In October 2014, New York University’s Center for Urban Science and Progress (CUSP) unveiled the Urban Observatory, as part of an urban informatics initiative for monitoring, recording, and modeling the actions and nonactions of New York City. Inspired by research methods in observational astronomy, the scientists at CUSP placed an 8 megapixel camera on top of a building in Downtown Brooklyn, which shoots one panoramic, long-distance image of Lower and Midtown Manhattan every 10 seconds. Using the Urban Observatory and a network of similar sensors, the scientists at CUSP are attempting to capture what they call “the pulse of the city,” formulating massive data sets that provide information regarding various domains of everyday life, ranging from energy efficiency to the detection of toxic releases. As urban informatics professionals, they imagine that the collected data will serve as “raw material” for policy making — once they have access to this raw material, the CUSP scientists will be able to model their predictions, and hope to ultimately (somehow) manufacture the steps required to reduce electricity consumption in office buildings, or to generate emergency responses to hazardous substances.
CUSP’s efforts perhaps constitute an attempt to retrofit New York City itself – to embed interfaces directly in the urban environment, collect large amounts of data, and eventually make the city “smart,” somewhat like Songdo of South Korea, or Masdar City of the United Arab Emirates. CUSP collaborates with companies like IBM and Cisco Systems, which excel in transforming cities into seamless, sentient interfaces for ubiquitous computing and data management. City builders around the world no longer talk about eco-cities, or even sustainability measures, but instead choose to focus on the discourse of “smartness,” summarized as a city’s ability to read, record and respond in real time to changing conditions of everyday life. Rather than relying merely on carbon emissions figures, for instance, designers and developers today instead call for a broader array of measurements that allow a wider range of observations in the urban environment, which can be mobilized for mitigating environmental problems. Big data, in the form produced by a smart city, offers yet another technological fix for climate change and energy scarcity.
In addition to making policy suggestions through its interactive surfaces, the smart city aspires toward a new collectivity, comprised of ten thousand little brothers, taking the place of one big brother. In this formulation, the urban subject becomes part of the city by volunteering data, and engaging in practices of visibility. While such visibility may grant new forms of access to many city dwellers, who suffer from an inability to make claims because they lack supporting quantitative evidence (CUSP scientists use public housing maintenance as an advocacy example), it also makes it very hard to maintain anonymity in the city, and further entrenches corporate means of city governance. IBM, for instance, works with retailers to test marketing strategies wherein consumers receive personalized offers based on their internet searches the moment they enter a store, or even merely walk down an adjacent street. Through a multiplicity of tracking methods, this emergent form of collectivity endangers the urban subject’s rights to remain silent.
It is worth noting that this form of visibility tracks, records, and capitalizes on the city dweller’s actions, more than her voice. The scientists at CUSP propose that once the appropriate sensors are in place, people’s movements almost alchemically become reconfigured as data. What emerges is not a sample but a whole data set, which does not depend on surveys, focus groups, or interviews. According to urban informatics professionals, this process eliminates the subjective social scientist, who molds the respondent’s answers through questions, as well as the respondent’s ability to narrate a storied perspective. Indeed, although some have pointed out that the collected data is, in fact, engineered and authored rather than raw, urban informatics professionals still pride their newborn ability to directly observe and trace crowds’ actions in real time through quantitative means.
While ethnographic perspectives are generally situated as “other” to big data research, there are some interesting similarities between the two. The massive interfaces that watch the city and its crowds are, in a sense, a grandiose version of participant observation, which itself allows ethnographers to study the discrepancies between what people say and what people do. Data scientists do not start with explicit research questions, but with wide ranging observations, and then mine the data for possible insights, almost like an ethnographer who goes through her field notes upon returning home from a research site. Similar to ethnographic research, the data that is generated does not provide causal links; instead, data scientists draw upon correlations between different types of actions, building possible personalities for identifiers like login names or IP numbers.
Of course, the privacy concerns related to the use of big data, represented most vividly by the Snowden case and the recent documentary Citizenfour, are far more extensive than what any qualitative research effort could generate, and should be taken very seriously. When asked about their efforts to observe Manhattan, CUSP scientists suggest that they use low-resolution cameras specifically because they wish to refrain from identifying individuals, while curtailing intrusions into places deemed private or personal. Yet it remains to be seen whether they will share the data with institutions like the NYPD. Interestingly enough, some data scientists state that the millennial generation has a different sense of privacy, and note how they may not care that much about such intrusion. While this would be an interesting shift to map or research, it cannot serve as a justification for invasive practices. Instead, as some designers propose, perhaps we could produce not seamless, but rather seam-full computational interfaces, which are designed provoke and raise awareness for the urban subject. These interfaces would remind people, as the BitTorrent billboard says: “your data belongs to you.”
Despite growing debate and conversations about urban informatics, some big data researchers note that we do not yet have a good vocabulary to discuss the shift towards a more quantified urban life. For instance, what does “the pulse of the city” really indicate? Many urbanists have already conceived the city as an organic whole, a cyborg with a brain, a heart and a circulatory system, but how does that organism or cyborg change when the city becomes attached to smart sensors that mediate and compile information at every step? While building experimental artifacts for tracing urban actions and nonactions, researchers could perhaps direct their efforts to building this vocabulary, and focusing more clearly on the stakes of the conversation – most importantly because this conversation will most likely stick around for the next few decades.
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 Kitchin, Rob. 2014. Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. Sage: London.
 Boelstroff, Tom. 2013. “Making Big Data In Theory” http://firstmonday.org/ojs/index.php/fm/article/view/4869/3750
 Shepard, Mark. 2011. “Toward the Sentient City” in Sentient City: Ubiquitous Computing, Architecture and the Future of Urban Space, ed. Shepard, M. Cambridge: MIT Press, p 16-37.