Ethnography Matters

Letter from the Editor: I am happy to announce the The Co-Designing with Machines edition. As someone with one foot in industry redesigning organizations to flourish in a data-rich world and another foot in research, I’m constantly trying to take an aerial view on technical achievements. Lately, I’ve been obsessed with the future of design in a data-rich world increasingly powered by of artificial intelligence and its algorithms. What started out over a kitchen conversation with my colleague, Che-Wei Wang (contributor to this edition) about generative design and genetic algorithms turned into a big chunk of my talk at Interaction Design 2016 in Helsinki, Finland. That chunk then took up more of a my brain space and expanded into this edition of Ethnography Matters, Co-designing with machines. In this edition’s introductory post, I share a more productive way to frame human and machine collaboration: as a networked system. Then I chased down nine people who are at the forefront of this transformation to share their perspectives with us. Alicia Dudek from Deloitte will kick off the next post with a speculative fiction on whether AI robots can perform any parts of qualitative fieldwork. Janet Vertesi will close this edition giving us a sneak peak from her upcoming book with an article on human and machine collaboration in NASA Mars Rover expeditions. And in between Alicia and Janet are seven contributors coming from marketing to machine learning with super thoughtful articles. Thanks for joining the ride! And if you find this to be engaging, we have a Slack where we can continue the conversations and meet other human-centric folks. Join our twitter @ethnomatters for updates. Thanks. @triciawang

Who is winning the battle between humans and computers? If you read the headlines about Google’s Artificial Intelligence (AI), DeepMind, beating the world-champion Go player, you might think the machines are winning. CNN’s piece on DeepMind proclaims, “In the ultimate battle of man versus machine, humans are running a close second.” If, on the other hand, you read the headlines about Facebook’s Trending News Section and Personal Assistant, M, you might be convinced that the machines are less pure and perfect than we’ve been led to believe. As the Verge headline puts it, “Facebook admits its trending news algorithm needs a lot of human help.”

The headlines on both sides are based in a false, outdated trope: The binary of humans versus computers. We’re surrounded by similar arguments in popular movies, science fiction, and news. Sometimes computers are intellectually superior to humans, sometimes they are morally superior and free from human bias. Google’s DeepMind is winning a zero-sum game. Facebook’s algorithms are somehow failing by relying on human help, as if collaboration between humans and computers in this epic battle is somehow shameful.

The fact is that humans and computers have always been collaborators. The binary human/computer view is harmful. It’s restricting us from approaching AI innovations more thoughtfully. It’s masking how much we are biased to believe that machines don’t produce biased results. It’s allowing companies to avoid taking responsibility for their discriminatory practices by saying, “it was surfaced by an algorithm.” Furthermore, it’s preventing us from inventing new and meaningful ways to integrate human intelligence and machine intelligence to produce better systems.

As computers become more human, we need to work even harder to resist the binary of computers versus humans. We have to recognize that humans and machines have always interacted as a symbiotic system. Since the dawn of our species, we’ve changed tools as much as tools have changed us. Up until recently, the ways our brains and our tools changed were limited to the amount of data input, storage, and processing both could handle. But now, we have broken Moore’s Law and we’re sitting on more data than we’re able to process. To make the next leap in getting the full social value out of the data we’ve collected, we need to make a leap in how we conceive of our relationships to machines. We need to see ourselves as one network, not as two separate camps. We can no longer afford to view ourselves in an adversarial position with computers.

To leverage the massive amount of data we’ve collected in a way that’s meaningful for humans, we need to embrace human and machine intelligence as a holistic system. Despite the snazzy zero-sum game headlines, this is the truth behind how DeepMind mastered Go. While the press portrayed DeepMind’s success as a feat independent of human judgement, that wasn’t the case at all. Read More… Co-designing with machines: moving beyond the human/machine binary

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[Image via GIPHY]

We are currently soliciting contributions to the March/April edition of EthnographyMatters. The aim of the edition is to document some of the innovative methods that are being used to explore online communities, cultures and politics in ways that connect people to the data created about/by them. By ‘method’, we mean both the things that ethnographers do (interviews, memo-ing, member checking, participant observation) as well as the principles that underpin what many of us do (serving communities, enabling people-centred research, advocating for change). Ethnography has never been tied indelibly with qualitative methods: the practice of ethnography requires using a suite of methods in order to reach our goals and there are multiple methods that ethnographers share with Big Data researchers.

The availability of data that is generated as a by-product of online activities offers researchers with useful ways of understanding online communities. Such methods can go far beyond merely the collection and visualisation/analysis of that data outside of the human context that constitutes the majority of Big Data research. ‘Small Methods for Big Data’ is not about methods “in the service of” Big Data but rather in the “context of”. Not “either… or” but rather “both… and”. Not one before the other, but both together in a circular motion towards understanding.

Examples of fresh ways of connecting data and people include:

• Defining the fieldsite by employing the metaphor of a network [Burrell, 2009];
• Using social media such as Instagram to write public field notes and memos [Wang, 2012];
• Conducting interviews with users by bringing in visualised traces of the user’s online experiences [Dubois and Ford, 2015].

There are, however, many others and we want to collect them as well as to publish reflections on their principled use in ethnographic and mixed method research in a small sample/vignette of innovative approaches. The vignette could then be used in teaching and research, inspiring others to add to the collection of methods and strategies used to connect people and data in innovative ways.

You can participate by sending details about interesting methods, strategies or reflections that you have encountered/experienced, or by writing a post for the upcoming edition.

Contributions to the vignette should be 300 words and should cover: what the method is, how the method works, why it works as well as where researchers can find more information about it.

Posts for Ethnography Matters’ ‘Small Methods for Big Data’ edition should be maximum 1,000 words and can offer a series of methods or focus on a single method and reflections on the use of that method. Contributor guidelines are here but email me if you have any questions.

Deadline: Friday 4 March, 2016

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Last week, we announced the rebirth of Ethnography Matters with a retrospective of the last five years of posts. Part of the rebirth involves meeting the community where it is at. And one of those places is Slack. So the Ethnography Matters, Anthrodesign, and EPIC teams have created a Slack channel for conversations about ​ethnographic methods. At Ethnography Hangout, we are an interdisciplinary group wearing many hats from design to tech and research, so you don’t need to have any formal background in ethnography to participate.

To us, creating a single Slack channel made a lot of sense to have our overlapping communities join into one place for conversations that extend beyond our own organizations and mailing lists.

We envision the Ethnography Hangout Slack to be a place for anyone to discuss applied ethnography. Those interested in discussion specifically grounded in the discipline of  Anthropology can also check out American Anthropology Association (AAA)’s Slack.

Founded in 2002, Anthrodesign’s mailing list established a new space for people working at the intersection of applied anthropology and design. Since 2005, EPIC has been promoting ethnography in organizations though the field’s premier annual conference, and more recently through an online community and professional resources at epicpeople.org . Launched in 2012, the Ethnography Matters blog has created publicly accessible content from people working in industry to academia at the cross section of technology and people. Despite having been formed at different times for different reasons, all three organizations  are committed to a people-centric to organizations, products, and services, thereby expanding the field of applied ethnography.

To join the discussion on Slack , please fill out this form where we ask for some information about you and your work. Read our Slack guidelines. We look forward to seeing you on Slack!

For any question about joining Ethnography Hangout Slack, please contact the administrators.

• Natalie Hanson, AnthroDesign @ndhanthro
• Tricia Wang, Ethnography Matters @triciawang
• Jennifer Collier, EPIC @epicpeople_org

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The editors of Ethnography Matters are pleased to announce that we’re back to our regular editorial calendar for 2016. We’ve set up a new series schedule for the year, with a focus on “centers of ethnographic practice.” Centers could be geographical (such as the focus on work happening at the interdisciplinary center, Highwire, in our first edition of 2016 edited by Joe Lindley), or centered around a particular idea, method or person. Each series will evolve over two months and will be edited by one of the team or by a guest editor.

In November last year, we celebrated the four-year anniversary of the founding of Ethnography Matters. Born in November 2011, Ethnography Matters was launched when we assembled a founding group of individuals who wanted to explore how technology makes us and how we make technology. Our original goal for starting Ethnography Matters was to create a body of work about ethnography that would be accessible in plain language to the public. No paywalls. No jargon. No degree waving. We wanted to build a community across industry, academia, and civil society. In the past four years, we have had an impressive collection of 182 posts, 13 editions, 14 interviews, 3 series, and 30 methods. Posts have been cited and reproduced in numerous academic publications and books, and the site has been featured as a resource for ethnographers in books by Christine Hine, Patricia Sunderland’s and Rita Denny, Gerrish & Lathlean, Gaillet & Eble and Bucchi & Trench.

Since 2011, we’ve watched this community grow on our WordPress dashboard from 500 readers a month to 15,000. It’s not only about numbers, though. We recognise our community not only in the numbers but in the stories we regularly hear from people who look to Ethnography Matters as a resource and talking point.

All communities need a narrative for why they exist, and Ethnography Matters is no different. Ethnography matters to us because it helps to keep technological development real. We believe that technologies need to develop close to the needs and experiences of users. Technologies need to aspire – to help us to not only do what we need to do but to be better people, to help us become a better society. These ideas have always mattered, but they matter now more than ever. In recent years, we’ve witnessed the global rise of new forms of automated and flextime labor systems such as Uber, Instacart, and Seamless. Technology is becoming increasingly embedded into our daily lives, bringing with it a particular set of logics that are difficult to resist. It’s clear that we’re in the middle of yet another social transition, but the question is, into what?Read More… Ethnography celebration and retrospective: We’re back!

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I “formally” discovered ethnography during my undergraduate degree in Cognitive Sciences when studying in France. Aside from classes in experimental psychology, we had courses in linguistics and cultural anthropology which is where I ran across this field and its approach. I remember that the lectures were fascinating, and the assignments were even more intriguing. We had to run interviews and observe curious topics such as how car-makers named auto-parts and their color, or how people make sense of the spatial environment. What caught me as interesting at the time was the approach, as it was totally different than the controlled experiments we had to run in Cognitive Psychology. Now that I think about it, the gap between these research endeavors is also huge in an epistemological sense, and I’m not sure that people in our program got that from the outset, but it was a marvelous opportunity to understand ethnography.

What I enjoyed was that it framed the way I was curious about the world, artifacts, people, and what they were doing. It basically corresponded to a more rigorous approach compared to something I use to do as a kid with my brother: going anywhere, sitting on a bench and looking at people, trying to make sense of what they were doing… an activity we used to called very naively “street physiognomy” (which, in retrospect, wasn’t physiognomy at all since we were focused on people’s activities).
Read More… We’re growing! Nicolas Nova Joins Ethnography Matters as a Contributor

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