Every day, myriad organizations and governments digitally collect data about our finances, health, and behavior. Recognizing the potential of such vast quantities of data as a tool to fight poverty, researchers at the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT recently launched the Innovations in Data and Experiments for Action Initiative (IDEA). IDEA was launched with startup support from the Alfred P. Sloan Foundation.

Since its founding in 2003, J-PAL has worked to reduce poverty by ensuring that policy is informed by scientific evidence. J-PAL affiliates typically run randomized evaluations by collecting primary data on the effectiveness of social programs. IDEA builds on the success of this strategy by partnering with governments, businesses, and nonprofits to utilize existing administrative data in experiments, and will use the results to scale up successful programs and strategically phase out those that aren’t achieving their desired goals.

“Using these data sets in creative and innovative ways to evaluate programs and therefore improve outcomes is a vital step toward making significant progress in the fight against poverty worldwide,“ says Iqbal Dhaliwal, J-PAL’s global executive director and a co-chair of IDEA. Dhaliwal notes that using existing data reduces research costs and frees up resources to serve many more people.

Already, J-PAL has worked effectively with administrative data from city and state governments in the United States and abroad. In Philadelphia, J-PAL-affiliated researchers used municipal data to track the impacts of a summer jobs program on crime, employment, and educational outcomes in low-income neighborhoods. In Rio de Janeiro, data on crime, police presence, and environmental factors informed an improved system for effective police response, helping to make communities safer.

To keep this momentum going, IDEA is planning for a conference that brings together researchers, data providers, and practitioners for collaborative discussions, presentations on IDEA’s ongoing work, and to kick off creating a handbook on best practices for using administrative data for research and evidence-based policy. IDEA is also exploring opportunities for collaboration with various other centers at MIT that are interested in working with big data, artificial intelligence, and machine learning, including the MIT Stephen A. Schwarzman College of Computing.

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