It is fairly common in public discourse for someone to announce, “I brought data to this discussion,” thus casting their own conclusions as empirical and rational. It is less common to ask: Where did the data come from? How was it collected? Why is there data about some things but not others?
MIT Associate Professor Catherine D’Ignazio SM ’14 does ask those kinds of questions. A scholar with a far-reaching portfolio of work, she has a strong interest in applying data to social issues — often to help the disempowered gain access to numbers, and to help provide a fuller picture of civic problems we are trying to address.
“If we want an educated citizenry to participate in our democracy with data and data-driven arguments, we should think about how we design our data infrastructures to support that,” says D’Ignazio.
Take, for example, the problem of feminicide, the killing of women as a result of gender-based violence. Activists throughout Latin America started tabulating cases about it and building databases that were often more thorough than official state records. D’Ignazio has observed the issue and, with colleagues, co-designed AI tools with human rights defenders to support their monitoring work.
In turn, D’Ignazio’s 2024 book on the subject, “Counting Feminicide,” chronicled the entire process and has helped bring the issue to a new audience. Where there was once a data void, now there are substantial databases helping people recognize the reality of the problem on multiple continents, thanks to innovative citizens. The book outlines how grassroots data science and citizen data activism are generally rising forms of civic participation.
“When we talk about innovation, I think: Innovation for whom? And by whom? For me those are key questions,” says D’Ignazio, a faculty member in MIT’s Department of Urban Studies and Planning and director of MIT’s Data and Feminism Lab. For her research and teaching, D’Ignazio was awarded tenure earlier this year.
Out of the grassroots
D’Ignazio has long cultivated an interest in data science, digital design, and global matters. She received her BA in international relations from Tufts University, then became a software developer in the private sector. Returning to her studies, she earned an MFA from the Maine College of Art, and then an MS from the MIT Media Lab, which helped her synthesize her intellectual outlook.
“The Media Lab for me was the place where I was able to converge all those interests I had been thinking about,” D’Ignazio says. “How can we have more creative applications of software and databases? How can we have more socially just applications of AI? And how do we organize our technology and resources for a more participatory and equitable future for all of us?”
To be sure, D’Ignazio did not spend all her time at the Media Lab examining database issues. In 2014 and 2018 she co-organized a feminist hackathon called “Make the Breast Pump Not Suck,” in which hundreds of participants developed innovative technologies and policies to address postpartum health and infant feeding. Still, much of her work has focused on data architecture, data visualization, and the analysis of the relationship between data production and society.
D’Ignazio started her teaching career as a lecturer in the Digital + Media graduate program at Rhode Island School of Design, then became an assistant professor of data visualization and civic media in Emerson College’s journalism department. She joined the MIT faculty as an assistant professor in 2020.
D’Ignazio’s first book, “Data Feminism,” co-authored with Lauren Klein of Emory University and published in 2020, took a wide-ranging look at many ways that everyday data reflects the civic society that it emerges from. The reported rates of sexual assault on college campuses, for instance, could be deceptive because the institutions with the lowest rates might be those with the most problematic reporting climates for survivors.
D’Ignazio’s global outlook — she has lived in France, Argentina, and Uruguay, among other places — has helped her understand the regional and national politics behind these issues, as well as the challenges citizen watchdogs can face in terms of data collection. No one should think such projects are easy.
“So much grassroots labor goes into the production of data,” D’Ignazio says. “One thing that’s really interesting is the huge amount of work it takes on the part of grassroots or citizen science groups to actually make data useful. And oftentimes that’s because of institutional data structures that are really lacking.”
Letting students thrive
Overall, the issue of who participates in data science is, as D’Ignazio and Klein have written, “the elephant in the server room.” As an associate professor, D’Ignazio works to encourage all students to think openly about data science and its social underpinnings. In turn, she also draws inspiration from productive students.
“Part of the joy and privilege of being a professor is you have students who take you in directions you would not have gone in yourself,” D’Ignazio says.
One of D’Ignazio’s graduate students at the moment, Wonyoung So, has been digging into housing data issues. It is fairly simple for property owners to access information about tenants, but less so the other way around; this makes it hard to find out if landlords have abnormally high eviction rates, for example.
“There are all of these technologies that allow landlords to get almost every piece of information about tenants, but there are so few technologies allowing tenants to know anything about landlords,” D’Ignazio explains. The availability of data “often ends up reproducing asymmetries that already exist in the world.” Moreover, even where housing data is published by jurisdictions, she notes, “it’s incredibly fragmented, and published poorly and differently, from place to place. There are massive inequities even in open data.”
In this way housing seems like yet another area where new ideas and better data structures can be developed. It is not a topic she would have focused on by herself, but D’Ignazio also views herself as a facilitator of innovative work by others. There is much progress to be made in the application of data science to society, often by developing new tools for people to use.
“I’m interested in thinking about how information and technology can challenge structural inequalities,” D’Ignazio says. “The question is: How do we design technologies that help communities build power?”
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