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Q&A with Professor Gwen Ottinger

April 13, 2016

Gwen Ottinger, PhD

Drexel University’s Gwen Ottinger, PhD, hosted a participatory design workshop in the San Francisco Bay Area in early April.

Professor Ottinger, the author of "Refining Expertise: How Responsible Engineers Subvert Environmental Justice Challenges" (2013), has an impressive research agenda based on questioning the environmental justice implications of current modes of science and technology. For her current project, Professor Ottinger has been traveling to the San Francisco Bay Area to do social science research in communities next to oil refineries, where residents are concerned about toxic chemicals in their air. We caught up with her to ask about research, her recent workshop and the virtues of inquiry that engages with communities’ real-world problems.

Q: What was the topic of your workshop?

A: The title of my workshop, “Meaning from Monitoring,” sums it up. Two of the four refinery communities in the Bay area now have access to a wealth of information about what’s in the air, thanks to years of activism to get refineries to install real-time monitors at their fencelines and in neighboring residential areas.  These monitors measure a range of chemicals that are linked to health effects, including benzene and hydrogen sulfide.  But even though the data are publicly available on a website, they’re so voluminous that it’s hard to figure out what they mean.  The user can’t easily generate an average to compare to health standards, for example--and even if she could, that wouldn’t tell the whole story.  Health standards may not be sufficiently protective, and averages can miss spikes in air pollution caused by accidents, leaks or malfunctions at the refinery or other nearby facilities.

In the workshop, my research team and I worked with residents of refinery communities, and representatives of environmental justice non-profits that assist them, to design a better system.  Our ultimate goal is to create a website and mobile app that will let people take the data and use it to tell powerful stories about what it means to live next to an oil refinery.  My colleagues from Intel Labs and Carnegie Mellon University’s CREATE Lab have developed some prototypes: we imagine that communities will want alerts when pollution surges, a way to report things that they are smelling, seeing, or feeling and the ability to look at other users’ reports.

But we’re not the authorities on what communities need, so we’re taking our prototypes to residents as a starting point for a discussion of what they want to be able to do with the data, and how we can make that happen.  We hope to walk away with a community-driven agenda for developing this new online platform.

Q: Is this related to the fieldwork you completed in the San Francisco Bay Area last year?

A: Very much so. I have been working on an oral history project with the same communities, documenting how they went from zero information on what was in the air surrounding refineries as recently as 1994, to the EPA and the Bay Area Air Quality Management District adopting regulations to require monitoring at refinery fencelines. My first article on that topic, called “Citizen Engineers at the Fenceline” was just published in January.

It’s doing this research along with the fieldwork that led to my book, that has enabled me to identify the weaknesses of the current systems for providing fenceline monitoring data to communities--and to have a pretty good idea of when data works for residents and when it doesn’t.  We’re not shooting in the dark with our prototypes. Instead, I’ve been able to identify a variety of stories that people are already telling about how refinery emissions affect them, and we’re specifically trying to design a system that will offer data that can be folded into those stories to increase their impact.

The two complementary tracks of the research are also both funded by the same grant, a 5-year CAREER award from the National Science Foundation.

Q: What sorts of data did you gather from that time in the field?

A: Interviews with residents and documents from the past 20 years of activism around monitoring issues.  We’re not producing any air quality data, just figuring out better ways to work with publicly available data generated by scientists.

Q: So it seems like on the one hand, you have these pretty interesting findings purely from a scientific perspective, while on the other hand, you also have this incredible story to tell about “user-friendly” science. Can you speak to this dual narrative a little more?

A: Actually, I think there are three kinds of findings. First, there’s the political science finding, about how activism combined with technological innovation can lead to policy change. Then there is the potential to draw interesting conclusions about what air quality in fenceline communities looks like and how it affects people’s health. But I don’t think we can make any claims about that yet. The data are, paradoxically, both too overwhelming and too limited. On the one hand, the detection limits on the monitors are high enough that you miss a lot that could be important, and health data aren’t correlated to the air monitoring data. On the other hand, we are limited in our ability to assess the data we do have, because we don’t have good ways to interpret them--either technologically or conceptually.  So the most interesting kind of finding is really the third one: “big data” doesn't do you much good unless you have a way to make sense of them.  What we hope to discover are some good ways to do that.

Q: I understand that your research assistants will be going with you – what has their role been in coding and organizing this information?

A: Nick Brooks, who has been working with me on a research co-op since September, has done an incredible amount of work to catalog the online platforms for monitoring data that are already out there--to make sure we’re not reinventing the wheel--and to try to solve the problem of how to make sense of so much data. What we’ve learned from him is that our current tools really aren’t adequate, and he’s helped identify the gaps and weaknesses that need to be addressed.  Amy Gottsegen, a computer science major who is just joining our team, will be taking the lead on implementing the system we conceive together on April 2.  And Derek Parrott, about to finish his MS in Science, Technology, and Society, has been my right-hand throughout all of this, coordinating the efforts of collaborators who are spread across the country.

Q: So what sort of impact do you hope this research agenda will have for people who live adjacent to oil refineries or other sites of environmental degradation?

A: I hope that my research will help to increase communities’ capacity to advocate for a clean environment, by giving them better access to information that they can pull into their testimony at public hearings, their interactions with refinery officials and their calls for improved monitoring at all industrial facilities.  Having quantitative data at your fingertips matters in all of these settings, but it’s only useful if it amplifies your message.  By designing information platforms with community members with political action in mind, I hope we’ll make it possible for them to incorporate quantitative data where they weren’t able to before.

Q: Finally, tell us a little about the rest of your research and teaching agenda – what’s next after this?

A: This project is at such an early stage of development, that it’s hard to think about what’s next.  The oral history aspect of my research will become a book on the trajectory of community-based monitoring and “citizen science” more generally.  Our nascent online platform will, I hope, become a new gold standard for providing environmental information to fenceline communities in a way they can really use. I expect that even if we are successful, it will take a lot of work to institutionalize it. In the long term, I’d like to use this project to launch a new model for responsible innovation that has social and environmental justice issues at its heart.