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MIT’s J-PAL Launches Project AI Evidence to Evaluate AI Solutions Against Poverty

MIT’s J-PAL secures funding for Project AI Evidence, launching eight studies to evaluate AI’s effectiveness in combating poverty with backing from Google.org and others.

The Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT has announced funding for eight new research studies aimed at exploring how innovations in artificial intelligence (AI) can be leveraged to combat poverty. This initiative, named Project AI Evidence (PAIE), seeks to clarify the effectiveness of various AI solutions and ensure that only the most beneficial and responsible technologies are expanded, while minimizing those that may pose risks.

The advent of AI has sparked a mix of enthusiasm and skepticism regarding its societal impacts. PAIE aims to bridge this gap by generating concrete evidence on successful AI applications. The project will foster collaboration among governments, technology firms, and nonprofit organizations, connecting them with leading economists at MIT and within J-PAL’s global network to assess and refine AI technologies addressing complex social issues.

The initiative will focus on pressing inquiries that policymakers are currently discussing, such as the efficacy of AI-assisted educational tools, the role of early-warning systems in mitigating natural disasters, the application of machine learning to combat deforestation in the Amazon, and the potential of AI-driven chatbots to enhance public health. Over the coming years, PAIE will conduct a series of funding competitions to solicit proposals that evaluate AI applications capable of resolving such critical questions.

Financial backing for PAIE comes from various sources, including a grant from Google.org, philanthropic contributions from Community Jameel, and grants from Canada’s International Development Research Centre and UK International Development. Moreover, PAIE has partnered with Amazon Web Services and received support from Eric and Wendy Schmidt, focusing on the exploration of generative AI in workplace settings, particularly in low- and middle-income nations.

Alex Diaz, head of AI for social good at Google.org, expressed enthusiasm about the collaboration, emphasizing the imperative to investigate which AI applications provide genuine benefits. “AI has great potential to benefit all people, but we urgently need to study what works, what doesn’t, and why, if we are to realize this potential,” he stated.

Furthermore, Maggie Gorman-Velez, vice president of strategy at the International Development Research Centre (IDRC), underscored the importance of accessible research in empowering diverse stakeholders to shape AI’s trajectory responsibly. “That is why IDRC is proud to be supporting this new evaluation work as part of our ongoing commitment to the responsible scaling of proven safe, inclusive, and locally relevant AI innovations,” she remarked.

Since its establishment in 2003, J-PAL has conducted over 2,500 rigorous evaluations of social policies and programs worldwide, establishing itself as a pivotal entity in assessing the societal effects of AI. Through PAIE, J-PAL plans to unite experts in AI technology and social policy, aligning with MIT President Sally Kornbluth’s emphasis on generative AI as a strategic priority.

Chaired by Professor Joshua Blumenstock of the University of California at Berkeley, alongside J-PAL Global Executive Director Iqbal Dhaliwal and Professor David Yanagizawa-Drott of the University of Zurich, PAIE has dedicated its initial round of funding to urgent policy questions across education, health, climate, and economic opportunity.

Among the research initiatives, one study seeks to enhance classroom effectiveness through AI. For example, an education enterprise in Kenya, EIDU, has developed an AI tool designed to help teachers identify learning gaps and tailor lesson plans accordingly. In India, the NGO Pratham is working on a similar AI tool aimed at scaling the evidence-informed Teaching at the Right Level approach. J-PAL researchers, including Daron Acemoglu and Iqbal Dhaliwal, will collaborate with these organizations to evaluate the impact of these technologies on both teachers’ productivity and students’ learning outcomes.

Another study explores the potential of AI tools to mitigate gender bias in educational settings, in partnership with Italy’s Ministry of Education. Researchers Michela Carlana and Will Dobbie will assess whether AI can help address teachers’ unconscious biases and improve gender equity in student performance.

A separate initiative in Kenya will evaluate an AI tool aimed at uncovering hidden job opportunities by identifying overlooked skills, particularly for marginalized groups such as youth and women. This project involves collaboration with NGOs Swahilipot and Tabiya; researchers Jasmin Baier and Christian Meyer will investigate how the AI tool alters job search strategies and employment outcomes.

As the use of AI in the social sector progresses, these evaluations represent an initial stride toward identifying effective and responsible solutions for alleviating poverty and inequality. Dhaliwal from J-PAL remarked, “While AI has incredible potential, we need to maximize its benefits and minimize possible harms. We’re grateful to our donors, sponsors, and collaborators for their catalytic support in launching PAIE.”

J-PAL is actively seeking new collaborators who share its vision of discovering and amplifying real-world AI solutions. The organization aims to assist more governments and social sector entities in adopting AI responsibly while continuing to expand funding for additional evaluations and providing policy guidance grounded in the latest research.

For more information on Project AI Evidence, interested parties can subscribe to J-PAL’s newsletter or contact [email protected].

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