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MIT staff blogger Chris Peterson SM '13

Prof. Catherine D’Ignazio on Urban Science for Public Good by Chris Peterson SM '13

One of the strange things about being 10,000 years old is that, while I’ve been tooling away judging teens, some of my classmates/labmates from when I was in my master’s program have gone on to build careers in academia. Some are even professors! And, as of this term, one of them, Catherine D’Ignazio, is even a professor at MIT! Oh god I’m old. 

Earlier today, Catherine circulated an announcement (and syllabus) for a new class she is teaching this term that I thought sounded totally rad:

11.S01 – 3 credits
Urban Science for Public Good: Gender and Racial Equity in Artificial Intelligence
Meets Mon 1:30 – 3pm
First-year Discovery class

Gender and racial equity are often central goals of urban planning. But what are gender and race? What happens when we start to measure and model these dimensions of identity? Conversely, what happens when we ignore gender and race in urban computation? This course introduces students to some of the leading scientists, theorists and practitioners who are working to challenge bias in AI and to use data and computation to work towards gender and racial equity in cities. Along the way, we will reflect on our own identities and learn critical concepts to navigate gender and race from fields such as Urban Planning, Women’s & Gender Studies, Critical Race Studies, and Computer Science.

I know from reading applications that a lot of prospective MIT students are interested in how to use/change technology to make the world less awful, and Catherine is one of the central faculty members involved in building out a new major (and affiliated lab) where that is a central object of concern contemporaneous with the new College of Computing. So I thought I’d ask her a few questions over email about who she is, what she’s doing, and how people at/aspiring to MIT can stay informed.
Who are you? 
I’m a new faculty at MIT in the Department of Urban Studies and Planning. My somewhat untraditional background is in software development, art/design and civic media. I graduated from the Media Lab/Center for Civic Media back in 2014 and have been thinking about how we can use data and technology for social good for some time. I also have a new book coming out called “Data Feminism” where Lauren Klein and I try to outline what a feminist approach to data science looks like. Spoiler alert: it’s not (only) about women and not (only) for women because it takes more than one gender to build a just and fair world. 
How would you describe what and how you hope to teach (in this class and generally at MIT)?
I like building things and making things, and I’m very excited to be back at MIT where so many incredible things are built and made. I’m also thrilled to be part of DUSP’s new urban science major (Course 11-6) that we are doing in collaboration with Course 6. At the same time, I embrace ideas of participatory design and co-design where you involve communities in the making process. I see this as essential if we are going to build technologies that truly serve the public. So collaboration and participation is a part of all of the classes, where we often work with different outside groups. For example, in my spring course called the Crowd Sourced City we are collaborating with the Cambridge Historical Commission, Boston Public Library and the Geochicas, a feminist activist collective out of Latin America. How do we use data and technology to create more equitable, livable and healthy cities? That’s a question we have to answer through building technology AND building relationships.
What are three books, papers, or other media that high school students interested in this field should read?
OK I have to say Data Feminism. Other great starting points are Cathy O’Neil’s Weapons of Math Destruction, ProPublica’s story on Machine Bias, Joy Buolamwini’s video “AI, Ain’t I a Woman?“. These start to point out some of the places where we are reproducing structural bias in data and AI, which is a huge risk for those of us who aspire to “do good” with data science. They also point towards the values, methods and tools we can adopt for us to start to do better.
Anything else that you want to say?
I’m starting a new lab called the Data + Feminism Lab so I would welcome folks to our public mailing list to stay up to date on guest speakers, job opportunities and other activities that we’ll post periodically. And just generally, feel free to get in touch with me and tell me about any interesting things happening around the community. I feel like I continue to discover new groups and spaces every day. And I need to learn the tunnels…
Hope you found this compelling and check out the syllabus and recommended readings so you can follow along at home!