It is kind of common in public discourse for somebody to announce, “I even have brought data into this discussion,” thereby presenting their very own conclusions as empirical and rational. Less incessantly asked is: Where does the information come from? How was it collected? Why is there data on some things but not others?
MIT Associate Professor Catherine D'Ignazio SM '14 asks such questions. As a scholar with a wide-ranging portfolio of labor, she has a powerful interest in applying data to social problems – often to make numbers more accessible to the disadvantaged and to supply a more comprehensive picture of the civic issues we seek to deal with.
“If we wish an informed citizenry to take part in our democracy with data and data-driven arguments, we must always take into consideration how we design our data infrastructures to support this,” says D'Ignazio.
Take, for instance, the issue of femicide, the killing of ladies consequently of gender-based violence. Activists across Latin America began tabulating cases on the problem and constructing databases that were often more thorough than official government records. D'Ignazio has been monitoring the issue and, together with colleagues, has been developing AI tools with human rights defenders to support their monitoring work.
D'Ignazio's 2024 book Counting Feminicide, in turn, chronicled your complete process and has helped bring the subject to latest audiences. Where there was once an information gap, due to revolutionary residents there are actually extensive databases helping people see the truth of the issue across multiple continents. The book describes how grassroots data science and citizen data activism generally are increasing types of citizen participation.
“When we discuss innovation, I feel: Innovation for whom? And from whom? For me, these are key questions,” says D’Ignazio, a college 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 yr.
Get out of the bottom
D'Ignazio has a long-standing interest in data science, digital design and global affairs. She received her BA in diplomacy from Tufts University after which became a software developer within the private sector. Returning to her studies, she earned an MFA from Maine College of Art after which an MS from MIT Media Lab, which helped her make clear her mental perspective.
“For me, the Media Lab was the place where I could bring all of my interests together,” says D'Ignazio. “How can we use software and databases more creatively? How can we use AI in a more socially just way? And how can we organize our technology and resources for a more participatory and equitable future for all of us?”
Of course, D'Ignazio didn't spend all of her time within the Media Lab investigating database problems. In 2014 and 2018, she co-organized a feminist hackathon called “Make the Breast Pump Not Suck,” where lots of of participants developed revolutionary technologies and policies for postpartum health and infant feeding. Nevertheless, much of her work focused on data architecture, data visualization, and analyzing the connection between data production and society.
D'Ignazio began her teaching profession as an instructor within the Digital + Media graduate program at Rhode Island School of Design after which became an assistant professor of knowledge visualization and citizen media within the journalism department at Emerson College. She has been an assistant professor on the MIT faculty since 2020.
D'Ignazio's first book, Data Feminism, co-authored with Emory University's Lauren Klein and published in 2020, took a comprehensive have a look at the numerous ways on a regular basis data reflects the civil society from which it emerges. For example, reported rates of sexual assault on college campuses could also be misleading since the institutions with the bottom rates may be those with probably the most problematic reporting climates for survivors.
D'Ignazio's global perspective—she has lived in France, Argentina, and Uruguay, amongst other places—has helped her understand the regional and national politics behind these issues, in addition to the challenges that citizen watchdogs can face in data collection. Nobody should think that such projects are easy.
“So much groundwork goes into producing data,” says D’Ignazio. “One thing that's really interesting is the tremendous amount of labor that's required on the a part of grassroots or citizen science groups to truly make data useful. And often that’s as a result of the institutional data structures which are really missing.”
Give students the chance to develop
Overall, the query of who’s involved in data science is, as D'Ignazio and Klein have written, “the elephant within the server room.” As an associate professor, D'Ignazio is committed to encouraging all students to think openly about data science and its societal underpinnings. In return, she can also be inspired by productive students.
“Part of the enjoyment and privilege of being a professor is having students who take you in directions you’ll never have gone yourself,” says D'Ignazio.
Wonyoung So, considered one of D'Ignazio's graduate students, is currently working on housing data issues. It is kind of easy for property owners to access details about tenants, but the opposite way around is less easy; This makes it difficult, for instance, to seek out out whether landlords have unusually high eviction rates.
“There are all these technologies that allow landlords to get almost any details about tenants, but there are so few technologies that allow tenants to learn about landlords,” D'Ignazio explains. The availability of knowledge “often reproduces asymmetries that exist already on this planet.” Additionally, she notes that even where housing data is published by jurisdiction, “the information is incredibly fragmented and published poorly and otherwise from place to position . “Even with open data, there are massive inequalities.”
In this manner, housing appears to be one other area where latest ideas and higher data structures may be developed. It's not a subject she would have focused on herself, but D'Ignazio also sees herself as a facilitator of revolutionary work by others. There are great strides to be made in applying data science to society, often through the event of recent tools available to people.
“I'm thinking about fascinated about how information and technology can address structural inequalities,” says D'Ignazio. “The query is: How can we develop technologies that help communities construct energy?”
