extend poverty prediction data:

• GitHub repository
• World Bank Living Standards Measurement Study (LSMS)
• Demographic and Health Surveys (DHS) Program

Read more about this amazing alternative approach to replacing live survey data about poverty to solve one of the world’s most pressing problems.

____

Related work that may also be of interest:

• An earlier paper detailing the transfer learning approach to poverty prediction
• A study on predicting poverty using mobile phone metadata