Harnessing AI to Combat Extreme Poverty: Opportunities and Challenges

Approximately 700 million people worldwide live in extreme poverty, surviving on less than $2.15 per day. Eradicating poverty is one of the United Nations' Sustainable Development Goals, yet measuring poverty remains a challenge due to the high cost and time-consuming nature of data collection. Artificial intelligence (AI) offers a promising solution, enabling rapid data analysis, broader population coverage, and the identification of patterns that human experts might overlook. In response, the World Bank is developing AI tools to predict food crises and violent conflicts while extracting insights from aid intervention data.

However, AI models are not without limitations. They can exhibit biases, potentially overlooking the poorest individuals who lack digital records. That said, existing poverty assessment systems are also imperfect. Traditional methods, such as household surveys, are costly and time-intensive. By contrast, AI-powered approaches leveraging satellite imagery and mobile phone data offer a more efficient means of identifying impoverished regions and individuals. For instance, a research team at Stanford University successfully used AI to analyze satellite images and predict poverty levels in African villages, achieving results comparable to field surveys at a significantly lower cost.

One notable example is Togo's NOVISSI social protection program, which used AI to analyze mobile phone usage patterns and satellite imagery, efficiently distributing $34 million in aid. Similar AI-driven initiatives are being implemented across other African nations. While AI predictions are not always entirely accurate, their ability to rapidly respond to emergencies makes them invaluable in crisis situations.

Despite AI's potential in poverty alleviation, experts caution against overreliance on technology. AI cannot fully replace on-the-ground surveys, particularly when measuring multidimensional poverty. Nevertheless, in scenarios with limited budgets and economic disruptions, AI could play a crucial role in ensuring aid reaches those who need it most. Moving forward, a hybrid approach that integrates AI with traditional field assessments may become the new standard in global poverty alleviation efforts.