Machine learning tools are helping researchers understand how income is distributed and progress towards reducing inequality

How artificial intelligence is helping to identify global inequalities

Machine learning tools are helping researchers understand how income is distributed and progress towards reducing inequality

How to Save Humanity in 17 Goals: reduce inequality within and among countries (SDG 10)

Francisco Ferreira’s first exposure to inequality of opportunity was during his daily ride to school in São Paulo, Brazil, and seeing children his age selling chewing gum on the streets. Ferreira, a former World Bank economist who now researches inequality at the London School of Economics, speculates on the wasted human talent caused by such hardships, and how many more scientists, engineers, entrepreneurs and writers there would be if inequalities could be tackled at an early stage in children’s lives. “I think it deserves even more attention than it already gets,” he says, before going on to describe progress towards delivering Sustainable Development Goal 10: to reduce inequality in and among countries, and how best to measure it. Ferreira outlines how machine learning tools are helping to identify the most powerful predictors of societal divisions and how income is distributed.

How to Save Humanity in 17 Goals is a podcast series that profiles scientists whose work addresses one or more of the SDGs. Episodes 7–12 are produced in partnership with Nature Water, and introduced by Fabio Pulizzi, its chief editor.

doi: https://doi.org/10.1038/d41586-024-01534-2

This story originally appeared on: Nature - Author:Dom Byrne