Researchers use machine learning on household surveys to optimize global antipoverty program targeting and costs
Summary
UC Berkeley professor Joshua Blumenstock uses machine learning and AI on household surveys to optimize targeting of antipoverty programs and estimate the cost to end extreme global poverty.
View Cached Full Text
Cached at: 07/06/26, 08:19 PM
Similar Articles
Measuring Poverty and Inequality with Reduced Data: A Machine Learning Approach Using Nigerian Household Data
This paper applies Random Forest Recursive Feature Elimination to Nigerian household survey data to identify minimal predictors that accurately classify poverty status, quintile distribution, and inequality position, showing that machine learning can reduce data requirements while preserving distributional information for monitoring poverty and inequality.
New AI model finds a cheaper path to healthier eating
Researchers at UC Davis developed an AI model that suggests small ingredient swaps to improve nutrition and reduce meal costs by up to 34%, as reported in PLOS Digital Health.
What happens when frontier LLMs are deployed in rural Rwanda? Lessons on usefulness, language gaps, and incorrect answers [D]
GiveDirectly's pilot in rural Rwanda paired unconditional cash transfers with a general-purpose AI chatbot, revealing both value as an always-available advisor and critical limitations including language gaps, irrelevant responses, and confidently incorrect answers, raising questions about evaluating models beyond benchmarks.
Empowering the Next Generation: Machine Learning at Berkeley's High School Workshop Initiative
Machine Learning @ Berkeley has launched a new high school workshop initiative called GREP to make machine learning education more accessible and inclusive for students of all backgrounds.
Measuring the impact of learning with AI in Sierra Leone and beyond
A pre-registered trial in Sierra Leone found that AI-powered Guided Learning significantly improved math scores, achieving 1.2 to 1.7 years of progress in eight weeks, while teachers reported enhanced professional growth and a shift toward facilitation roles.