Ethnography Matters

Note from the Editor, Tricia Wang: Next up in our Co-designing with machines edition is Madeleine Clare Elish, (@mcette), is an anthropologist and researcher at Data & Society, presents a case for why current cultural perceptions of the role of humans in automated systems need to be updated in order to protect against new forms of bias and worker harms. Read more about her research on military drones and machine intelligence at Slate. Madeleine also works as a researcher with the Intelligence & Autonomy Initiative at Data & Society which develops empirical and historical research in order to ground policy debates around the rise of machine intelligence.

“Why would an anthropologist study unmanned systems?” This is a question I am often asked by engineers and product managers at conferences. The presumption is that unmanned systems (a reigning term in the field, albeit unreflexively gendered) are just that, free of humans; why would someone who studies humans take this as their object of study? Of course, we, as ethnographers, know there are always humans to be found.  Moreover, few if any current systems are truly “unmanned” or “autonomous.” [1] All require human planning, design and maintenance. Most involve the collaboration between human and machine, although the role of the human is often obscured. When we examine autonomous systems (or any of the other terms invoked in the related word cloud: unmanned, artificially intelligent, smart, robotic, etc) we must look not to the erasures of the human, but to the ways in which we, as humans, are newly implicated.

My dissertation research, as well as research conducted with the Intelligence and Autonomy Initiative at Data & Society, has examined precisely what gets obscured when we call something, “unmanned” or “autonomous.” I’ve been increasingly interested in the conditions and consequences for how human work and skill become differently valued in these kinds of highly automated and autonomous systems. In this post, Tricia has asked me to share some of the research I’ve been working on around the role of humans in autonomous systems and to work through some of the consequences for how we think about cooperation, responsibility and accountability.

Modern Times, 1936 [giphy]

The Driver or the System?

Let me start with a story: I was returning to New York from a robot law conference in Miami. I ordered a Lyft to take me to the Miami airport, selecting the address that first populated the destination field when I typed the phrase “airport Miami” into the Lyft app. The car arrived. I put my suitcase in the trunk. I think the driver and I exchanged hellos–or at the very least, a nod and a smile. We drove off, and I promptly fell asleep. (It had been a long week of conferencing!) I woke up as we were circling an exit off the highway, in a location that looked distinctly not like the entrance to a major airport. I asked if this was the right way to the airport. He shrugged, and I soon put together that he did not speak any English. I speak passable Spanish, and again asked if we were going to the right place. He responded that he thought so. Maybe it was a back way? We were indeed at the airport, but not on the commercial side. As he drove on, I looked nervously at the map on my phone.

Read More… The future of designing autonomous systems will involve ethnographers

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Silvia Lindtner

Amelia Guimarin

Editor’s Note: Silvia Lindtner (@yunnia) and Amelia Guimarin (@femhacktweets) round out the March-April theme on makers, hackers, and engineers with this post that shares three stories of hackers and makers in China. Their observations complicate the celebratory story of hacking/making, giving us a richly detailed look at some of the real challenges and triumphs in this very active space. Silvia Lindtner (@yunnia) is a postdoc at the ISTC-Social at UC Irvine and at Fudan University Shanghai, and is the cofounder of Hacked Matter. She researches, writes and teaches about maker culture and its intersections with manufacturing in China. Drawing on her background in interaction design and media studies, she merges ethnographic methods with approaches in design and making. This allows her to provide deep insights into emerging cultures of technology production and use. Amelia Guimarin (@femhacktweets) is a independent producer and researcher at UC Irvine.  She has a background in anthropology and documentary filmmaking and focuses on issues of identity, labor and sustainability.  She also runs femhack.com, a showcase of DIY strategies for females with a hacker attitude.

“Making” is envisioned as a new mode of engaging the world, empowering citizens to turn from passive consumers into active participants in economic processes, state affairs and technological innovation. It is heralded as the saviour of broken economies and educational systems, across developed and developing regions alike. This vision of the rising maker is a powerful one. Indeed, it has attracted significant corporate investment (from places like Intel), drawn the attention of governments (from Obama to China) and mobilized money and people across regions (enabled in part by the set-up of new hardware accelerators like HAXLR8R). Making gets people excited (again). It is the story of adventure and of conquering unfamiliar territory to reinvent how technological futures are made today — at its heart it is a vision of technological and social progress. Journalists, scholars, and makers alike have been busy telling this story, joining in on the promotion of making as the harbinger of an industrial revolution (Anderson 2012). What has fallen through the cracks, however, are other stories of making that do not neatly fit the maker story of linear technological progress, of the Californian culture of cool and of embarking on a bold adventure. In this blog post, we focus on telling this other story of making — of those makers who are rarely thought of as makers and whose stories are less often told. Earlier this month, we traveled to Shenzhen to attend China’s first featured Maker Faire. Both of us came to the Maker Faire predominantly as researchers, although with different vantage points. Silvia lives in China and has been conducting ethnographic research with China’s maker scene and its intersection with manufacturing since 2010. Amelia lives in California, where she has been working as a documentary filmmaker and researcher on the topic of hacking and education. We recently embarked on a collaborative project of producing a documentary film on China’s makers, with a particular focus on what is going in the Southern parts of China, where small scale maker entities are forging new connections with manufacturers. There is both a power and responsibility that comes with holding paper, pen and camera – a topic that has received much attention in the discipline of anthropology. The ethnographer makes her fieldsite – she choses whose story to capture and how to tell it, co-constructing the sites she studies through the narrative that emerges from her work. It was in the evening of the last day of the maker faire, when it occurred to us that there was another maker story to be crafted here; it was the end of two exhilarating days filled with workshops, panels, and product showcases with presenters ranging all the way from small-scale start-ups to large corporations like Intel and Foxconn. We were about to head back to the hotel to drop off the equipment, when we paused. Something had changed. The streets that were filled, just hours before, with thousands of enthusiastic makers and visitors were empty, aside from a group of workers, who were in the midst of tearing down the large tents that had protected the booths of gadgeteers from the heavy rain of southern China. It was quiet, aside from the shouts of the workers who in a coordinated effort disassembled the tent. A few hours later – while the makers partied, drank, danced, talked, and celebrated their successful event – the tents were dismantled and loaded onto large by-standing trucks, with no sign left of a big event having ever taken place. A woman with a broom made out of twigs swept the street of the faire’s last remains.

Shenzhen maker faire tents being torn down

It was in this moment that it became clear to us how much attention is paid to the making of the thing, while the work that goes into sustaining and enabling making the thing is rarely appreciated or lauded as equally cool and valuable. Who builds up and tears down (literally and metaphorically) the maker tent? Who performs the work of organizing maker faires and conferences, of raising money, of building important social connections to promote and engage makers and consumers? What other modes of making are there? What alternative models of collaboration and open-ness do we overlook? This post will not be about the loudest, boldest and coolest projects at the Shenzhen Maker Faire. It will be about those who work more quietly, and perhaps with more sincerity, than their noisy counterparts on stage. Read More… Making! The Other Story: Robot#10, Twins Separated at Birth, and Hacker Mama

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Marisa Cohn

Editor’s Note: Marisa Leavitt Cohn writes to us from Stockholm, where she is a postdoctoral scholar studying the politics of software systems and computing work practices.

In this contribution to the series on Hackers, Makers, and Engineers, she tells us about her research on relationships to technological change in a long-lived NASA-ESA software infrastructure project. Her research considers how people live alongside technological change, inhabit the temporal rhythms of computing work, and approach concerns of legacy, inheritance, and survival of computational practices as they contemplate the end of life of the mission.

Marisa has a BA in anthropology from Barnard College and a PhD in informatics from UC Irvine, and she’s joining ITU Copenhagen as a professor in the fall. She’s a member of the ISTC-Social. 

Ethnographers have often been positioned in the technology field as translators between the worlds of technology use and design. When I first began my fieldwork with an engineering team at a NASA space science mission, I thought I might be able to trouble this dyadic concept of translation work between design and use by examining a case in which a complex set of translations took place between a diverse set of organizational actors, from scientists to engineers to managers. Indeed, I observed the engineers on the team working on a weekly basis to turn hundreds of observation requests from scientists all across the globe into commands that can be executed on a spacecraft over a billion kilometers away. This complex translation work was supported in turn by hundreds of software tools that had been developed over the years to, as one engineer described it, “turn scientists’ dreams into vectors.”

Yet when I presented early versions of this work to the social computing research community, I found that the relevance of my work was often challenged. The engineering project I was examining was deemed a “one-off,” a bespoke system that served a single purpose, and which was ultimately “disposable” since the spacecraft would be destroyed in space once it had run out of fuel and completed its mission. Not only that, the software tools that I was studying in organizational contexts were now decades old. They were written in FORTRAN and some of the earliest graphical interface programming languages, tools which have largely been abandoned by the engineering community – reaching end of support, dying out, or even being actively petitioned into retirement.

These make great bookmarks now. Image courtesy of http://en.wikipedia.org/wiki/File:FortranCardPROJ039.agr.jpg

These challenges begged the question – what is to be gained by studying the work of engineers maintaining a space robot from the 90s? What is the role of the ethnographer in studying the so-called technological “dinosaurs” – the old-timers who are stuck in engineering methods and tools of the past? What relevance do these obsolete software tools and engineering practices that go along with them have for understanding technology today? Even to many of the engineers at the mission, my interest in their software tools seemed a bit odd. As one responded to my research,

You think our software is interesting?! It’s not Google or anything.

Legacies of a 90s space robot

These questions put me on the defensive about my contribution to the study of sociotechnical systems and my role as an ethnographer in the field. What was my role, as a translator or participant or otherwise? One of the roles I was enlisted into at the mission organization showed that this defensiveness was a part of my informants’ reality as well. I was asked to help with their work towards a final mission report, to help preserve some of the stories of their engineering accomplishments for the historical archive. The archive of scientific data was already assured, but what about the engineering knowledge gathered over the course of the mission? Might the work they have done over the past two decades be of any use for future outer planets missions? What if there is not another mission of this kind for another 50 or 100 years?

Read More… Engineering obsolescence

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Lilly U. Nguyen

Editor’s Note: Lilly U. Nguyen (@deuxlits) tells us how in her own work on the ethnography of software in Vietnam, she both studies and embodies “diaspora” – and she shares the insights that diaspora has given her. She is a postdoctoral scholar at the ISTC-Social at UC Irvine. She studies race, labor politics, and information technology in Vietnam and among the Vietnamese diaspora.

Lilly’s post continues the March-April edition focusing on ethnographies of makers, hackers, and engineers.

In my work, ethnography takes on diasporic dimensions.

These qualities touch on several of the questions raised in previous posts in this blog series, such as the distinction between self and other and the Cartesian coordinates of studying up and down in Nick Seaver’s post and the disciplinary shifts as described in Austin Toomb’s post. For those of us who study decidedly contemporary phenomena like algorithms, hackers and (in my case) software, ethnography allows us to study people who are neither entirely like us nor entirely unlike us.

Many of us who do this kind of work find a home in the field of science and technology studies (STS). This field has a long tradition of people who have professional training in scientific fields only to then move into the humanities and social sciences. In a similar kind of move, I find that many of us who study technology have had some kind of professional experience with hackers, algorithms, or software. In my case, I previously worked in a non-profit organization in Silicon Valley that worked to promote openness in educational institutions. This included building online portal systems to encourage teachers to share pedagogical materials as well as promoting data-based decision-making among education administrators and faculty. This professional experience shaped my research by providing insight into the challenges and limits of promoting openness and freedom through technical artifacts like databases and software.

I suspect that the biographies of many of us who do this kind of ethnographic work might be similar: previous degrees in computer science, degrees in other technical and scientific disciplines, professional experience in industry. And then a fork. A catapult into new terrain … or probably something more subtle, but a change nonetheless onto a new trajectory. A pivot, perhaps.

Pivots, turns, and forked paths. Courtesy https://www.flickr.com/photos/pfly/188629337/

These pivots, turns, and forked paths carry with them diasporic qualities. Diaspora, in and of itself, is a tricky and complicated thing. In the inaugural issue of Diaspora, Tölölian (1991) writes that the term initially referred to dispersed populations exiled from homelands who were then forced to live among strangers. In these early formulations, diaspora comprised a history of dispersal, nostalgia of homeland, alienation in host countries, desires for return, and a collective identity importantly defined by the tenuous relationships between home and the displaced here.

Read More… Ethnography as Diaspora

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Katie Pine

Max Liboiron

Editor’s Note: Katie Pine and Max Liboiron continue this week’s theme of makers, hackers, and engineers with a post about the politics and performativity of measurements, central to the practice of many engineers and scientists.

Katie Pine (@khpine) is a postdoc in Intel Labs Cultural Transformation Lab, and is currently in residence at UC Irvine.  Katie’s work bridges Computer Supported Cooperative Work, Organization Studies, and Science & Technology Studies.  At present her NSF-funded research examines micro-foundations of IT-enabled accountability policy and practice in the healthcare domain.

Max Liboiron (@maxliboiron) is a postdoc at Northeastern University’s Social Science Environmental Health Research Institute (SSEHRI) and a co-founding member of the Superstorm Research Lab, a mutual aid research collective. Liboiron studies “techniques of definition,” the tools and practices used by scientists and activists to make emerging, contested, amorphous forms of environmental harm manifest.

From common core to quantified self, measurement is increasingly part and parcel of our daily lives.  We use number-driven measurements to make visible, manage, and regulate increasingly nuanced aspects of daily life, work, public institutions, and our environment.

However, measurements are never mere faithful representations of nature, but have social and political origins and ramifications.  We are exploring two aspects of measurement that often go unnoticed: first, the situated, complex work that goes into making measurements work in the first place (and the fact that this work is inherently social, cultural, and political), and second, the idea that measurements themselves can be seen as performative, creating and re-creating the very things they are intended to make visible.

Representational theory defines measurement as “the correlation of numbers with entities that are not numbers,” a process of transformation, translation, and even interpretation at the level of sampling and gathering data. What is selected for measurement and what is not, how measurements are standardized, what counts as an important unit of measure, and how measurements are used all have stakes for the systems of which they are part.

Moser & Law (2006) argue that current metaphors for information as “flow” are inaccurate, as these metaphors presume that information is immutable, something that is created and exists in the world and thus can be taken up, passed around, and used for calculation.  Moser and Law instead argue that we can see information as something that is inherently mutable and relational, that changes its shape as it is circulated and used.  To put it more simply, information never fully has meaning on its own – it becomes meaningful and usable when a particular person or group make decisions about what the information is and how they can use it.

A good example comes from a recent study on counting rates of infection in hospitals (Dixon Woods et Al., 2012).  The authors found that an act as seemingly simple as counting infections was actually highly social and cultural – the answer to the question “what counts?” varied widely from one hospital to another, calling into question the current focus in healthcare (and investment of healthcare dollars) on quality measures as a tool for achieving reforms such as infection reduction in practice. Making meaning of numbers requires acts of both calculation and judgment, what Moser & Law call “qualculation.”

Read More… Measurements: The Qualitative Work of Quantitative Work

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Austin Toombs

Editor’s Note: Austin Toombs (@altoombs) brings a background in computer science and a critical sensibility to his ethnographic research on maker cultures.  He explores the formation of maker identities in his research, focusing on how specific sites such as hackerspaces, makerspaces, Fab Labs, and other co-working spaces intersect with the politics of making, gendered practices, urban vs. rural geographies, and creative hardware and software developments. Austin is a PhD student in Human Computer Interaction Design in the School of Informatics and Computing at Indiana University. He is a member of the Cultural Research In Technology (CRIT) Group, and is advised by Shaowen Bardzell and Jeffrey Bardzell. He is also a member of ISTC-Social.

My research as a PhD student began by looking at cultures of participation surrounding hobbyist programming. I was—and still am—interested in the fuzzy-gray area between work and play, and as someone who misses the puzzle, thrill, and flow of programming, these communities were great starting points for me. Working on this research led me, almost inevitably, toward my ethnographic work with my local hackerspace and the broader maker community. In this context, I have seen how this local community embraces the work/play ambiguity, how it can function primarily as a social environment, and how it works to actively cultivate an attitude of lifelong, playful, and ad hoc learning. In this post I explore the role ethnography played in my work and how the ethnographic approach helped me get to these insights. I also discuss some of the complications and issues I have run into because of this approach, and how I am working toward solving them. For more information, feel free to contact me!

the role of ethnography in my work

My first encounter with the concept of a hackerspace came from my initial research on hobbyist programmers. I remember nearly dancing with excitement when I realized that the city I lived in happened to have a hackerspace, because I knew immediately that I would be joining them in some capacity, if not for research, then for my own personal enjoyment. The first few visits to the space were exploratory; I wanted to see what was going on, how the members and regular attendees interacted with each other, and whether or not this seemed like a good fit for my research.

My initial goal was to use the site as a potentially endless supply of case studies to explore my questions about work and play. Thankfully, I realized fairly early on that this case-study-first approach would not work for me. Instead, I found myself drawn to the overall narrative of the hackerspace and its members. How did this particular maker community form? What did the members do for their day jobs? How did they become ‘makers’? What do they think about themselves, and how has becoming a member of this community influenced that?

Read More… Falling in: how ethnography happened to me and what I’ve learned from it

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Nick Seaver

Editor’s Note: Nick Seaver (@npseaver) kicks off the March-April special edition of Ethnography Matters, which will feature a number of researchers at the Intel Science and Technology Center for Social Computing on the forefront of exploring the cultures of hackers, makers, and engineers.

Nick’s post makes the case for the importance of “studying up“: doing ethnographies not only of disempowered groups, but of groups who wield power in society, perhaps even more than the ethnographers themselves.

Nick’s own research explores how people imagine and negotiate the relationship between cultural and technical domains, particularly in the organization, reproduction, and dissemination of sonic materials. His current project focuses on the development of algorithmic music recommendation systems. Nick is a PhD candidate in sociocultural anthropology at UC Irvine. Before coming to UCI, Nick researched the history of the player piano at MIT. 

When people in the tech industry hear “ethnography,” they tend to think “user research.” Whether we’re talking about broad, multinational explorations or narrowly targeted interviews, ethnography has proven to be a fantastic way to bring outside voices in to the making of technology. As a growing collection of writing on Ethnography Matters attests, ethnography can help us better understand how technology fits into people’s everyday lives, how “users” turn technologies to unexpected ends, and how across the world, technologies get taken up or rejected in a diverse range of cultural contexts. Ethnography takes “users” and shows how they are people — creative, cultural, and contextual, rarely fitting into the small boxes that the term “user” provides for them.

But ethnography doesn’t have to be limited to “users.”

Engineers in context. cc by-nc-nd 2.0 | http://www.flickr.com/somewhatfrank

My ethnographic research is focused on the developers of technologies — specifically, people who design and build systems for music recommendation. These systems, like Pandora, Spotify, Songza, or Beats Music, suggest listening material to users, drawing on a mix of data sources, algorithms, and human curation. The people who build them are the typical audience for ethnographic user studies: they’re producing technology that works in an explicitly cultural domain, trying to model and profile a diverse range of users. But for the engineers, product managers, and researchers I work with, ethnography takes a backseat to other ways of knowing people: data mining, machine learning, and personal experience as a music listener are far more common sources of information.

Ethnographers with an interest in big data have worked hard to define what they do in relation to these other methods. Ethnography, they argue, provides thick, specific, contextualized understanding, which can complement and sometimes correct the findings of the more quantitative, formalized methods that dominate in tech companies. However, our understandings of what big data researchers actually do tend to lack the specificity and thickness we bring to our descriptions of users.

Just as ethnography is an excellent tool for showing how “users” are more complicated than one might have thought, it is also useful for understanding the processes through which technologies get built. By turning an ethnographic eye to the designers of technology — to their social and cultural lives, and even to their understandings of users — we can get a more nuanced picture of what goes on under the labels “big data” or “algorithms.” For outsiders interested in the cultural ramifications of technologies like recommender systems, this perspective is crucial for making informed critiques. For developers themselves, being the subject of ethnographic research provides a unique opportunity for reflection and self-evaluation.

Starbucks Listeners and Savants

Among music tech companies, it is very common to think about users in terms of how avidly they consume music. Here is one popular typology, as printed in David Jennings’ book Net, Blogs, and Rock ‘n’ Roll:

Read More… Studying Up: The Ethnography of Technologists

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danah boyd (@zephoria) is a Principal Researcher at Microsoft Research, a Research Assistant Professor in Media, Culture, and Communication at New York University, and a Fellow at Harvard’s Berkman Center. In 2009 Fast Company named boyd one of the most influential women in technology. Also in 2010, Fortune named her the smartest academic in the technology field and “the reigning expert on how young people use the Internet.” Foreign Policy named boyd one of its 2012 Top 100 Global Thinkers “for showing us that Big Data isn’t necessarily better data”. danah just published, It’s Complicated: The Social Lives of Networked Teens.  

There’s this idea that hard-core techies are code geeks. But hard-core techies also look like ethnographers. A tech ethnographer not only has to understand cultural code, but the mechanisms for how software design links back up to tech practices. I sat down with one of the most well known tech ethnographers of our time, danah boyd (@zephoria). 

Over breakfast at The Ace Hotel’s Breslin, danah and I talked about her career. This fascinating and personal interview reveals danah’s journey through industry and academia.

We’re also excited to have danah’s interview launch Ethnography Matter’s second column, Tell Me More,  featuring interviews with people who are pushing the boundaries of ethnography in unconventional and exciting ways. We conduct the first interview and then post a follow up interview with crowd-sourced questions from the audience. 

Post your follow-up question for danah in the comments or tweet it with the hashtag #askdanah by March 10. danah will select her favorite questions to answer in her second interview!  

Tricia: danah, I’m super excited that we get to talk ethnography over some yummy breakfast food! Earlier last year, you were inducted into the SXSW Hall of Fame.  An ethnographer being validated by geeks! I was beyond excited when I heard this news. How did you feel when you found out?

danah: SXSW has been a very important event to me for a long time. I learned so much about the tech industry through that conference by spending late nights drinking with entrepreneurs and makers. I actually got many a job that way too. It was at SXSW where Ev Williams and I started debating blogging practices. He hired me to work for him that summer.  Oh, and SXSW was where I met my partner.

Tricia: What? Are you serious?

danah: ::laugh:: Ayup!  And now we have a baby who we’re taking back to SXSW this year.

Tricia: Shut up. That is so sweet. Where did you guys meet at SXSW?

danah. At a Sleater-Kinney show.

Tricia: That’s awesome.

danah: It’s just funny to be honored there because I’ve selfishly gotten so much out of the conference.

Tricia: Well I remember very clearly when I read the transcript of the keynote you delivered at SXSW in 2010. It was about Facebook’s issues with privacy. Your talk generated so much discussion. How did you settle on this topic?

danah: I thought, what could I do that would provoke this audience to think? I saw it as a political platform; not big P but small p. I wanted to use this opportunity to challenge norms inside tech industry. I decided to take on the underlying values and beliefs in tech industry regarding privacy because my research was showing that the rhetoric being espoused was naïve. My topic was not surprising for academics, but it was for practitioners.Read More… Tell Me More danah boyd: an interview with the author of “It’s Complicated: The Social Lives of Networked Teens”

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