I would push MIT to always remember that it has a commitment to local, as well as global, collaborations. By this, I mean to emphasize the need to build technologies that serve a public, and therefore have an applied nature for a given community.
As a software developer and a database programmer for 15 years, I've always had a deep interest in building public-interest technologies. I also fundamentally believe it is possible to use technology in the service of justice, even when those technologies were developed for a military context or have been used to maintain systems of racial domination. Technologies emerge and have become innovative with imperfect historic roots. And yet, this past purpose does not need to determine what the future is for a given technology. Rather, I think technologies are and can be shaped by active political processes. I'm also increasingly interested in how we can use AI and machine learning, specifically in the realm of human rights, and even more specifically in the realm of data activism. I think a lot right now about grassroots data practices. Folks based in various kinds of grassroots communities who are doing their own data science, who are working with data in, like highly creative ways and instead of using AI and machine learning to make Jeff Bezos more money, how might we use those same technologies to build power for activists who are working for gender and racial justice.
A big part of my engagement with these interests are channeled into my work as director of the Data + Feminism Lab (D+F Lab). The lab works with a broad array of technologies and to think about and to operationalize how we use data and computation to build greater gender and racial justice. Through this combination of technology and a justice-driven mission, the D+F Lab considers how we work with data and computation to reach gender and racial justice goals, and with what technologies can this be achieved. One of the goals of the D+F lab is to think about ways we can model better technology in the service of social justice, not only in terms of products and outcomes, but also in the process of making technologies. This can be achieved by thinking about participatory process and who is involved in actively shaping the future of technologies and who they serve. Within the lab, we work with a whole variety of different technologies, including web applications such as small interactive websites or small applications, and one larger, ongoing, deeply participatory project called Data Against Feminicide. In this project, the D+F team interviews data activists across a transnational network of over 180 groups predominantly located across Latin America which produce data about feminicide –gender related violence against women and girls – as well as community health in their respective contexts. Through these interviews, we ask what kind of digital tools could better support their work in order to ultimately develop an AI/ML recommendation system, much like Google Alerts. This tool uses machine learning through an open-source tool called Media Cloud to catalog potentially relevant articles into a database for organizations to use while limiting individual exposure to brutal, often graphic accounts of violence against women recorded in local press and news articles.
The question I always have about public interest is which “public,” there are many publics and so which public are we talking about? I think the work that I'm most interested in doing, which will probably show up repeatedly in these projects, is one which incorporates the voices, the creativity, and the knowledge of people that are typically excluded from public processes. This includes grassroots voices who are deep experts in their community and their contexts, but who are not at the center of debates around ethics and AI, yet they have an important role to play in the shaping of technology. I think that for me [public interest technology] is a kind of commitment, and part of that vision includes how do we create technology that serves interests other than wealth extraction? This also means that as researchers, we commit to working with people that are excluded from these processes of expertise and technology development. A real commitment to broadening the conversation around technology requires both acknowledging and including the voices not currently at the table, especially for conversations about technology and policy in this country. If we want to serve the public interest, we need to collaborate. We need to build relationships with those folks who are not present in those boardrooms, in congressional testimonies, in funding circles, and other spaces of exclusionary power.
My understanding of social obligation and the public interest is based in my experience in art school, where I learned through forming art collectives and collaborations to embrace pluralism and the feminist idea that we create strength and knowledge production by bringing many perspectives to the table. My work then and my work today is strengthened by dialogue and engagement with individuals and groups in my local community in the Boston area, as well as internationally with activists, artists, students, and colleagues in academia. In my own work, I have cultivated a commitment to local and global collaborations.
Thinking more broadly, I would push MIT to always remember that it has a commitment to local, as well as global, collaborations. By this, I mean to emphasize the need to build technologies that serve a public, and therefore have an applied nature for a given community. From there, I would also highlight the need to develop tools with attention toward maintenance and scaling of actual public technologies to carry them into the future and for new forms of use because they are increasingly a matter of public interest, like WhatsApp or Google Docs, to create what Ethan Zuckerman terms “Digital Public Infrastructure.” Thinking through how we scale public interest technologies and how we move from a research and prototype model, which I would say that's very much where academia is now. For example, as a field, human computer interaction is incentivized to build novel little doodads and then throw them in the trash—this process has been called prototype proliferation, and it is basically the current model. The challenge we currently face for public interest technology is not only a technical question, but also a question of maintenance and sustainability—how do we build, scale and maintain digital technologies in the public interest?
Catherine D’Ignazio is an Associate Professor of Urban Science and Planning in the Department of Urban Studies and Planning. She is the director of the Data + Feminism lab. D'Ignazio is a scholar, artist/designer and hacker mama who focuses on feminist technology, data literacy and civic engagement. She has run reproductive justice hackathons (like the Make the Breast Pump Not Suck Hackathon), designed global news recommendation systems, created talking and tweeting water quality sculptures, and led walking data visualizations to envision the future of sea level rise. With Rahul Bhargava, she built the platform Databasic.io, a suite of tools and activities to introduce newcomers to data science. Her 2020 book from MIT Press, Data Feminism, co-authored with Lauren Klein, charts a course for more ethical and empowering data science practices. D'Ignazio's second book, Counting Feminicide: Data Feminism in Action (MIT Press 2024), highlights how mainstream data science can learn a lot from the care and memory work of grassroots feminist activists across the Americas. Her research at the intersection of technology, design & social justice has been published in FAccT, the ACM Conference on Fairness, Accountability, and Transparency, the Journal of Community Informatics, and the proceedings of Human Factors in Computing Systems (ACM SIGCHI). Her art and design projects have won awards from the Tanne Foundation, Turbulence.org and the Knight Foundation and exhibited at the Venice Biennial and the ICA Boston.
