Author: Scott Murray | Institute for Data, Systems, and Society<\/p>\n
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.<\/p>\n
At a unique MIT event convened by MIT\u2019s Technology and Policy Program<\/a> (TPP), a part of the Institute for Data, Systems, and Society<\/a> (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.<\/p>\n \u201cOne 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,\u201d says Becca Browder, a Policy Hackathon organizer and student in TPP. \u201cI think the event achieved that goal.\u201d<\/p>\n 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.<\/p>\n 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.<\/p>\n \u201cThe city is taking climate change very seriously,\u201d 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 \u201cgood give-and-take\u201d to be had from partnering with local universities. \u201cThe 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.\u201d<\/p>\n 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. \u201cThe interaction with the challenge sponsor helped me think about how to better communicate my research findings with policymakers in the future,\u201d says Qiu, whose team GAMMDRYL also included TPP alumnus Arthur Yip SM \u201914. GAMMDRYL won the climate challenge with a proposal recommending the city team up with a citizen science initiative that crowdsources rainfall data.<\/p>\n \u201cI learned that it is often useful to help decision-makers to understand their data better,\u201d Qiu says.<\/p>\n 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.<\/p>\n \u201cBy using creative visualization techniques, they simulated how their policy suggestions can result in an overall improvement in service efficiency,\u201d Abdelfattah says of the winning team\u2019s proposal. \u201cTheir 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.\u201d<\/p>\n 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” \u2014 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.<\/p>\n The urban planning challenge, sponsored by the City of Boston\u2019s Department of Innovation and Technology, tasked participants with assessing the impact of AirBnB on neighborhood economies and Boston\u2019s affordable housing crisis, using the city\u2019s short-term rental data. The future of work challenge, posed by the MIT Initiative on the Digital Economy<\/a> (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.<\/p>\n This was the third MIT Policy Hackathon: an inaugural hackathon<\/a> was held in spring 2018, and another was organized for Boston Hubweek<\/a> in fall 2018. Students hope to make it a fixture of the program. \u201cIDSS and TPP work on how policy and society interact with science and technology, and how we can use data to enhance policy,\u201d Browder says. \u201cThese are also main goals of the hackathon, so there is strong strategic alignment between the event and the host organizations.\u201d<\/p>\n TPP director Noelle Selin agrees. \u201cTPP and IDSS are educating scientists, engineers, and leaders who can use the tools of data science as well as speak the language of policy,\u201d says Selin, a professor in IDSS and Earth, Atmospheric, and Planetary Sciences. \u201cWe need this type of interdisciplinary thinking to tackle the most pressing challenges facing society.\u201d<\/p>\n<\/div>\n Go to Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"