Welcome to the CASTAC blog, the official blog of the Committee on the Anthropology of Science, Technology, and Computing!
Alan Turing was involved in some of the most important developments of the twentieth century: he invented the abstraction now called the Universal Turing Machine that every undergraduate computer science major learns in college; he was involved in the great British Enigma code-breaking effort that deserves at least some credit for the Allied victory in World War II, and last, but not the least, while working on building early digital computers post-Enigma, he described — in a fascinating philosophical paper that continues to puzzle and excite to this day — the thing we now call the Turing Test for artificial intelligence. His career was ultimately cut short, however, after he was convicted in Britain of “gross indecency” (in effect for being gay), and two years later was found dead in an apparent suicide.
The celebrations of Turing’s birth centenary began three years ago in 2012. As a result, far, far more people now know about him than perhaps ever before. 2014 was probably the climax, since nothing is as consecrating as having an A-list Hollywood movie based on your life: a film with big-name actors that garners cultural prestige, decent press, and of course, an Academy Award. I highly recommend Christian Caryl’s review of the The Imitation Game (which covers Turing’s work in breaking the Enigma code). The film is so in thrall to the Cult of the Genius that it adopts a strategy not so much of humanizing Turing or giving us a glimpse of his life, but of co-opting the audience into feeling superior to the antediluvian, backward, not to mention homophobic, Establishment (here mostly represented by Tywin Lannister, I’m sorry, Commander Denniston). Every collective achievement, every breakthrough, every strategy, is credited to Turing, and to Turing alone. One scene from the film should give you a flavor of this: as his colleagues potter around trying to work out the Enigma encryption on pieces of paper, Turing, in a separate room all by himself, is shown to be building a Bombe (a massive, complicated, machine!) alone with his bare hands armed with a screwdriver!
The movie embodies a contradiction that one can also find in Turing’s life and work. On one hand, his work was enormously influential after his death: every computer science undergrad learns about the Turing Machine, and the lifetime achievement award of the premier organization of computer scientists is called the Turing Award. But on the other, he was relatively unknown while he lived (relatively being a key word here, since he studied at Cambridge and Princeton and crossed paths with minds ranging from Wittgenstein to John Von Neumann). Perhaps in an effort to change this, the movie (like many of his recent commemorations) goes all out in the opposite direction: it credits Turing with every single collective achievement, from being responsible for the entirety of the British code-breaking effort to inventing the modern computer and computer science. « Read the rest of this entry »
Georges Doriot, who founded the first publicly traded venture capital firm in 1946, arguably announced a new regime of speculative capital when he said: “I want money to do things that have never been done before” (Ante 2008). In the years immediately after World War II, the establishment of venture capital firms was crucial to the ascent of a new kind of commercial enterprise, one that has profoundly influenced the development of digital technologies on a very broad scale. It was with the creation of the first venture capital firms that a financial network to support technology startup companies began to form. The fact that the earliest Silicon Valley startups were funded by venture capital investments is an indicator of the degree to which the developmental trajectory of personal computing has been intertwined with that of finance capital. Fairchild Semiconductor, for example, was the first startup funded by venture capital (in 1957), and it launched numerous “spin-off” companies that were collectively responsible for the innovations that enabled what became the microelectronics industry. Since then, of course, venture capital has grown into a powerful industry that directs vast financial resources into technology startup companies. But venture capital investment doesn’t only fuel the tech startup economy — it actively shapes it.
Research on Silicon Valley’s high tech industry suggests that venture capitalists’ importance to processes of innovation has more to do with their role in selecting promising companies than with simply providing financing itself (Ferrary & Granovetter 2009). Beyond choosing the criteria for valuation by which the potential commercial success of startups is measured, they determine which innovations will even have a chance to enter the market. The result is that Silicon Valley innovation is guided directly by finance capital’s future-oriented logic of speculation. Companies with few tangible assets pursue funding without which they will have little chance to successfully launch their products and, as business news coverage attests, some companies are valued at billions of dollars without demonstrating that they have the means to become profitable. What matters is keeping the possibility of a market open. One could think, for example, of Snapchat, a popular photo and video sharing app that has expanded through significant venture capital investments. Last year, the company was valued at $10 billion, despite the fact that it generates almost no revenue, mostly on the basis of its potential to reach users and create an audience.
Barry Dornfeld’s 1998 book Producing Public Television, Producing Public Culture was a formative one that knocked me from media studies to media anthropology (and made me realize that my “revolutionary” new idea for fieldwork had been scooped). For my first post on the CASTAC Blog as an Associate Editor, I want to return to my intellectual roots to interview Dornfeld, and discuss his transition from NYU assistant professor and University of Pennsylvania Communication program director to ethnography evangelist in the business world.
Producing Public Television saw Dornfeld conducting full-fledged participant observation amidst the producers at PBS while they assembled a transnational documentary called Childhood. This book has influenced both my dissertation and my fieldwork among television producers, particularly for its treatment of expertise. Dornfeld, for example, addresses the degree to which producers consider themselves proxies for their audiences, vehicles for a kind of mass-mediated paternalism, or feel shackled by a necessity to communicate reductively. But in learning about his professional trajectory, I found myself curious about his unconventional movement(s) between academia and industry. And as our potential for engagement with the business (or at least non-academic) world is on the minds of some in the CASTAC community, I thought I’d talk to Dornfeld about his work on media production, the use of ethnography in the business world, and his most recent book on how ethnography can help organizations adjust during periods of intense change. Below, he graciously answers my questions.
Elizabeth Rodwell: First, how aware are you of the legacy your book “Producing Public Television” has had in anthropology and media studies? What has been the legacy of that publication in your professional life?
Barry Dornfeld: I am aware that some folks still use and refer to the book, which I am pleased to be reminded of after all these years. Not being in academia any more limits my exposure a bit, but I do hear periodically from people who are studying media production and find the book useful. And I have some old colleagues who still assign the book. I think the perspective and method hold up well, even if the world of media and media theory have evolved.
ER: Do you think television corporations have become more sophisticated in their understanding of audiences than they were when you conducted your doctoral fieldwork? « Read the rest of this entry »
In January, researchers from National Chung Cheng University in Taiwan and Alpen-Adria-Universität in Austria published a study in the journal Public Understanding of Science exploring the use of science words as lyrical elements in popular Taiwanese mainstream music. The intent of the study was to understand better how non-scientists were using science terminology in creating pop music songs, and perhaps learn something about bridging social contexts by exploring aspects of the most fundamental element of science communication: words.
The study examined the content and quantity of scientific terms and expressions distributed throughout mainstream music lyrics as a potential reflection of the presence of science into Taiwanese popular culture and life. Starting with a list of 4526 songs created between 1990 and 2012 generated from the Golden Melody Awards, Asia’s mainstream music awards, the authors then reduced the sample based on the “relation of lyrics to science/technology” criterion. A total of 377 songs were ultimately selected for analysis by a panel of three researchers from the fields of science communication, communication, and popular culture. They examined the lyrics looking for scientific and technological terms, scientific metaphors, and/or expressions of scientific implications, and then categorized them as scientific activity or products, scientific research subjects, or cultural idioms. In those 377 songs, the researchers found 858 science words or phrases.
“Crowd” and “cloud” computing are exciting new technologies on the horizon, both for computer science types and also for us STS-types (science and technology studies, that is) who are interested in how different actors put them to (different) uses. Out of these, crowd computing is particularly interesting — as a technique that both improves artificial intelligence (AI) and operates to re-organize work and the workplace. In addition, as Lilly Irani shows, it also performs cultural work, producing the figure of the heroic problem-solving innovator. To this, I want to add a another point: might “human computation and crowdsourcing” (as its practitioners call it) be changing our widely-held ideas about experts and expertise?
Here’s why. I’m puzzled by how crowdsourcing research both valorizes expertise while at the same time sets about replacing the expert with a combination of programs and (non-expert) humans. I’m even more puzzled by how crowd computing experts rarely specify the nature of their own expertise; if crowdsourcing is about replacing experts, then what exactly are these “human computation” experts themselves experts on? Any thoughts, readers? How might we think about the figure of the expert in crowd computing research, given the recent surge of public interest in new forms of — and indeed fears about — this thing called artificial intelligence?
A book I wrote, Developer’s Dilemma [Press, Amazon Physical Book, Amazon Kindle, iBooks], was recently published by MIT Press. It is an ethnography that explores the secretive everyday worlds of game developers working in the global videogame industry. There is an excerpt of the book over at Culture Digitally if you’re interested in checking out some of the words prior to making a commitment to the rest of the text.
But I didn’t really want to start this year off just plugging my book. I mean, I did plug it. Just then. You should check it out. But that isn’t the point of this post. I recently Skyped into Tom Boellstorff‘s graduate seminar to discuss the book. One of the questions they asked me had to do with “game talk” and if I thought game talk had to do more with boundary policing than it had to do with actually having real utility and functionality. Game talk, in essence, is the use of game names as a shorthand means by which to reference the rather complex mechanics and ideas that set certain games apart. It was a wonderful question, because in the book I write:
Deflategate, or Ballghazi, and the Conundrum of Expertise (or: why anthropologists should write about football)
It is the week of Super Bowl Sunday and I live with a Patriots fan. For the last two weeks all serious conversation in our house has revolved around some aspect of the upcoming game. Unless you have been living under a rock (or inside a book), you can probably guess that most of our conversations center around why a set of footballs used by the Patriots during the AFC Championship game were found to be under the minimum psi level specified by the NFL. Were the Patriots cheating by manually deflating footballs? Or is there a “natural” explanation for the deflation?
The interesting question from an STS perspective, and the hinge which cheating allegations revolve around, is whether or not the atmospheric conditions at the AFC championship game could have caused a football to deflate what the NFL has called “a significant amount.” The question is a thorny one because it is entirely unclear who counts as an expert on football deflation, where one might turn to find an expert opinion, or even what criteria might be appropriate in determining who is, or is not, an expert on football deflation. Worse, how might one find a deflation expert who does not have a rooting interest for or against the Patriots at this late date? In short, who may enunciate the truths of football deflation?
Patriots head coach, and noted gridiron alchemist, Bill Belichick was the first to turn to science for an explanation. Like a modern day Boyle, he held a press conference in which he detailed an experiment conducted at the Patriots facility which he claimed demonstrated that natural conditions caused “significant” football deflation at the AFC Championship game. His explanation was detailed and involved a special method of preparing the football for play (that is, getting the correct feel for the quarterback) that can change the psi level without manual deflation.
As the co-chairs of CASTAC, we’re taking this opportunity to thank you for visiting The CASTAC Blog and to share our plans for 2015 and beyond! But first, we’d like to introduce ourselves.
I’m Jenny Carlson, continuing co-chair of CASTAC. For those new to CASTAC and its blog, I’m a visiting assistant professor of anthropology at Southwestern University, as well as a visiting research fellow at Rice University’s Center for Energy and Environmental Research in the Human Sciences. I work on the everyday, affective dimensions of energy transitions in Germany and, more recently, in the United States. I focus on ordinary structures of feeling at sites of small-scale energy development, exploring how sentiments shape infrastructures for producing energy and engaging in politics. My aim is to theorize how the politics of energy unfolds among those who live at sites of energy development but don’t formally participate in these projects and, going from this vernacular politics, to better understand how site-specific dynamics push back against policy projections, offering a more nuanced perspective on the social underpinnings of participation in areas of rapid technoscientific development.
And I’m Nick Seaver, writing from UC Irvine, where I’m a PhD candidate in anthropology and a researcher with the Intel Science and Technology Center for Social Computing. I succeeded longtime co-chair Jennifer Cool, whose hard work has enabled our interest group to not only survive, but thrive as part of the AAA’s General Anthropology Division. I research the development of algorithmic recommender systems for music — yes, like Pandora — among a broad network of academic and corporate researchers, engineers, and scientists in the US. I’m very interested in the resonances between these algorithmic approaches to “culture” and those from anthropology’s past, so I am also researching the history of computing in sociocultural anthropology. My goal is to gain some analytical purchase for anthropologists on those things we call “big data” or “algorithms” — to enhance our ability to make critiques that are informed and have impact, and to recognize the continuities between these “new” phenomena and older technologies we are more familiar with.