MIT Policy Hackathon connects data-driven problem solvers
As the size, complexity, and interconnection of societal systems increase, these systems generate huge amounts of data that can lead to new insights. These data create an opportunity for policymakers aiming to address major societal challenges, provided they have the tools to understand the data and use them for better decision-making.
At a unique MIT event convened by MIT’s Technology and Policy Program (TPP), a part of the Institute for Data, Systems, and Society (IDSS), interdisciplinary teams analyzed data sets and created policy proposals to real challenges submitted by academic groups and local government. The student-run MIT Policy Hackathon gathered data analysts, engineers, scientists, domain experts, and policy specialists to look for creative, data-driven solutions addressing major societal issues.
“One of the goals of the hackathon is to show others the power of using technology and policy together to craft solutions to important societal problems,” says Becca Browder, a Policy Hackathon organizer and student in TPP. “I think the event achieved that goal.”
The hackathon teams worked over 48 hours on one of five challenges in the areas of climate, health, artificial intelligence and ethics, urban planning, and the future of work. The hackathon ended in a proposal pitch session to a panel of judges from academia, government, and industry.
In the climate challenge, sponsored by the City of Boston, teams examined precipitation data to help the city prepare for increased flooding due to climate change.
“The city is taking climate change very seriously,” says Charlie Jewell, director of planning and sustainability for the Boston Water and Sewer Commission. After mentoring and judging the climate challenge, Jewell said there was a “good give-and-take” to be had from partnering with local universities. “The organizers and participants all did such an unbelievable job. I got some great ideas from participants for looking at our rainfall data in different ways. They also showed what kind of data they needed and how we could get it.”
Hackathon participant Minghao Qiu, a student at IDSS in the Social and Engineering Systems doctoral program, also found the opportunity to work directly with stakeholders useful. “The interaction with the challenge sponsor helped me think about how to better communicate my research findings with policymakers in the future,” says Qiu, whose team GAMMDRYL also included TPP alumnus Arthur Yip SM ’14. GAMMDRYL won the climate challenge with a proposal recommending the city team up with a citizen science initiative that crowdsources rainfall data.
“I learned that it is often useful to help decision-makers to understand their data better,” Qiu says.
The overall winner of the hackathon was a team called Dream ER, who worked on the health challenge. This challenge, sponsored by Harvard School of Public Health graduate student Ahmed Mahmoud Abdelfattah, asked for ways to optimize emergency rooms by studying patient traffic and outcome data.
“By using creative visualization techniques, they simulated how their policy suggestions can result in an overall improvement in service efficiency,” Abdelfattah says of the winning team’s proposal. “Their proposal was also quite generalizable, meaning that those same methods they used to examine the data and simulate changes can be applied to other hospitals and other care settings.”
For the AI and ethics challenge, sponsored by the Berkman Klein Center for Internet and Society at Harvard University, teams worked to develop a resource, such as a visualization tool, to help nontechnical policy advocates understand different definitions of "algorithmic fairness" — especially in the context of criminal justice risk-assessment tools. Participants had access to data shared by journalists who evaluated COMPAS, a widely-used recidivism risk scoring tool.
The urban planning challenge, sponsored by the City of Boston’s Department of Innovation and Technology, tasked participants with assessing the impact of AirBnB on neighborhood economies and Boston’s affordable housing crisis, using the city’s short-term rental data. The future of work challenge, posed by the MIT Initiative on the Digital Economy (IDE), asked for a broad exploration of the potential for machine learning to automate tasks. Using a data set of work activities put together by researchers at MIT and Carnegie Mellon University, this challenge asked for policy proposals that help predict and prepare for the impact of machine learning automation on industries and workers.
This was the third MIT Policy Hackathon: an inaugural hackathon was held in spring 2018, and another was organized for Boston Hubweek in fall 2018. Students hope to make it a fixture of the program. “IDSS and TPP work on how policy and society interact with science and technology, and how we can use data to enhance policy,” Browder says. “These are also main goals of the hackathon, so there is strong strategic alignment between the event and the host organizations.”
TPP director Noelle Selin agrees. “TPP and IDSS are educating scientists, engineers, and leaders who can use the tools of data science as well as speak the language of policy,” says Selin, a professor in IDSS and Earth, Atmospheric, and Planetary Sciences. “We need this type of interdisciplinary thinking to tackle the most pressing challenges facing society.”