The vast amount of data generated daily across society is widely touted as a game-changer for research, technological innovation, and even policy making. But “big data will not change the world unless it’s collected and synthesized into tools that have a public benefit,” said Sarah Williams, an assistant professor of urban planning at MIT, in a panel discussion on the future of cities, at a conference convened last week by the Institute for Data, Systems and Society (IDSS).
The ways in which data can be used to produce change was a common theme among speakers at the IDSS celebration, which focused on how the deluge of data being gathered in the big data era can be used to tackle society’s most pressing challenges. The two-day event brought together experts from a variety of fields, including energy, health care, finance, urban planning, engineering, computer science, and political science. The lineup even featured one speaker who, MIT President L. Rafael Reif joked, “knows who will win the election in November.” That would be Nate Silver, founder and editor-in-chief of the political poll analysis website FiveThirtyEight.
The event participants had much to celebrate. Launched in July 2015, IDSS accomplished a number of milestones in its first year, including the introduction of a new undergraduate minor in statistics and data science, a new doctoral program in social engineering and systems, a professional education course in data science, and a center focused on statistics and data sciences.
The all-star speaker lineup at the event was a testament to IDSS’s ability to bring together “data scientists and systems engineers with experts in economics, finance, urban planning, energy, public health, political science, social networks, and more,” Reif said. He added that IDSS is “a unit that can magnify individual talents through collaborations, a unit that aspires to generate groundbreaking ways to understand society’s most difficult problems and lead us to badly needed solutions.”
At IDSS, researchers are focused on taking “an analytical, data-driven approach to problems,” said Munther Dahleh, director of IDSS and the William A. Coolidge Professor of Electrical Engineering and Computer Science. “We collect the data, we develop the models, and from these models we develop insights, policies, and decisions.”
The event opened with a panel discussion focused on the future of voting and elections. Charles Stewart, the Kenan Sahin Distinguished Professor in the MIT Department of Political Science, set the stage by noting the increasing role of data in the political process. Stewart, who co-directs the Caltech/MIT Voting Technology Project, described how data is collected from voter registration files, campaigns and politicians, public opinion polls, campaign contribution records, and more. He added that many citizens might be surprised to learn that the identity of anyone who has registered to vote is public record, while the data and computer code in voting machines is not always available to the public or election officials.
“Interest in election data is not simply about choosing the best candidates or policies,” Stewart explained. “It’s also about who controls the data and how it is used.”
MIT alumna Kassia DeVorsey ’04, who worked for the Obama campaign and is now the chief analytics officer at the Messina Group and founder of Minerva Insights, explained that while previously only presidential campaigns invested in gathering and analyzing data, nowadays, “if you’re running for mayor in a small town, you’re thinking strategically about ‘how can I use data to best run my campaign.’” She noted that the voter-information data compiled by the Obama campaign was the team’s most valuable resource in trying to address and influence the electorate.