The power of machine learning is being harnessed to address humanity’s most pressing challenges by analyzing community-driven insights and identifying tailored solutions.
By analyzing unique family-defined economic challenges in Paraguay, Kenya, and Egypt, a new project is harnessing machine learning to identify solutions tailored to specific community needs.
Poverty isn’t just about low income — it involves interconnected challenges shaped by systemic issues and personal behaviors.
A key step in overcoming it is empowering families to define their unique economic challenges and assess their situations. Fundación Paraguaya’s Poverty Stoplight, a survey-based digital tool, helps families do just that.
With TWCF funding, Robert Krueger of Worcester Polytechnic Institute (WPI) leads a project that leverages the power of AI and the Stoplight tool in the fight against poverty.
His team is using machine learning to analyze Poverty Stoplight's data from families in Paraguay, Kenya, and Egypt, identifying “clusters” of opportunities where specific economic activities could be established to benefit communities and drive lasting change.
WPI News featured the launch of this project on their podcast.
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Historically, approaches to poverty have often relied on a narrow focus, such as income levels. However, people’s experiences of poverty often involve multiple, interconnected factors, such as inadequate housing or access to sanitation.
“It’s important to understand the needs of people in low- and middle-income countries, the resources they possess, and what they say they need to gain self-sufficiency through economic development,” Krueger says. “With AI, we can rapidly parse through large amounts of data to identify opportunities, not just needs.”
The project leverages data from the Poverty Stoplight tool which allows families to define their own challenges across diverse dimensions of wellbeing.
This innovative approach ensures that solutions are tailored to the unique needs of each community. As an example, Krueger highlights how training carpenters and masons to construct composting toilets in areas with poor sanitation can create jobs while simultaneously addressing public health needs. Such localized, multi-faceted strategies stand in contrast to one-size-fits-all economic policies.
Another objective of this project, says Krueger, is to show how the rapidly advancing field of AI can be integrated with social sciences to enhance policies and interventions. This involves demonstrating to data scientists how their skills can be leveraged in new and impactful ways, while also highlighting to social scientists the positive potential of AI tools. "The potential of AI and the social sciences lies in how we use information and apply our different skills to pull correlations and explanations out of vast amounts of data so we can take the critical steps that will be necessary to address humanity’s most pressing problems," he shares.
Learn more about how the project plans to determine economic opportunities from the viewpoint of those who would benefit from the allocation of resources here.
Image Source: Poverty Stoplight, resources. Participants using the Poverty Stoplight program.
