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Mathematicians have used machine learning to develop a new model for measuring poverty in different countries that junks old notions of a fixed poverty line .
The study by academics at Aston University, published in the journal
Nature Communications, suggests mainstream thinking around poverty is outdated because it places too much emphasis on subjective notions of basic needs and fails to capture the full complexity of how people use their incomes.
They say their new model - which uses computer algorithms to synthesise vast amounts of spending and economic data - could help policymakers worldwide predict future poverty levels and plan interventions to alleviate the problem.
Poverty line shmoverty line: Backed by AI, researchers want a new way to measure poverty
The poverty line concept is outdated and counterproductive.
Poverty is the common denominator for developing nations, usually defined against an arbitrary poverty line. Individuals or countries below it are considered ‘poor’ and those above it, not so much. But this isn’t necessarily the only way of measuring poverty, and it’s not the best way by any stretch. A team of researchers are now suggesting the use of machine learning to define what poverty really means in different contexts.
Image credit: Flickr / Anna Wolf