Along with teaching Metrics and Data Visualization at DSI, Wenfei Xu is urban planner, data scientist, and designer whose research uses data-driven methods to understand the geographies of urban inequality. She has worked at organizations such as CARTO, the Civic Data Design Lab, Stamen Design and Senseable Cities Lab at MIT, and is currently pursuing a Ph.D. in Urban Planning at Columbia GSAPP.
What is design for social innovation?
More and more, we recognize the social inequities historically and presently embedded in our institutional practices, both in public and private sectors. What’s so interesting for me is that these issues are simultaneously large and personal. For instance, behind the measurable impact of the legacy of racialized mortgage lending (the topic of my primary research) are personal stories of immeasurable loss. How do we reconcile this plurality of perspectives using diverse ways of knowing?
I think this is where designers come in. When I think about the role of a designer, I don’t think about someone who is just highly capable at colors, graphics, or communication. Designers are people who are capable of bringing together different types of ideas and different ways of seeing the world to propose something coherent and original. And yes, they do also have the great ability to translate it back to the world in a way that the intended audience can understand! Designers are great interdisciplinarians, and to have a set of designers thinking about issues of socio-political importance is really fortunate for the world.
What would you like to say to prospective students about the program & the course you teach?
Everyone comes to the program with great ideas for creating a positive influence on the world. I believe the goal of the program and my class in particular is to help students instrumentalize those intentions through practice. I teach the Data Metrics and Visualization sequences, in which we emphasize “practice” because my students will ultimately have very tangible, real-world questions to address. An example of this is understanding the impact of gentrification in a neighborhood. It’s a messy topic with different ways of understanding what it means, different ways to measure it, and often the data for the question you want to ask isn’t available. What do we do? We think critically about our research question and propose designs that can help us triangulate towards an answer. We try to think with kindness and from multiple perspectives, but with an agility of methods.
Can you talk a little bit about your background and the work you do outside of DSI?
My background is perhaps best described as an interdisciplinary hodge-podge. I’m an architect, economist, data scientist (whatever that means!) by training, who’s somehow found her way into an urban planning doctoral program. My research is on the discriminatory legacies of the American mortgage system, gentrification, and housing policy more generally. On a day to day basis, this means I read a lot, code a lot, and am sad a lot about how recent and ongoing our housing system has failed those most in need. Sometimes, I also try to make maps and web tools to illustrate my research.
Can you talk in more detail about a project that you are working on?
Sure. My dissertation project looks at the legacies of institutionalized redlining in the US, as enabled by the Federal Housing Administration. Back in the 1930s and 40s, when we were creating the American mortgage market as we know it now, the US government decided that they wanted to support homeownership through insuring mortgages of new homebuyers. However, these new loans were mostly for white home buyers to move to the suburbs, while many areas in the city were excluded from access to any credit. Not surprisingly, these areas were disproportionately minority. And of course, homeownership is really important for building wealth and improving one’s socioeconomic outcomes, it turns out. Therefore, when we trace the current racial wealth gap, we can see that a lot of it is rooted in disparate homeownership levels. My research is then to understand not just the magnitude of this historical mortgage discrimination, but also understand how and what kinds of long-term, path-dependent impacts it may have created. For instance, one legacy is that these inner-city neighborhoods saw a lot of disinvestment that may have created the conditions for later gentrification. Wait for the paper to find out! (You might have to wait a while because academic publishing is slow.)
If you could give one piece of advice to students starting DSI, what would it be?
I think there is always some ambiguity (but also freedom) in a newer field like Design for Social Innovation in terms of what you’re supposed to do, how you’re supposed to do it, and whether you’re headed in the right direction. We might try a lot of things that don’t seem to work out. Instead, I’d offer that any research or work is an iterative learning process where (trust me) you eventually get to a proposal or outcome that feels right. Phew, now that you know you’ll be ok in the end, you’ve been given this wonderful space to explore and establish new precedents for interdisciplinary thinking. How lucky!