Seeing Gentrification

San Francisco is gentrifying. The Anti-Eviction Mapping Project’s message could be communicated in so many words. Instead, the project uses a chaotic, disparate collection of images, links, data, audio recordings, maps, and written narratives to digitally visualize San Francisco’s gentrification. The project’s approach to data visualization is one that leads with distortion. As a user, I was disoriented immediately upon entering the site. I didn’t know where to click first, where to look first, or what the site wanted me to do or understand. That first impression planted a seed of antagonism that remained with me for the duration of my interaction with the project.

But I trudged on, clicking more or less randomly through the maps, the reports, the narratives, the statistics, the visuals. Slowly I got the picture. Tech companies are moving to San Francisco and driving up real-estate prices, and lower-income, long-time San Francisco residents are being evicted. The eviction part I got right away. But the narrative that tech companies are precipitating these evictions took me longer to understand. I had to click through dozens of links before I found the text stating explicitly that certain companies, people, laws, and organizations were to blame for gentrification.

I didn’t appreciate that. I felt that the project had not been entirely forthcoming with me; at first, it seemed like project was a neutral recorder of this phenomenon – just the messenger, so to speak. Only later did I realize that this project had a hard-lined bias: anti-tech, pro-arts. Pro-queer, pro-left, pro-marginalized groups of all kinds. I suppose a more attentive user might have picked this up sooner, based on the fact that the project explicitly states that it is “anti-eviction,” and that people being evicted are, more often than not, marginalized in some way. But I reached this conclusion late, and it revitalized my sense of antagonism.

Oddly enough, that sense of antagonism toward the project spilled over into a sense of antagonism toward the people being evicted. Not only did I not feel sympathetic, I felt outright dismissive and even slightly aggressive towards them. As if, rather than combat eviction, I would rather accelerate the process; I wanted to just evict 100% of non-tech workers in San Francisco,  so that this project would be pushed to its limit and sort of explode, and I wouldn’t have to deal with it anymore.

I think that this reaction stemmed from a feeling that I was being marginalized by the project. Because they took such care to distort the information, because they had such a hard political stance, and because they referred to local laws and neighborhoods with such familiarity, I felt like I didn’t really belong in their movement. Like I was very much an outsider. And that, to even be considered for ‘membership’ in this anti-eviction club, I would have to whole-heartedly adopt their anti-tech, pro-local-arts-and-disenfranchised-groups stance. Now, I consider myself to be very far to the left politically, but I hate this kind of ethical leftism that clearly marks an enemy (tech) and makes it a question of good vs. evil. So I found myself, once again, rebelling against the project and siding with the evil tech companies. I found myself thinking, yes, of course there is gentrification; since the 1950s and the birth of computing it has been inevitable that this part of the country would gentrify – you can’t fight the forces of history, so stop waving these sob-stories in my face and trying to provoke my sympathy and support.

I was taken aback by the force of this reaction even as I was experiencing it. I found myself wondering how I could be so cruel, heartless, and privileged. But then, when I thought about how the project was orchestrating this emotional turmoil in me, I rebelled against it further and hardened my antagonistic stance.

I appreciate that the Anti-Eviction Mapping Project was able to elicit such strong emotions from me, even though they might not have been the emotions the project intended me to feel. I attribute this strength of emotion to the experience of being a user, not a reader. I had to click my way through so much of the information, and scroll, and open links, and zoom in, and zoom out, and adjust my volume, and interact in all of these ways such that I got my hands dirty. They successfully dragged me in to the gentrification process, and made me a player.

The problem, though, was that I didn’t sympathize with the people being evicted. I felt involved in this phenomenon, but so ambivalent about my involvement and aggressive toward the project that I wanted to get uninvolved as quickly as possible. Sympathy was the missing ingredient. If only the project had been able to make me feel sympathetic, I think it would have been a powerful combination of user-engagement and emotional investment.

In order for the project to make me feel sympathy – or, in order for it to get me ‘on board’ with its mission and ideals – it needed to hold my hand more. I needed a narrative guide, a map through the maps. I needed a place to start. A beginning, a middle, and an end. The first thing I needed to see was the sentence “San Francisco is gentrifying.” Then slowly introduce the data. Then the stories. Then the history. Then the causes.

That feeling of collaboration, like the project is working with me to help me see something I hadn’t seen before, was sorely missed. Instead, the project felt like a jumbled mess, and that it was somehow my responsibility to make sense of it all.

Additionally, as someone who has never spent time in San Francisco, I needed this project to introduce me to the city. Rather than confronting me with the fact that in the Mission Hill neighborhood x% of long-term residents have been evicted, they need to tell me why I should care about Mission Hill, or what it is. This is just basic courtesy. If I’ve just met someone at a dinner party, I’m not going to start referring to the names of neighborhoods near my hometown with cavalier disregard for the fact that my interlocutor has no idea what/where any of these places are. It’s bad manners. This project, I thought, had bad manners. It alienated me from San Francisco by referring to these neighborhoods by name without giving me context for what they were.

In conclusion, I’m intrigued by this project. I’m intrigued by the combination of visuals, numbers, writing, and audio to tell a cohesive story. I’m intrigued by the strength of my (negative) reaction to the information. I think the model of attracting users, rather than readers, is an effective technique for digital storytelling. But I would have liked to have had a more carefully organized, less distorted user experience. I’m sure that there are data visualization projects out there that adopt this approach (if anyone could recommend one, I’d love to take a look). I’m excited to continue interacting with digital visualization projects like this one, and to develop an ability to discern which data-representing techniques and storytelling methods I prefer.


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