Years ago a colleague commented that the AAA meetings were becoming, well, a bit predictable. There would probably be scores of papers on social injustice expressed through ethnicity, race, gender, nationalism, class, and other familiar socio-cultural variables. I have spoken in my own work about how we must begin including, in a more systematic way, notions of injustices based on technological affiliations and values. But even if our recognizable list were expanded further, it still leaves anthropology operating within a particular paradigm of investigation. This paradigm might be conceptualized, as Lyon-Callo (2013) puts it, as a project of “critical thinking,” in which anthropologists as educators engage in “critically [problematizing] common sense things like race, class, gender, sexuality, family structures, migration and trade policies.” He writes quite insightfully about these patterns in his article, “Teaching for Hope?” which appeared in Anthropology News (January/February, 2013). I will extrapolate on these ideas and refer to this model as the “critical thinking paradigm.” (If you don’t like the word “paradigm” you can substitute the word, “orientation”).
Lyon-Callo argues that the critical thinking paradigm in pedagogy comes close to presuming ignorance of these issues on the part of all students. In anthropology, this paradigm is often treated as a form of “secret knowledge” that only we as experts can see. It is up to us to reveal this knowledge as well as the cultural and political conditions under which it becomes hidden. However, he argues that today’s students are different. Many of them are personally familiar with injustices such as class exploitation and racism. In the western Michigan area where Lyon-Callo teaches, students have direct experience with class and poverty issues. Even when the critical thinking paradigm remains powerful, Lyon-Callo observes many students leaving his classroom with a sense of hopelessness and a “what do we do now?” feeling. Lyon-Callo is concerned that this orientation will just produce a legion of pessimists.
This article obviously made an impact on me, as my colleague and I also observed anthropology’s patterned pessimism. Certainly many studies show that if you seek negative patterns you will find them—and only them. Books such as The Happiness Advantage (2010), which one of my students recommended, argue that it is important to seek out positive ideas and messages, even if they are not immediately visible. The exercise should not be done in a vacuous, Pollyanna way, but in a way that helps create tangible change, instead of focusing one’s entire lens on problems that initially feel intractable.
Similarly, Lyon-Callo looks to inspiration from JK Gibson Graham and Stephen Healy, who recommend rejecting the idea that exploitation is inevitable and “work instead toward producing a politics of possibilities.” Some might read in this the resurrection of an age-old debate between applied and basic research. Do we have the right to interfere in other people’s lives on this level? But the better question is, can we continue to morally ignore all the things we might do to help people move beyond their situation?
For Lyon-Callo’s students at Western Michigan University, ideas about exploitation and the failure of capitalism are all too real. Do they really need a continued stream of pedagogy filled with the attitude adjustment of critical thinking? Maybe some do, but many others are experiencing it first hand. For many students, problems are so chronic that, according to Lyon-Callo, “The fantasy of the American Dream has been replaced with a fantasy of the loss of the middle class as inevitable.” There is really no need to upend these students’ common sense—they are not the children of privilege that need a new world view. In response, he has turned his pedagogical focus toward imagining tangible change in his students’ lives through creative solutions, such as cooperativism, and other problem-solving, novel approaches.
I like the way he advocates for a “politics of possibilities,” and I too am interested in how imagination and visions of the future might pave the way for alternative approaches to doing anthropology. The vision described here goes beyond the simple debate about applied versus basic anthropology. At their core, these ideas speak more broadly to the orientation of an entire discipline, one which advocates moving beyond observing problems to turn its lens toward collecting data about what is going right in the world.
Could it be that my colleague and I recognized the pessimistic panels at AAA because that is what we were primed to see? We are quite well aware that anthropology is a huge discipline with many projects that are obviously complex and involve more than reiterating a list of patterned injustices. But it feels as though there are, at least, “hot buttons” that tend to get pressed more than others on particular topics when viewed through an anthropological lens. Perhaps it is time to change the paradigm away from only “critical thinking” and analysis.
The idea is not that we are abandoning basic research on social injustice; clearly these projects will and must continue. Just because people are sensitive to one thing, such as economic injustices, does not mean they understand all the other means of discrimination. The economically oppressed, for example, may not understand issues of sex and gender, or what it might mean to feel prejudice as a transgendered individual. Anthropology deals with an ever-shifting kaleidoscope of issues. Further, injustices continue to happen all over the world in places that dominant populations continue to ignore.
Critical thinking and exposure of hidden problems are not going away. Nevertheless, the suggestion here is that it is time also to embrace and incorporate a new orientation toward a future that hasn’t yet occurred—and doesn’t have to. It is time to turn our orientation in part toward a future anthropology that is a hopeful anthropology.
I look forward to having my own orientation expanded through the stories and research projects that will hopefully appear on The CASTAC Blog in the coming months.
As I conclude a semester teaching anthropology of technology, one of my favorite themes has to do with how people perform affiliations to technologies, as well as related beliefs, practices, and values. In that spirit, I’d like to repost here, on The CASTAC Blog, a brief summary of some themes I’ve developed and worked with in order to understand the relationship between technology and identity. This post was originally written for Savage Minds, but I’d like to re-post it here to continue the conversation among folks directly researching issues of anthropology and technology. As always, comments welcome!
There’s a new sociological variable in town, one which I call performing technical affiliation. Technically speaking, it is not a new way of thinking about identity. For many years, perhaps millennia, people have enacted aspects of identity by interacting with and through technologized objects, forms of knowledge and related practices and values. Nevertheless, technical affiliation is not recognized on the same level of analytical importance as are traditional variables—such as class, sex, gender, ethnicity, and social race—that are most often cited in anthropological studies of sociality. It is time that technical affiliations are brought more systematically into analyses of identity and negotiations of the self.
Performing technical affiliation means displaying in words or actions, alliances to objects, values, beliefs, or practices that are often assumed to be associated with particular technical cultures (Lange 2003, 2011). A basic example might be someone declaring, “I can’t live without my iPhone!” meaning that they prefer this device and its interactional implications over those offered by other devices or other brands of mobile phone. When people affiliate toward something, they also tend to affiliate away from something else. Performances may be much more subtle and complex. They refer to more than purchasing decisions (which are of course laden with many other beliefs). Performances can indicate how people accomplish being a competent, moral person in the world. For instance, some people believe that learning about technology is best accomplished in a self-directed way, rather than through taking classes in schools. How one should learn to use technical systems, or how one should share information through media are important aspects of everyday identity performance. Performing technical affiliation routinely occurs in offline, as well as online contexts.
The concept draws on Goffman’ (1959) notion of performing the self in everyday life, but does not imply a simple binary that equates performances with being “onstage” versus hiding a more true self “offstage.” Such a notion has often simplistically been applied to studies of computer-mediated communication to dichotomize online (onstage) versus offline (offstage) behavior. But writing many years ago, Goffman (1963: 9) demonstrated that such an assumption over determines how much identity information is actually shared in person. Speaking about in person interaction, he used the term “virtual” identity to refer to incorrect assumptions that people impute onto others, such as assuming they have never been in prison, have never had a depression, or have never harbored other stigmas. A binary application of the performance concept also under determines what identity information is shared online. Studies too numerous to list here have shown how much identity information is given and given off (in Goffman’s sense) in online contexts.
The concept of performing technical affiliation instead emphasizes Goffman’s (1981) work on footing, which acknowledges that people may exhibit different levels of intensity or commitment to beliefs and practices. Some people may be animating someone else’s original statements and technologically-inflected worldviews. Others may be the authors or originators of such beliefs, and hold them to be very influential in their everyday decision making. The concept is purposefully broad to accommodate many levels of affiliation. An analogy may be drawn to the metaphor of affiliation to a club. One person may receive the newsletter and read it now and again; another person may be the club’s president.
Another vignette may illustrate the concept. Years ago, I gave a talk at the American Anthropological Association meeting. At one point, a speaker who was using a laptop PC struggled to get his audio-visuals to display properly. Another person on the panel quipped, “You should have used a Mac.” A few knowing chuckles traveled around the room. Later, after hearing my talk, this panelist told me that his quip was not a good example of performing technical affiliation, because he had no personal affiliation to the Macintosh computer. I assured him that it was an excellent example.
Recall that the concept takes into account different levels of performativity and varying commitments to the affiliations contained therein. His remark performed affiliation to the idea that Macintosh computers are better for manipulating media than are PCs. He was animating a notion that was commonly held (although may or may not be true), among Macintosh supporters, and others who believe it. His was a performance that would not be intelligible if people did not think that this belief was common. The joke would unintelligibly fall flat if everyone “knew” that PCs and Macs were equally effective for working with media. He himself does not have to believe the idea in order for the joke/performance to “work.”
Performing technical affiliation is a part of human life; people cannot get particular jobs or have certain kinds of successful relationships if they do not convincingly display particular orientations to specific technologies or technically-inflected worldviews and values. But sometimes performing technical affiliation can be problematic not only for individuals but society as a whole. For example, in her classic ethnography of physicists, Traweek (1988) noted a competitive tension between the theoretical physicists and the experimental physicists in an advanced research lab. The latter designed experiments to test the theories of the former.
Advances in physics could not proceed without their collaboration, but identity displays often coded in-group members as superior to out-group members. A theoretical physicist told Traweek that it was appropriate for an anthropologist to study such a “primitive tribe” as experimentalists. Each group learned to display a “studied disregard for each other’s judgment” (Traweek 1988: 112). One empirical question is, to what extent do such displays advance or impede the production of human knowledge? How might their collaboration change if their cultural disregard was seen as a performance of technical affiliation that, if changed, could advanced the field much further?
It may be objected that technical affiliations only apply to specialized groups or elite technologists. But such an assumption ignores the anthropological record, and how technologies influence how people conceive of the self and how they choose to be a moral person in the world. For example, consider Gershon’s (2010) book on breaking up on the social network site of Facebook. She argues that people held definite ideas about how one should end a romantic relationship. Using particular media was seen to reflect something important about the morality and sensitivity of the person breaking up. If a person chose to break up over Facebook rather than in person, people used this information to make moral judgments about them. Their media choices often had more salience in determining a person’s social character in those situations than any of the other traditional identity variables. To argue that Facebook is or is not a true “technology” are, in and of themselves, performances of technical affiliation.
Another objection may be that people do not consciously orient toward technical affiliations in everyday life. Yet, the impact of any identity variable such as class, ethnicity, gender, and so forth must be empirically shown to be important in analyses of social behavior. Just because people do not verbalize or understand the impact of their affiliations is not sufficient proof that the variable is unimportant for understanding contemporary self-construction. The same argument may be forwarded with regard to other variables, such as class. Americans often say they are in the “middle class” and do not necessarily orient around class. Yet these elisions do not prove that class is irrelevant for people’s social negotiation of the self, nor that society is “class-blind” with regard to determining socio-economic opportunities.
Perhaps hesitancy about adopting the construct exists because identity variables such as gender and class may influence people’s technical affiliations. But such variables are not predictive of technical affiliations. Knowing that someone is a man of a certain economic class, for instance, does not determine his views on whether computer platforms should all be open source, or whether he should take certain drugs to address health issues, or whether learning the programming language of Python is a good use of his time. Certainly, technical affiliations have interactions with other variables, as is the case with traditional identity variables. For example, in reaction to second wave feminism, which explored universalized experiences of womanhood, third wave feminists convincingly showed that other variables such as ethnicity and class brought much to bear on the experiences of being a woman in particular cultural groups. The same is true of technical affiliations. Important interactions between such affiliations and other identity variables should be empirically studied to broaden understanding of how technologized worldviews impact self-construction.
The time is right to acknowledge what has been discussed for a quite some time. As long-standing cyborgs, people’s technologized identities have historically been part of the human condition (Haraway 1991). Affiliations to technologies and related values and world views speak volumes about who we are as people, as members of cultures, and as individuals. Technical affiliations are crucial aspects of social identity. Scholars should systematically incorporate them in analytical studies of social behavior as routinely as any other traditional sociological variable.
Gershon, Ilana. 2010. The Breakup 2.0: Disconnecting Over New Media. Ithaca: Cornell University Press.
Goffman, Erving. 1981. Forms of Talk. Philadelphia: University of Pennsylvania Press.
Goffman, Erving. 1963. Stigma: Notes on the Management of a Spoiled Identity. New York: Simon & Schuster Inc.
Goffman, Erving. 1959. The Presentation of Self in Everyday Life. New York: Doubleday.
Haraway, Donna J. 1991. Simians, Cyborgs, and Women: The Reinvention of Nature. New York: Routledge.
Lange, Patricia G. 2011. Video-mediated Nostalgia and the Aesthetics of Technical Competencies. Visual Communication 10(1): 25-44.
Lange, Patricia G. 2003. Virtual Trouble: Negotiating Access in Online Communities. Ph.D. Dissertation. University of Michigan. Available from UMI at: http://disexpress.umi.com/dxweb.
Traweek, Sharon. 1988. Beamtimes and Lifetimes: The World of High Energy Physicists. Cambridge: Harvard University Press.
January 15th, 2013, by Patricia G. Lange Comments Off
Although anthropologists have been working with large-scale data sets for quite some time, the term “big data” is currently being used to refer to large, complex sets of data combined from different sources and media that are difficult to wrangle using standard coding schemes or desktop database software. Last year saw a rise in STS approaches that try to grapple with questions of scale in research, and the trend toward data accumulation seems to be continuing unabated. According to IBM, we generate 2.5 quintillion bytes of data each day. This means that 90% of the data in the world was created during the last 2 years.
Big data are often drawn and aggregated from a very large variety of sources, both personal and public, and include everything from social media participation to surveillance footage to consumer buying patterns. Big data sets exhibit complex relationships and yield information to entities who may mine highly personal information in a variety of unpredictable and even potentially violative ways.
The rise of such data sets yields many questions for anthropologists and other researchers interested both in using such data and investigating the techno-cultural implications and ethics of how such data is collected, disseminated, and used by unknown others for public and private purposes. Researchers have called this phenomenon the “politics of the algorithm,” and have called for ways to collect and share big data sets as well as to discuss the implications of their existence.
I asked David Hakken to respond to this issue by answering questions about the direction that big data and associated research frameworks are headed. David is currently directing a Social Informatics (SI) Group in the School of Informatics and Computing (SoIC) at Indiana University Bloomington. Explicitly oriented to the field of Science, Technology, and Society studies, David and his group are developing a notion of social robustness, which calls for developers and designers to take responsibility for the creation and implications of techno-cultural objects, devices, software, and systems. The CASTAC Blog is interested in providing a forum to exchange ideas on the subject of Big Data, in an era in which it seems impossible to return to data innocence.
Patricia: How do you define “big data”?
David: I would add three, essentially epistemological, points to your discussion above. The first is to make explicit how “Big Data” are intimately associated with computing; indeed, the notion that they are a separate species of data is connected to the idea that they are generated more or less “automatically,” as traces normally a part of mediation by computing. Such data are “big” in the sense that they are generated at a much higher rate than are those large-scale, purpose-collected sets that you refer to initially.
The second point is the existence of a parallel phenomenon, “Data Science,” which is a term used in computing circles to refer to a preferred response to “Big Data.” Just as we have had large data sets before Big Data, so we have had formal procedures for dealing with any data. The new claim is that Big Data has such unique properties that it demands its own new Data Science. Also part of the claim is that new procedures, interestingly often referred to as “data mining.” will be the ones characteristic of Data Science. (What are interesting to me are the rank empiricist implications of “data mining.”) Every computing school of which I know is in the process of figuring out how to deal with/“capitalize” on the Data Science opportunity.
The third point is the frequently-made claim that the two together, Big Data and Data Science, provide unique opportunities to study human behavior. Such claims become more than annoying for me when it is asserted that the Big Data/Data Sciences uniquenesses are such that those pursuing them need not pay any attention to any previous attempt to understand human behavior, that only they and they alone are capable of placing the study of human behavior on truly “scientific” footing, again because of their unique scale.
Patricia: Do you think that anthropologists and other researchers should use big data, for instance, using large-scale, global information mined from Twitter or Facebook? Do you view this as “covert research”?
David: We should have the same basic concern about these as we would any other sources of data: Were they gathered with the informed consent of those whose activities created the traces in the first place? Many of the social media sites, game hosts, etc., include permission to gather data as one of their terms of service, to which users agree when they access the site. This situation makes it hard to argue that collection of such data are “covert.” Of course, when such agreement has not been given, any gathered data in my view should not be used.
In the experience of my colleagues, the research problem is not so much the ethical one to which you refer so much as its opposite—that the commercial holders of the Big Data will not allow independent researchers access to it. This situation has led some colleagues to “creative” approaches to gathering big data that have caused some serious problems for my University’s Institutional Review Board.
In sum, I would say that there are ethical issues here that I don’t feel I understand well enough to take a firm position. I would in any particular case begin with whether it makes any sense to use these data to answer the research questions being asked.
Patricia: Who “owns” big data, and how can its owners be held accountable for its integrity and ethical use?
David: I would say that the working assumption of the researchers with whom I am familiar is either the business whose software gathers the traces or the researcher who is able to get users to use their data gathering tool, rather than the users themselves. I take it as a fair point that such data are different from, say, the personal demographic or credit card data that are arguably owned by the individual with whom they are associated. The dangers of selling or similar commercial use of these latter data are legion and clear; of the former, less clear to me, mostly because I don’t know enough about them.
Patricia: What new insights are yielded by the ability to collect and manipulate multi-terrabyte data sets?
David: This is where I am most skeptical. I can see how data on the moves typically made by players in a massive, multiplayer, online game (MMOG) like World of Warcraft ™ would be of interest to an organization that wants to make money building games, and I can see how an argument could be made that analysis of such data could lead to better games and thus be arguably in the interest of the gamers. When it comes to broader implications, say about typical human behavior in general, however, what can be inferred is much more difficult to say. There remain serious sampling issues however big the data set, since the behaviors whose traces are gathered are in no sense that I can see likely to be randomly representative of the population at large. Equally important is a point made repeatedly by my colleague John Paolillo, that the traces gathered are very difficult to use directly in any meaningful sense; that they have to be substantially “cleaned,” and that the principles of such cleaning are difficult to articulate. Paolillo works on Open Source games, where issues of ownership are less salient that they would be in the proprietary games and other software of more general interest.
Equally important: These behavioral traces are generated by activities executed in response to particular stimulations designed into the software. Such stimuli are most likely not typical of those to which humans respond; this is the essence of a technology. How they can be used to make inferences about human behavior in general is beyond my ken.
Let me illustrate in terms of some of my current research on MMOGs. Via game play ethnography, my co-authors (Shad Gross, Nic True) and I arrived at a tripartite basic typology of game moves: those essentially compelled by the physics engine which rendered the game space/time, those responsive to the specific features designed into the game by its developers, and those likely to be based on some analogy with “real life” imported by the player into the game. As the first two are clearly not “normal,” while the third is, we argue that games could be ranked in terms of the ratio between the third and the first two, such ratio constituting an initial indicator of the extent of familiarity with “real life” that could conceivably be inferred from game behavior. Perhaps more important, the kinds of traces to be gathered from play could be changed to help make measures like this easier to develop.
Patricia: What are the epistemological ramifications of big data? Does its existence change what we mean by “knowledge” about behavior and experience in the social sciences?
David: I have already had a stab at the first question. To be explicit about the second: I don’t think so. There are no fundamental knowledge alterations regarding those computer mediations of common human activity, and we don’t know what kind of knowledge is contained in manipulations of data traces generated in response to abnormal, technology-mediated stimuli.
Patricia: boyd and Crawford (2011) argue that asymmetrical access to data creates a new digital divide. What happens when researchers employed for Facebook or Google obtain access to data that is not available to researchers worldwide?
David: I find their argument technically correct, but, as above, I’m not sure how important its implications are. I am reminded of a to-remain-unnamed NSF program officer who once pointed out to a panel on which I served that NSF was unlikely to be asked to fund the really cutting edge research, as this was likely to be done as a closely guarded, corporate secrete.
Patricia: What new skills will researchers need to collect, parse, and analyze big data?
David: This is interesting. When TAing the PhD data analysis course way back in the 1970s, I argued that to take random strolls through data sets in hopes of stumbling on a statistically significant correlation was bad practice, yet this is in my understanding, the approach in “data mining.” We argue in our game research that ethnography can be used to identify the kinds of questions worth asking and thus give a focus, even foster hypothesis testing, as an alternative to such rampant empiricism. Only when such questions are taken seriously will it be possible to articulate what new skills of data analysis are likely to be needed.
Patricia: How can researchers insure data integrity across such mind-boggling large and diverse sets of information?
David: Difficult question if dealing with proprietary software; as with election software, “trust me” is not enough. This is why I have where possible encouraged study of Open Source Projects, like that of Giacomo Poderi in Trento, Italy. Here, at least, the goals of designers and researchers should be aligned.
Patricia: To some extent, anthropologists and other qualitative researchers have always struggled to have their findings respected among colleagues who work with quantitative samples of large-scale data sets. Qualitative approaches seem especially under fire in an era of Big Data. As we move forward, what is/will be the role and importance of qualitative studies in these areas?
David: As I suggested above, in my experience, much of the Data Science research is epistemologically blind. Ethnography can be used to give it some sight. By and large, however, my Data Science colleagues have not found it necessary to respond positively to my offers of collaboration, nor do I think it likely that either their research communities of funders like the NSF, a big pusher for Data Science, will push them toward collaboration with us any time soon.
Patricia: What does the future hold for dealing with “big data,” and where do we go from here?
David: I think we keep asking our questions and turn to Big Data when we can find reason to think that they can help us answer them. I see no reason to jump on the BD/DS bandwagon any time soon.
On behalf of The CASTAC Blog, please join me in thanking David Hakken for contributing his insights into a challenging new area of social science research!
Patricia G. Lange
The CASTAC Blog
The CASTAC community joined together in 2012 to launch this blog and begin dialogue on contemporary issues and research approaches. Even though the blog is just getting off the ground, certain powerful themes are already emerging across different projects and areas of study. Key themes for the coming year include dealing with large data sets, connecting individual choices to larger economic forces, and translating the meaning of actions from different realms of experience.
Perhaps the most visible trend on our minds right now involves dealing with scale. How can anthropologists, ethnographers, and other STS scholars address large data sets and approaches in research and pedagogy, while also retaining an appropriate relationship to the theories and methods that have made our disciplines strong? As we look ahead to 2013, it would seem that a big question for the CASTAC community involves finding creative and ethical ways to deal with phenomena that range from the overwhelmingly large to the microscopic, in order to provide insight and serve our constituents in research and teaching.
Discussing large-scale forays into education and research
In the past two weeks in her posts on MOOCs in the Machine, Jordan Kraemer, our dedicated Web Producer, has been reflecting on how higher education is grappling with MOOCs, or “massive open online classes,” which open up opportunities to those who have been shut out of traditional elite institutions. At the same time, serious questions emerged about the ramifications of trade-offs between saving money and providing high-quality education. Kraemer points out that much of the debate ties into larger arguments about why it is that people have been shut out of education and how concentration of wealth and the neoliberalization of the university are challenging the old equation of supporting open-ended research that ultimately strengthens and supports teaching. She proposes new forms of graduate education in which recent graduates are supported by their universities with teaching jobs, to complete teaching experience, transfer teaching loads from full-time faculty, and support graduate students as they transition into full-time positions.
Part of the issue with MOOCs has to do with questions of scale, and how or whether individual lectures and course preparation can be generalized to large-scale audiences in ways that provide solid instruction without compromising quality. Higher-education depends upon staying current with research, and so far, we do not have enough evidence to support the idea that MOOCs will work or will address all of the concerns emerging from the neoliberalization of the academy. Those of us interested in online interaction and pedagogy will be watching this space closely in the coming year.
Questions of scale also came into play with Daniel Miller’s discussion of doing Eight Comparative Ethnographies. Miller argues that doing several ethnographies at the same time will enable comparative questions that are not possible when investigating one site alone. He provides an example from social network sites. He asks, to what extent are particular behaviors the product of a type of site, a single site, or the intersection of cultures in which a site is embedded? Is the behavior so because it is happening on Facebook or because the participants are Brazilian? A comparative study enables a level of analysis that is more inclusive than that derived from a single study. Expanding scale without compromising the traditions and benefits of ethnographic work remains a challenge for these and other large-scale projects in the future, which have the potential to provide crucial insights.
Making small-scale choices visible
As one set of researchers bring up issues with regard to enormously large-scale education and research, other STS participants on The CASTAC Blog are dealing with the opposite issue, which involves grappling with how the dynamics of extremely personal and individualistic acts—such as the donation of sex cells—interact with large-scale economic and cultural forces. In her post on The Medical Market for Eggs and Sperm, Rene Almeling, the winner of the 2012 Forsythe Prize, provides an inside look into how human beings’ donations of sex cells are connected to much larger economic forces that play out differently for women and men. Women are urged to regard egg donation as a feminine act of a gift; men are encouraged to see donation as a job. Almeling ties our understanding of what might be an individual act into economic forces, as well as gendered, cultural expectations about families and reproduction. Gendered framings of donation not only impact the individuals who provide genetic material, but also strongly influence the structure of the market for sex cells.
Another key issue on our minds has to do with dealing with personal responsibility and showing how individual choices impact much larger social and economic forces in finance, computing, and going green.
In his post, On Building Social Robustness, David Hakken raises the question of how individuals contributed to large-scale economic and social crises, such as the recent disasters in the world of finance. His project is informed by work that is trying to deal with the first “5,000 years” in the history of debt. He proposes developing a notion of social robustness, parallel to the idea of the technical notion of robustness in computer science.
His work provides an intriguing use of ideas from people whom we study, and applying them as an inspiration for making social change. When Hakken asks about the extent to which computing professionals are ethically responsible for the financial crisis, he is proposing a way of asking how a large-scale disaster can be traced to more individual, micro-units of action. By investigating these connections, his project informs a conversation that is increasingly picking up steam in the area of the anthropology of value.
Hakken’s reflections are especially haunting as he warns of the difficulties of building a career in anthropology and STS. As he is moving towards retirement, his perspective is especially valued in our community. As an antidote to more provincial institutional perspectives, he urges a more consolidated and community approach that involves supporting each other in doing the important work that the CASTAC community has the potential to achieve.
Questions of scale and responsibility are once again intertwined in David J. Hess’s post on Opening Political Opportunities for a Green Transition. Hess points out that a non-partisan political issue has become partisan despite the fact that the planet has now surpassed a carbon dioxide level that it has not had for at least 800,000 years! But because change is imperceptibly slow to the human eye, politics is allowed to complicate change. Hess has worked to investigate what he calls the “problem behind the problem,” which involves the lack of political will to address environmental sustainability and social fairness, which considerably worsens the environmental problem itself. He provides real solutions through an ambitious three-part series of books that propose “alternative pathways” or social movements centered on reform in part through the efforts of the private sector.
Notably, personal experiences in anthropology inform Hess’s work. Although he is in a sociology department and in an energy and environment institute, he points out that an anthropological sensibility continues to inform his thinking. While the discourse on these issues has traditionally revolved around a two party system, Hess’s more anthropological approach makes visible other ideologies such as localism and developmentalism that may pave a more direct path to “good green jobs” and a more sensitive and responsible green policy. Again interacting with questions of scale, Hess’s notions of responsibility are grounded in understanding the “broad contours” of the “tectonic shifts” of ideology and policy that are underway in working toward a green transition in the United States and around the world. Without real action, however, his prognoses remains pessimistic.
Translating phenomena across different realms of experience
A theme that also emerged from our nascent blog’s initial posts had to do with understanding the ramifications of processing one realm of experiencing by using metaphors and concepts from another. In her post on the Anthropological Investigations of MIME-NET, Lucy Suchman explores the darker side of entertainment and its relationship to military applications. She investigates how information and communication technologies have “intensified rather than dissipated” what theorists have described as the “fog of war.”
The problem is partly one of translation. How is it possible to maintain what military strategists call “situational awareness,” which has to do with maintaining a constant and accurate mental image of relevant tactical information. Suchman is studying activities such as The Flatworld Project, which bring together practitioners from the Hollywood film industry, gaming, and other models of immersive computing to understand these dynamics. Such a project also involves analyzing how such approaches “extend human capacities for action at a distance,” and present ethical challenges to researchers as they grapple with military realms and connecting seemingly disparate but interrelated areas such as war and healthcare.
Lisa Messeri’s post, Anthropology and Outer Space, offers an absolutely fascinating look into human conceptualization of place. She asks, why should earthlings be concerned about what is happening on Mars? Her work focuses on how “scientists transform planets from objects into places.” Significant milestones in space exploration such as the passing of Venus between the Earth and the Sun (not scheduled to do so again until 2117) and the landing of the Mars rover, Curiosity, provide rich areas to mine for understanding cultural notions of place and human exploration. Curiosity has its own Twitter account (!) and tweets freely about its experience of “springtime” in its southern hemisphere. Messeri argues that this kind of language “bridges” our worlds in that Curiosity somehow seems to experience something that is familiar to humans—springtime. Scientists are now studying things that are so far away that telescopes cannot take an image of them. Somehow, these “invisible” objects become familiar and complex. Planets begin to seem like places because of the way in which language “makes the strange familiar,” and bridges the experience between events on an exoplanet and life on Earth.
Astronomers become place makers, and observing these processes shows how spaces become “social” even as Messeri argues, “humans will never visit such planetary places.” Messeri shows how such conceptualizations can lead to the spread of erroneous scientific rumors that get reported on national news organizations. Her work shows not only how knowledge production is compromised by the use of such metaphors but also provides an intriguing look at how humans process invisible objects through the cultural production of imagined place.
Tune in next week!
Given that questions of scale were on our minds in 2012, it is especially fitting that we launch 2013 with a discussion about Big Data, and the challenges and opportunities that emerge when entities collect and combine huge data sets that are far too large to handle through ordinary coding schemes or desktop databases. Social scientists, technologists, and other researchers must grapple with numerous issues including legibility, data integrity, ethics, and usability. I am particularly pleased that David Hakken agreed to be interviewed by The CASTAC Blog to discuss his views. Next week, he provides fascinating insights into what the future holds for dealing with Big Data!
Before signing off, I would like to thank everyone for their participation in The CASTAC Blog, especially those who wrote posts, left comments, read articles, and tweeted our posts to the world. I very much appreciated everyone’s participation. The richness of the posts makes it too difficult to adequately cover all the content of the past year in one commentary, but rest assured that everyone’s post is contributing to the conversation and is valued by the CASTAC community.
In an effort to include more voices and keep a continuing flow of content, The CASTAC Blog is now seeking a core group of “frequent” contributors to keep pace with new developments in this space in 2013. Notice that I use the term “frequent” sparingly—even a few posts throughout the year makes you a frequent contributor. Please consider sharing your thoughts and views with the CASTAC community. If you would like to join in, please email me at: email@example.com.
I look forward to an interesting and productive year ahead!
Patricia G. Lange
The CASTAC Blog
Greetings! Welcome to the CASTAC Blog, an exchange for ideas and information about science and technology as social phenomena. We hope to build on a thriving community of scholars from around the world who are concerned about the implications of technologized products and worldviews that are impacting human beings and other forms of life. Our focus is interdisciplinary and welcoming to a variety of scholars interested in a diverse set of research issues, ethics, and impacts of technology on increasingly blended forms of humans and machines in contemporary life.
The CASTAC Blog was created by Patricia G. Lange, Jennifer Cool, and Jordan Kraemer, who are all members of the Committee on the Anthropology of Science, Technology, and Computing (CASTAC). CASTAC is a sub-committee of the General Anthropology Division (GAD) of the American Anthropological Association (AAA). For more than 20 years, CASTAC has had a thriving presence at AAA, as researchers have come together to exchange views about what it means to conduct anthropological research in technologized arenas. Sometimes the opportunities and challenges we face are very different, given that we research everything from nanotechnology to new media. In other instances, though, we face similar challenges, such as public perception of how we as researchers question the effects and processes of science, technology, and computing (the so-called “science wars”). Other challenges we often face include working in interdisciplinary terrain and receiving resistance from the academy or industry about our contributions. Many of us simply wish to geek out and connect with other people who are doing cool things in the intersection of anthropology and sociology and science and technology studies.
Our goal is to encourage dialogue—in a truly polyvocal space—on research findings, tools, new events, and social connections to others in this intersection of domains. We welcome contributions from interested parties within and outside of CASTAC to post about their research, contribute off-the-cuff comments or ask stimulating questions that can bring greater understanding to processes and products of humans’ engagement with technology.
Even writing a simple description of this domain presents challenges. The discipline of anthropology has exhibited a long-standing, anthropos-centric focus; but scholars within our community are already writing about the importance of microbes, biological organisms, and artificial life in ways that inevitably broaden the terrain of consideration of anthropological inquiry. Those of us engaged in research of new media have also pushed the boundaries of anthropological practice by following the “action” and going online to investigate new social formations that increasingly rely on mediated communication.
In an important way, we are all pushing the boundaries of anthropology. We wish to create a space where this kind of intellectual risk-taking is safe and welcome. I think we all realize that what we are doing today is, in fact, going to be the taken-for-granted anthropology of tomorrow. When I faced resistance from certain quarters about my dissertation project on MUDs (multi-user dimensions) and the social implications of tech talk, a wonderful mentor at the University of Michigan told me that I was ahead of my time and that my colleagues would catch up one day. We suspect many, if not all of us, have similar tales to tell, and the stakes are considerably higher in a number of technical and scientific areas. Happily, we have a community to hand that is ready and eager to hear what you have to say!
Consider this space a dialogue in progress that’s about promoting community both within and outside of CASTAC. We are interested in hearing many voices rather than gathering journal-ready copy. Scientific and humanistic insights need not be produced from the single peer-review journal path, as we all know. The backstage conversations often spark the big ideas, and provide much-needed support in challenging times.
Of course social spaces like this only work if everyone contributes in some way. After many years of being relatively quiet, CASTAC’s business meeting at AAA in the Fall of 2011 showed that many of us wish to continue to meet and keep a space alive for interacting with our colleagues in this space. We have devised The CASTAC Blog to accommodate different kinds of dialogue and contributions. We welcome submissions from all scholars in this area and people from different perspectives, including students, faculty, practitioners, policy makers, and other interested readers.
- People are encouraged to post about their initial observations, ongoing work, or research results in the Research section of the blog.
- Other people may wish to talk about methods or tools that they found useful or problematic in our Tools & Techniques section.
- Our section Beyond the Academy may be of particular interest to those who grapple with these issues in non-academic settings.
- We have also included a Member Sound Off section to encourage ideas about how the community can be improved, and to encourage personal statements of what it means to be part of a community like this.
What do you hope being part of this dialogue will bring? What can The CASTAC Blog, the organization of CASTAC or even other scholars in this space do to help you attain your goals? Join us!
COMING SOON! We have wonderful posts from Lucy Suchman, David Hakken, and David J. Hess in the pipeline, so stay tuned to the CASTAC Blog!
– Patricia G. Lange, Editor-in-Chief
We all know that robust tools can help facilitate research, but we do not always have the time to test the latest products and processes. Here’s a place to offer advice, suggestions, and ask for help on how to tackle specific problems. What software have you found helpful for capturing data, transcribing interaction, conducting research, or analyzing findings? What problems tend to come up? Are there techniques in conceptualization, mapping, coding or other stages of the research process that you have identified as particularly helpful? Feel free to share information about what worked and what didn’t when using technology to gain insight into your projects.