Source: MIT News - AI

Project AI Evidence (PAIE) – New Funding for AI‑Driven Poverty Research

The Abdul Latif Jameel Poverty Action Lab (J‑PAL) at MIT has awarded funding to eight new research studies to understand how artificial‑intelligence innovations can be used in the fight against poverty through its new Project AI Evidence (PAIE).

The age of AI has brought wide‑ranging optimism and skepticism about its effects on society. To realize AI’s full potential, PAIE will identify which AI solutions work and for whom, and scale only the most effective, inclusive, and responsible solutions — while scaling down those that may potentially cause harm.

PAIE will generate evidence on what works by connecting governments, tech companies, and nonprofits with world‑class economists at MIT and across J‑PAL’s global network to evaluate and improve AI solutions to entrenched social challenges.

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Core Questions Guiding the Initiative

PAIE is prioritising the questions policymakers are already asking:

• Education: Do AI‑assisted teaching tools help all children learn?
• Disaster response: How can early‑warning flood systems help people affected by natural disasters?
• Environment: Can machine‑learning algorithms help reduce deforestation in the Amazon?
• Health: Can AI‑powered chatbots improve people’s health?

In the coming years, PAIE will run a series of funding competitions to invite proposals for evaluations of AI tools that address these and many other pressing issues.

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Funding & Partnerships

PAIE is financially supported by:

• A grant from Google.org
• Philanthropic support from Community Jameel
• A grant from Canada’s International Development Research Centre (IDRC) and UK International Development
• A collaboration agreement with Amazon Web Services
• A grant from Eric and Wendy Schmidt, awarded on the recommendation of Schmidt Sciences, to study generative AI in the workplace—particularly in low‑ and middle‑income countries

Alex Diaz, head of AI for social good at Google.org, says:
“We’re thrilled to collaborate with MIT and J‑PAL, already leaders in this space, on Project AI Evidence. 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.”

Maggie Gorman‑Velez, vice‑president of strategy, regions, and policies at IDRC, adds:
“Artificial intelligence holds extraordinary potential, but only if the tools, knowledge, and power to shape it are accessible to all — that includes contextually grounded research and evidence on what works and what does not. 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.”

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Leadership

• Chair: Professor Joshua Blumenstock (University of California, Berkeley)
• J‑PAL Global Executive Director: Iqbal Dhaliwal
• Co‑Chair: Professor David Yanagizawa‑Drott (University of Zurich)

J‑PAL’s track record: Since 2003, its network of researchers has led over 2,500 rigorous evaluations of social policies and programs worldwide. Through PAIE, J‑PAL will bring together leading experts in AI technology, research, and social policy, aligning with MIT President Sally Kornbluth’s focus on generative AI as a strategic priority.

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New Evaluations of Urgent Policy Questions

The studies funded in PAIE’s first round explore urgent questions across education, health, climate, and economic opportunity.

1. AI in Classrooms – Boosting Students & Teachers

• Background: Existing research shows personalized learning is vital but hard to implement with limited resources.
• Projects:
  • Kenya: Education social enterprise EIDU has built an AI tool that helps teachers identify learning gaps and adapt daily lesson plans.
  • India: NGO Pratham is developing an AI tool to scale the evidence‑informed Teaching at the Right Level approach.
• Researchers: Daron Acemoglu, Iqbal Dhaliwal, and Francisco Gallego will evaluate the effects on teachers’ productivity and students’ learning (project page).

2. Reducing Gender Bias in Schools

• Goal: Assess whether AI tools can help close gender gaps in student performance by addressing teachers’ unconscious biases.
• Collaboration: Italy’s Ministry of Education.
• Team: J‑PAL affiliates Michela Carlana and Will Dobbie, together with Francesca Miserocchi and Eleonora Patacchini.
• Tools:
  1. An AI system that predicts student performance.
  2. Real‑time feedback on the diversity of teachers’ decisions.

3. AI‑Enhanced Career Counseling

• Context: In Kenya, many youth, women, and individuals without formal education lack visibility into job opportunities.
• Intervention: An AI tool that identifies overlooked skills and matches users to suitable employment.
• Partners: NGOs Swahilipot and Tabiya.
• Researchers: Jasmin Baier and J‑PAL researcher Christian Meyer will evaluate the tool’s impact on job matching and skill discovery (project details).

(The original text truncated after “will evaluat”; the intended continuation is captured above.)

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Looking Ahead

PAIE will continue to commission, evaluate, and disseminate rigorous evidence on AI‑driven solutions that can be responsibly scaled to reduce poverty worldwide. By aligning cutting‑edge technology with robust social‑science methods, the initiative aims to ensure that AI benefits are inclusive, equitable, and sustainable.

How the tool changes people’s job‑search strategies and employment
This study will shed light on AI as a complement, rather than a substitute, for human expertise in career guidance.

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Looking forward

As the use of AI in the social sector evolves, these evaluations are a first step in discovering effective, responsible solutions that will go the farthest in alleviating poverty and inequality.

J‑PAL’s Dhaliwal notes:
“J‑PAL has a long history of evaluating innovative technology and its ability to improve people’s lives. 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, which will help us do exactly that by continuing to expand evidence on the impacts of AI innovations.”

J‑PAL is also seeking new collaborators who share its vision of discovering and scaling up real‑world AI solutions. It aims to support more governments and social‑sector organizations that want to adopt AI responsibly, and will continue to expand funding for new evaluations and provide policy guidance based on the latest research.

To learn more about Project AI Evidence, subscribe to J‑PAL’s newsletter or contact paie@povertyactionlab.org.