Using machine learning to track human development at global scale and high spatial resolution
The Human Development Index (HDI) is widely used by policymakers and academics to summarize three key dimensions of wellbeing: the population’s health, human capital, and standard of living. A more comprehensive measure of wellbeing than income or wealth alone, HDI is used to categorize countries by their level of human development, which, in turn, can determine allocations of global resources. However, the United Nations releases official global estimates of HDI annually only at the highly aggregated national level, preventing their use for many policy and aid applications. This project builds on recent advances in machine learning and satellite imagery to develop the first global estimates of HDI for second-level administrative units (e.g., municipalities/counties) and for a global ~10km × 10km grid. To accomplish this, we develop and validate a generalizable downscaling technique based on satellite imagery that allows for training and prediction with observations of arbitrary shape and size. Our results indicate that more than half of the global population was previously assigned to the incorrect HDI quintile within each country, due to aggregation bias resulting from lower resolution estimates.
Speakers:
Hannah Druckenmiller
Assistant Professor
California Institute of Technology
Moderators:
Markus Reichstein
Director & Professor
Max Planck Institute for Biogeochemistry
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What is AI for Good?
We have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.
More than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.
AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.
Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.
The Human Development Index (HDI) is widely used by policymakers and academics to summarize three key dimensions of wellbeing: the population’s health, human capital, and standard of living. A more comprehensive measure of wellbeing than income or wealth alone, HDI is used to categorize countries by their level of human development, which, in turn, can determine allocations of global resources. However, the United Nations releases official global estimates of HDI annually only at the highly aggregated national level, preventing their use for many policy and aid applications. This project builds on recent advances in machine learning and satellite imagery to develop the first global estimates of HDI for second-level administrative units (e.g., municipalities/counties) and for a global ~10km × 10km grid. To accomplish this, we develop and validate a generalizable downscaling technique based on satellite imagery that allows for training and prediction with observations of arbitrary shape and size. Our results indicate that more than half of the global population was previously assigned to the incorrect HDI quintile within each country, due to aggregation bias resulting from lower resolution estimates.
Speakers:
Hannah Druckenmiller
Assistant Professor
California Institute of Technology
Moderators:
Markus Reichstein
Director & Professor
Max Planck Institute for Biogeochemistry
Join the Neural Network!
https://aiforgood.itu.int/neural-network/
The AI for Good networking community platform powered by AI.
Designed to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI.
Watch the latest #AIforGood videos!
https://www.youtube.com/c/AIforGood/videos
Stay updated and join our weekly AI for Good newsletter:
http://eepurl.com/gI2kJ5
Check out the latest AI for Good news:
https://aiforgood.itu.int/newsroom/
Explore the AI for Good blog:
https://aiforgood.itu.int/ai-for-good-blog/
Connect on our social media:
Website: https://aiforgood.itu.int/
Twitter: https://twitter.com/AIforGood
LinkedIn Page: https://www.linkedin.com/company/26511907
LinkedIn Group: https://www.linkedin.com/groups/8567748
Instagram: https://www.instagram.com/aiforgood
Facebook: https://www.facebook.com/AIforGood
What is AI for Good?
We have less than 10 years to solve the UN SDGs and AI holds great promise to advance many of the sustainable development goals and targets.
More than a Summit, more than a movement, AI for Good is presented as a year round digital platform where AI innovators and problem owners learn, build and connect to help identify practical AI solutions to advance the United Nations Sustainable Development Goals.
AI for Good is organized by ITU in partnership with 40 UN Sister Agencies and co-convened with Switzerland.
Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.
