As modern societal systems grow in complexity and interconnectedness, they generate unprecedented volumes of data that can unlock transformative insights. For policymakers tackling major global challenges, this data represents a significant opportunity—provided they possess the tools to analyze it effectively and leverage it for informed governance decisions.
At an innovative event hosted by MIT's Technology and Policy Program (TPP), part of the Institute for Data, Systems, and Society (IDSS), multidisciplinary teams collaborated to analyze complex datasets and develop data-driven governance artificial intelligence solutions to real-world problems submitted by academic institutions and municipal governments. The student-led MIT Policy Hackathon brought together data analysts, engineers, scientists, domain experts, and policy specialists to devise creative, AI-augmented approaches to pressing societal issues.
"One of our primary objectives is demonstrating how integrating technology and policy can craft powerful solutions to critical societal problems," explains Becca Browder, a Policy Hackathon organizer and TPP student. "I believe this year's event successfully achieved that mission."
Over 48 intensive hours, hackathon teams tackled one of five challenges spanning climate resilience, healthcare innovation, AI ethics applications, urban development, and workforce transformation. The culmination featured a proposal pitch session to a distinguished panel of judges representing academia, government, and industry sectors.
In the climate challenge, sponsored by the City of Boston, teams analyzed precipitation patterns to help the municipality prepare for increased flooding risks associated with climate change.
"The city is treating climate adaptation as a critical priority," notes Charlie Jewell, director of planning and sustainability for the Boston Water and Sewer Commission. After mentoring and evaluating the climate challenge submissions, Jewell highlighted the value of collaborating with local universities: "The organizers and participants delivered exceptional work. I gained valuable insights on alternative approaches to analyzing our rainfall data. They also clearly articulated what additional data they needed and potential acquisition methods."
Hackathon participant Minghao Qiu, an IDSS doctoral student in the Social and Engineering Systems program, found direct stakeholder engagement particularly beneficial. "Interacting with the challenge sponsor helped me refine my approach to communicating research findings to policymakers," says Qiu, whose team GAMMDRYL included TPP alumnus Arthur Yip SM '14. GAMMDRYL secured victory in the climate challenge with a proposal recommending the city partner with a citizen science initiative to crowdsource rainfall data.
"I discovered that helping decision-makers better understand their data is often incredibly valuable," Qiu reflects.
The hackathon's grand prize went to Dream ER, a team addressing the healthcare challenge. Sponsored by Harvard School of Public Health graduate student Ahmed Mahmoud Abdelfattah, this challenge focused on optimizing emergency room operations through analysis of patient flow and outcome data.
"Through innovative visualization techniques, they demonstrated how their policy recommendations could enhance overall service efficiency," Abdelfattah remarks about the winning proposal. "Their approach was also highly transferable, meaning the methods they developed for data analysis and change simulation could be applied to other healthcare facilities and delivery contexts."
For the AI ethics challenge, sponsored by Harvard's Berkman Klein Center for Internet and Society, teams developed resources—including visualization tools—to help non-technical policy advocates understand various interpretations of "algorithmic fairness," particularly concerning criminal justice risk-assessment tools. Participants accessed data shared by journalists who evaluated COMPAS, a widely utilized recidivism risk scoring system.
The urban planning challenge, sponsored by Boston's Department of Innovation and Technology, tasked participants with evaluating AirBnB's impact on neighborhood economies and the city's affordable housing crisis using municipal short-term rental data. Meanwhile, the future of work challenge, presented by the MIT Initiative on the Digital Economy (IDE), invited broad exploration of machine learning's potential to automate various tasks. Using a dataset of work activities compiled by MIT and Carnegie Mellon researchers, this challenge sought policy proposals to predict and prepare for machine learning automation's impact on industries and workers.
Marking the third installment of the MIT Policy Hackathon, this event follows the inaugural hackathon in spring 2018 and a subsequent edition organized for Boston Hubweek in fall 2018. Students aim to establish it as a program staple. "IDSS and TPP focus on the intersection of policy, society, science, and technology—and how we can enhance policy through data," Browder explains. "These principles also represent the hackathon's core objectives, creating strong strategic alignment between the event and its host organizations."
TPP director Noelle Selin concurs. "TPP and IDSS are developing scientists, engineers, and leaders who can wield data science tools while communicating effectively in policy language," says Selin, a professor in IDSS and Earth, Atmospheric, and Planetary Sciences. "This interdisciplinary thinking capacity is precisely what we need to address society's most pressing challenges."
