The Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT has launched Project AI Evidence (PAIE), a major initiative designed to bring scientific rigor to the deployment of artificial intelligence in low- and middle-income countries. While the hype surrounding AI’s potential to solve global issues remains high, PAIE aims to bridge the gap between optimism and evidence by connecting governments and tech companies with world-class economists. By conducting randomized evaluations, the initiative will determine which AI tools truly empower marginalized communities and which ones might inadvertently cause harm or reinforce existing biases.

The first phase of the project features diverse pilot studies, including AI-powered teaching tools in Kenya and India that help educators identify specific student learning gaps and adapt lesson plans in real-time. Another notable project involves collaborating with Italy’s Ministry of Education to test if AI algorithms can mitigate unconscious gender bias in the classroom by providing teachers with immediate feedback on their decision-making diversity.

Supported by major entities like Google.org and Amazon Web Services, PAIE represents a strategic shift toward evidence-informed AI scaling rather than speculative implementation. The initiative underscores the importance of treating AI as a complement to human expertise rather than a wholesale replacement, particularly in sensitive sectors like career counseling and healthcare. As these evaluations progress, the findings will serve as a global blueprint for the ethical and effective integration of frontier technologies into international development policy.

The Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT has launched Project AI Evidence (PAIE), a major initiative designed to bring scientific rigor to the deployment of artificial intelligence in low- and middle-income countries. While the hype surrounding AI’s potential to solve global issues remains high, PAIE aims to bridge the gap between optimism and evidence by connecting governments and tech companies with world-class economists. By conducting randomized evaluations, the initiative will determine which AI tools truly empower marginalized communities and which ones might inadvertently cause harm or reinforce existing biases.

The first phase of the project features diverse pilot studies, including AI-powered teaching tools in Kenya and India that help educators identify specific student learning gaps and adapt lesson plans in real-time. Another notable project involves collaborating with Italy’s Ministry of Education to test if AI algorithms can mitigate unconscious gender bias in the classroom by providing teachers with immediate feedback on their decision-making diversity.

Supported by major entities like Google.org and Amazon Web Services, PAIE represents a strategic shift toward evidence-informed AI scaling rather than speculative implementation. The initiative underscores the importance of treating AI as a complement to human expertise rather than a wholesale replacement, particularly in sensitive sectors like career counseling and healthcare. As these evaluations progress, the findings will serve as a global blueprint for the ethical and effective integration of frontier technologies into international development policy.