The Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT has provided 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.
The age of AI has brought widespread optimism and skepticism about its effects on society. To realize the full potential of AI, Project AI Evidence (PAIE) will identify which AI solutions work and for whom, and scale only the most effective, inclusive and responsible solutions – while minimizing those that could potentially cause harm.
PAIE will generate evidence on what works by connecting governments, tech companies, and nonprofits with world-class economists across MIT and J-PAL’s global network to evaluate and improve AI solutions to societal challenges.
The new initiative is prioritizing questions that policymakers are already asking: Do AI-assisted learning tools help all children learn? How can early warning flood systems help people affected by natural disasters? Can machine learning algorithms help reduce deforestation in the Amazon? Can AI-powered chatbots help improve people’s health? In the coming years, PAIE will run a series of funding competitions to invite proposals for evaluating AI tools that will address these and many other questions.
PAIE is financially supported by a grant from Google.org, philanthropic support from Community Jameel, grants from the Canadian Center for International Development Research and UK International Development, and a collaboration agreement with Amazon Web Services. Through a grant from Eric and Wendy Schmidt, awarded by the recommendation of Schmidt Sciences, the initiative will also study generic AI in the workplace, particularly in low- and middle-income countries.
Alex Diaz, head of AI for social good at Google.org, says, “On Project AI Evidence we are thrilled to collaborate with MIT and J-PAL, who are already leaders in this field. AI has huge potential to benefit all people, but if we are to realize this potential we urgently need to study what works, what doesn’t, and why.”
“Artificial intelligence holds extraordinary potential, but only when the tools, knowledge, and power to shape it are accessible to all – including relevant research and evidence on what works and what doesn’t,” says Maggie Gorman-Velez, vice president of strategy, sectors and policies at IDRC. “That is why IDRC is proud to support this new evaluation work as part of our ongoing commitment to responsible scaling of proven safe, inclusive and locally relevant AI innovations.”
J-PAL is uniquely positioned to help understand the impacts of AI on society: since its founding in 2003, J-PAL’s network of researchers has led more than 2,500 rigorous evaluations of social policies and programs around the world. Through PAIE, J-PAL will bring together leading experts in AI technology, research, and social policy, with MIT President Sally Kornbluth’s focus on generative AI as a strategic priority.
PAIE is chaired by Professor Joshua Blumenstock of the University of California at Berkeley; Iqbal Dhaliwal, Global Executive Director, J-Pal; and Professor David Yanagizawa-Drott of the University of Zurich.
New assessment of pressing policy questions
The studies funded in the first round of PAIE’s competition explore pressing questions in key areas such as education, health, climate and economic opportunity.
How can AI be most effective in classrooms, helping both students and teachers?
Existing research shows that personalized learning is important for students, but it is challenging to implement with limited resources. In Kenya, education social enterprise EIDU has developed an AI tool that helps teachers identify learning gaps and optimize their daily lesson plans. In India, Non Government Organization (NGO) Pratham is developing an AI tool to increase the impact and scale of evidence-informed learning at the right level approach. J-PAL researchers Daron Acemoglu, Iqbal Dhaliwal and Francisco Gallego will work with both organizations to study the impacts and potential of these different use cases on teacher productivity and student learning.
Can AI tools reduce gender discrimination in schools?
Researchers are collaborating with Italy’s Ministry of Education to evaluate whether AI tools can help reduce the gender gap in student performance by addressing teachers’ unconscious biases. J-PAL colleagues Michela Karlana and Will Dobie, along with Francesca Miserocchi and Eleonora Patacchini, will study the effects of two AI tools, one that helps teachers predict performance and another that gives feedback in real-time on the variability of their decisions.
Can AI help career counselors find more job opportunities?
In Kenya, researchers are evaluating whether AI tools can identify neglected skills and open up employment opportunities, particularly for youth, women and those with no formal education. In collaboration with the NGOs Swahilipot and Tabia, Jasmine Baer and J-PAL researcher Christian Meyer will evaluate how the tool changes people’s job search strategies and employment. This study will shed light on AI as a complement to, rather than a substitute for, human expertise in career guidance.
looking forward
As the use of AI in the social sector evolves, these assessments are a first step in the search for effective, responsible solutions that will be at the forefront of reducing poverty and inequality.
J-PAL’s Dhaliwal says, “J-PAL has a long history of evaluating innovative technology and its potential to improve people’s lives. While AI has incredible potential, we need to maximize its benefits and minimize potential harms. We are grateful to our donors, sponsors and partners for their catalytic support in launching PAIE, which will help us do this by continuing to expand the evidence on the impacts of AI innovations.”
J-Pal is also looking for new partners who share its vision of exploring and scaling 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-PAIL’s newsletter or contact paie@povertyactionlab.org.
