The Abdul Latif Jameel Poverty Motion Lab (J-PAL) at MIT has awarded funding to eight latest research studies to know how artificial intelligence innovations may be utilized in the fight against poverty through its latest Project AI Evidence.
The age of AI has brought wide-ranging optimism and skepticism about its effects on society. To understand AI’s full potential, Project AI Evidence (PAIE) will discover which AI solutions work and for whom, and scale only essentially the most effective, inclusive, and responsible solutions — while cutting down those who may potentially cause harm.
PAIE will generate evidence on what works by connecting governments, tech corporations, and nonprofits with world-class economists at MIT and across J-PAL’s global network to judge and improve AI solutions to entrenched social challenges.
The brand new initiative is prioritizing questions policymakers are already asking: Do AI-assisted teaching tools help all children learn? How can early-warning flood systems help people affected by natural disasters? Can machine learning algorithms help reduce deforestation within the Amazon? Can AI-powered chatbots help improve people’s health? In the approaching years, PAIE will run a series of funding competitions to ask proposals for evaluations of AI tools that address questions like these, and lots of more.
PAIE is financially supported by a grant from Google.org, philanthropic support from Community Jameel, a grant from Canada’s International Development Research Centre and UK International Development, and a collaboration agreement with Amazon Web Services. Through a grant from Eric and Wendy Schmidt, awarded by suggestion of Schmidt Sciences, the initiative will even study generative AI within 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 on this space, on Project AI Evidence. AI has great potential to profit all people, but we urgently need to check what works, what doesn’t, and why, if we’re to understand this potential.”
“Artificial intelligence holds extraordinary potential, but provided that the tools, knowledge, and power to shape it are accessible to all — that features contextually grounded research and evidence on what works and what doesn’t,” adds Maggie Gorman-Velez, vice chairman of strategy, regions, and policies at IDRC. “That’s the reason IDRC is proud to be supporting this latest evaluation work as a part of our ongoing commitment to the responsible scaling of proven protected, inclusive, and locally relevant AI innovations.”
J-PAL is uniquely positioned to assist understand AI’s effects on society: Since its inception in 2003, J-PAL’s network of researchers has led over 2,500 rigorous evaluations of social policies and programs around the globe. Through PAIE, J-PAL will bring together leading experts in AI technology, research, and social policy, in alignment with MIT president Sally Kornbluth’s give attention to generative AI as a strategic priority.
PAIE is chaired by Professor Joshua Blumenstock of the University of California at Berkeley; J-PAL Global Executive Director Iqbal Dhaliwal; and Professor David Yanagizawa-Drott of the University of Zurich.
Latest evaluations of urgent policy questions
The studies funded in PAIE’s first round of competition explore urgent questions in key sectors like education, health, climate, and economic opportunity.
How can AI be best in classrooms, helping each students and teachers?
Existing research shows that personalized learning is significant for college kids, but difficult to implement with limited resources. In Kenya, education social enterprise EIDU has developed an AI tool that helps teachers discover learning gaps and adapt their day by day lesson plans. In India, the nongovernmental organization (NGO) Pratham is developing an AI tool to extend the impact and scale of the evidence-informed Teaching on the Right Level approach. J-PAL researchers Daron Acemoglu, Iqbal Dhaliwal, and Francisco Gallego will work with each organizations to check the consequences and potential of those different use cases on teachers’ productivity and students’ learning.
Can AI tools reduce gender bias in schools?
Researchers are collaborating with Italy’s Ministry of Education to judge whether AI tools may also help close gender gaps in students’ performance by addressing teachers’ unconscious biases. J-PAL affiliates Michela Carlana and Will Dobbie, together with Francesca Miserocchi and Eleonora Patacchini, will study the impacts of two AI tools, one which helps teachers predict performance and a second that offers real-time feedback on the range of their decisions.
Can AI help profession counselors uncover more job opportunities?
In Kenya, researchers are evaluating if an AI tool can discover neglected skills and unlock employment opportunities, particularly for youth, women, and people without formal education. In collaboration with NGOs Swahilipot and Tabiya, Jasmin Baier and J-PAL researcher Christian Meyer will evaluate how the tool changes people’s job search strategies and employment. This study will make clear AI as a complement, relatively than a substitute, for human expertise in profession guidance.
Looking forward
As use of AI within the social sector evolves, these evaluations are a primary step in discovering effective, responsible solutions that can go the furthest in alleviating poverty and inequality.
J-PAL’s Dhaliwal notes, “J-PAL has an extended history of evaluating revolutionary technology and its ability to enhance people’s lives. While AI has incredible potential, we’d like to maximise its advantages and minimize possible harms. We’re grateful to our donors, sponsors, and collaborators for his or her catalytic support in launching PAIE, which can help us do exactly that by continuing to expand evidence on the impacts of AI innovations.”
J-PAL can be looking for latest collaborators who share its vision of discovering and scaling up real-world AI solutions. It goals to support more governments and social sector organizations that need to adopt AI responsibly, and can proceed to expand funding for brand spanking new evaluations and supply policy guidance based on the most recent research.
To learn more about Project AI Evidence, subscribe to J-PAL’s newsletter or contact paie@povertyactionlab.org.