PUBLIC POLICY ANTHROPOLOGIST

Since at least the late 2000s, I have been observing – sometimes organizing, and sometimes participating in – diverse forums featuring different combinations of politicos, policy decision-makers, academics, and applied practitioners, which have broached the relationship between “culture” and “security,” sometimes in overlapping but often in notably different ways. At times, the purpose is to ascertain how new cultural developments might disrupt established security goals. At other moments, it is the other way around, with an emphasis upon ways new security priorities are driving cultural interventions. A previously obscure term – cultural security – is now in much wider use, even if it means different things to different people.

I am not alone. In 2009 the Aspen Institute put together a big-name event also dedicated to “culture and security.” In 2010 the National Intelligence Council hosted a meeting on the topic of “cultural diplomacy and security.” In 2011 the National Humanities Alliance sponsored an event addressing “national security and other global challenges through cultural understanding” at the Capitol Visitor Center. Also in 2011, the Wilson Center hosted a conference to promote interagency conversation on “culture in the military.” Early this year, Georgetown University hosted a Chatham House event on “cultural dialogue in East Asian security.” This past June in D.C., the Institute for Cultural Diplomacy hosted a “global dialogue about cultural diplomacy, national security and global risks.” And so on.

Below the surface of these frequent forums are multiple ongoing initiatives across the securityscape – and periodic efforts to organize them – for enhancing cultural capacity or for identifying key cultural factors of conflict. But beyond the U.S. military’s well-documented cultural turn, something more is percolating here. Less observed are the effects of a preoccupation with security upon the agendas of civilian cultural agencies and other non-traditional participants in security policy and practice.

We could describe this as two simultaneous trends: the securitization of culture and the enculturation of security. The first comprises attention by national security agencies in the U.S. and elsewhere to culture as one potential source of insecurity; in the process re-conceptualizing it in ways consistent with a security-centric worldview. This trend includes groups and countries that perceive the security of their own cultures as under constant existential threat. The second trend includes ways that culture, as a resource, has been applied in many different ways as a part of solutions to diverse problems of security. Often, it seems, security agencies promote the first trend while non-security actors respond by bolstering the second.

One arena in which the term – cultural security – has gained a foothold is in discussions of the strategic importance of preserving artworks, monuments, archaeological sites and artifacts when considering the implications for international affairs of the international art market, the antiquities trade, and the illegal looting or destruction of art and artifacts. This attention includes greater recognition by the U.S. military of the strategic value of capacity-building in heritage training, protection, and preservation, as a force multiplier, incorporated into stability operations, and in collaboration with civilian partners.

Efforts of heritage planning—emergency preparedness and response—also regularly coalesce in terms of the push and pull around “cultural property,” as increasingly defined by international law, as a basis of calls for repatriation, as a politicized resource of community or national identity, and as a source of conflict or its mitigation. If the historian David Lowenthal condemns the proliferation of these “heritage wars,” such developments indicate how cultural identity and related questions are now subject to an ongoing global process of securitization.

Reference to cultural security also points to distinct or diverging national security policies. If the term is not a part of the U.S.’s domestic security lexicon, it figures significantly in China’s. A search in Google Scholar for [cultural security + China] generated over 1,500 hits since the early 2000s, demonstrating a lively scholarly cottage industry in China around its cultural security. China’s approach to cultural security is often embodied in concepts from the Chinese martial arts, or wushu, which is regularly extolled as a resource for “safeguarding national cultural security.”

In 2011, the Central Committee of China’s Communist Party approved a decision to further develop the country’s cultural industry, improve citizens’ confidence in Chinese culture, and enhance its soft power, all understood as parts of the effort to protect China’s national “cultural security.” And earlier this year, President Hu Jintao made the case for China to bolster its cultural security and to “strengthen its cultural production to defend against the West’s assault on the country’s culture and ideology.” China’s Ministry of Culture includes Lady Gaga on a growing list of songs that cannot be legally downloaded because they “endanger national cultural security.” For China, cultural security is a national policy issue in ways it is not in the U.S.

If China’s government understands its national identity through a cultural security framework, one recent trend in international affairs has been to consider the sources of difficulties in multilateral cooperation to be, in significant part, cultural. As the conventional wisdom holds, particular national cultures lead to distinct policy worldviews which, in turn, inform differing assumptions underlying security goals. New joint efforts, therefore, encourage “cultural dialogue in international security” as a way to act internationally while not thinking universally, and to head off a “clash of values” provoked by “contrasting cultural approaches to security.” Other projects seek to be low-profile platforms promoting “strategic listening” and cooperative research on non-traditional threats – including the increased “securitization of identity” – by exploring the multiple ways culture can be “an important dimension of human security.”

Public agencies and non-profits in the U.S. active in “culture and the arts” – traditionally not so concerned with national security policies – now regularly consider what constructive role they too might play in the universe of possibilities presented when culture is brought to bear on problems of security and vice-versa. But it is not clear if there is such a role.

Safeguarding cultural property, cultural diplomacy, and the building of international applied humanities partnerships are three activities we might point to. But future cultural diplomacy efforts addressing the priorities of the security state would do well to consider how those priorities often problematically determine the range and shape of available cultural interventions.

Traditionally, cultural diplomacy aspires to a mixed bag of countering stereotypes, building relationships, improving dialogue, telling stories, creating spaces of commonality, or raising controversial issues, often across fraught geopolitical boundaries. The recent run of “Black Watch” at the Shakespeare Theater Co. in Washington D.C., which follows the fortunes of a Scottish regiment in Iraq, is a good example of theater crossing boundaries to address controversy generated by security decision-making.

Yet ours is a moment characterized by multilateral and political formulations of cultural property, whereby culture is conceived as a rivalrous, exclusive source of identity, existentially threatened, and with sharply defined boundaries to be defended and safeguarded. And “cultural security,” with its associated language of strategic value and threat assessments, appears to promote the manufacture of an increasing “climate of risk” vis-à-vis culture that seeks to solidify boundaries instead of enabling cross-over. In other words, aren’t cultural diplomacy and cultural security largely at odds?

Note: This post originally appeared on the Center for Public Diplomacy blog site: http://uscpublicdiplomacy.org/index.php/newswire/cpdblog_detail/risk_assessment_in_encounters_between_culture_and_security/

Amy Zalman recently proposed that “soft power” – as a conceptual frame for understanding global politics – is too narrow and has outlived its usefulness. Her provocation generated fruitful responses and suggests that we might be ready to stop treading water and move beyond our decade-long fixation with the term to new and more constructive places. Zalman rightly points to the costs of the partial privileging of the “soft” (e. g. cultural narratives, symbols, stories) at the expense of the “hard” (e. g. economic or military force), insisting that these two cannot be pried apart, even analytically, without diminishing appreciation for how power in fact works.

Complementing Zalman is Craig Hayden’s additional suggestion that her critique helps to shift attention to the myriad ways soft and hard power are connected and simultaneously expressed through the continued proliferation of diverse kinds of (often non-state) networks. The increasingly variegated facts of Castells’s “network society” make clear that networks mediate the distribution of meaning and value in ways demanding our attention.

Conjoined, these arguments present a compelling picture. They suggest the need to reframe our analysis of global politics in ways transcending distinctions of “soft” and “hard” while better accounting for the many entanglements of the “symbolic” with the “material.” This is particularly congenial to me, trained as a sociocultural anthropologist, since this discussion has been front and center in the discipline for some time. I too have promoted doing so in my own recent writing on cultural diplomacy.

Together, one question these discussions encourage is: How are stories meaningfully distributed across different kinds of networks and to what effect? Instead of inferring cultural consensus when identifying specific groups, for the practice of public diplomacy such questions help us to a more realistic appraisal of the variety of cultural accounts among people otherwise related.

At this juncture we can offer the inverse of Zalman’s argument about soft power: too often, ever more ubiquitous network analyses seem to privilege the “hard” over the “soft” to the detriment of our understanding of how networks work. Certainly in security policy and studies this is the case. We have seen a flood of so-called link analyses, where the game is always to identify connections between nodes in different networks, or who is connected to whom and how. The emphasis is upon the importance of the “hard” social facts of the shape and distribution of connections within and across networks, in order to identify key “information nodes,” “information brokers,” or, in the War on Terror, the “bad guys.”

Ann-Marie Slaughter’s recent call for more attention from U.S. foreign policy decision-makers to the ubiquity of “network centrality” is timely. But, while she notes in passing network “nutrients” – flows of goods, services, expertise, funding, and political support – she is most interested in the density of connections and positioning of networks. Likewise, a recent study in Nature on social influence across networks of Facebook users concluded that more frequent interactions between friend pairs – “strong ties” – have a much greater influence than do “weak ties” on a person’s behavior. Again, it is all about the facts of connection. We can further note how behavior, composed of empirically observable actions, is prioritized over cultural meaning or belief.

More attention has been given to identifying people, their behavior, their connections, and network nodes than has been given to how information is distributed across networks or what these symbols, values or stories mean to network participants.

The New York Times recently ran a story about researchers who used the computational tools of social network analysis to assess the historical or fictional sources of well-known epics like the Iliad. In other words, they were examining the relation between epic narratives and networks. Their analysis privileged connections that were highly assortative – that is, with high frequencies of people associating with people like themselves – as one key “real-life indicator” corroborating an epic’s likely historical origin. Here and most everywhere else “hard” trumps “soft”.

Assortativity is a useful principle in epidemiology because it helps to explain the behavior of diseases as they spread through a population. But we are too prone to use viral metaphors to describe the movements of information, ideas, or beliefs through networks. Despite our fascination with social media technologies, we should not assume that a contagion model best characterizes the relationship of stories to networks. Instead, this might be a case of misplaced concreteness, to use A. N. Whitehead’s useful term.

Significant work has been done on so-called “knowledge-based networks” and their relevance for public diplomacy. One case is Mai’a Cross’s analysis of networks of policy decision-makers working toward security integration in the European Union. She shows how greater internal network cohesion increases network influence. For the EU case, cohesion includes the ways these decision-makers share expertise, common cultural and professional norms, and regular participation in the same meetings.

Assortative thinking encourages demonstrations of how like seeks like, while the effectiveness of knowledge-based networks is understood to turn on shared commonalities, notably, of culture. But exclusive attention to the social facts of connectivity through networks – rather than how people invest network participation with significance – means we assume that the information, knowledge, symbols, or stories that circulate through networks are shared in the same ways and mean the same things. But this is a poor assumption. Social solidarity (or, shared network participation) does not require cultural consensus.

What about when cultural information – like stories – is unevenly distributed through a given network? We are in dire need of a sharper and more grounded appreciation of how compelling ideas, values, or cultural meanings travel through social arrangements of people and how people differently relate to them. This means paying greater attention to variable interpretations of cultural information across networks beyond the shared facts of membership in networks.

Uneven distribution can take the form of stories that mean different things to different people in different locations across a given network. In the 1990s, while conducting research on political change in Bolivia, I interviewed dozens of men about the start of their political careers. Many cited the decisive influence of radicalized high school teachers who encouraged them into joining the Bolivian Communist Party in the 1970s. These men still consorted as members of informal political networks, connected by shared political and economic ties, relationships of kinship, friendship and heritage, as well as long hours spent in each other’s company. But many cited the party’s ideological intransigence – especially its derision of the relevance of cultural identity in largely indigenous Bolivia – to explain their departure from it. While carrying over much of the party’s discourse, they were swayed to other forms of political participation more consistent with their indigenous heritage. While each told the “story of the Left” in Bolivia to me and to one another, they did not interpret it in the same ways.

Resonant stories, particularly political narratives, can mean many things to those perpetuating them. Even “strong ties” in identified networks don’t guarantee cultural consensus. In a climate of policy and research where our attention to networks is increasing, but where this work is focused on the use of computational tools to identify their shape and constituent parts, we might be neglecting the problem of cultural meaning in networks. And so we risk having little insight into the sense network participants make out of their own participation. If we confuse the facts of sharedness with a potentially nonexistent interpretive consensus, we risk missing the import of the story.

Note: This post originally appeared on the Center for Public Diplomacy blog site: http://uscpublicdiplomacy.org/index.php/newswire/cpdblog_detail/the_hard_and_soft_of_cultural_diplomacy_networks_and_stories_in_global_affa/

While taking part in an energetic three-day convening at Georgetown University dedicated to “Global Performance, Civic Imagination, and Cultural Diplomacy,” it became clear that the meeting was itself evidence for the continued emergence of a global network linking artists, performers, cultural policy makers, human rights activists, social justice advocates, academics, diplomacy practitioners, and others in international affairs, all variously pursuing new intersections of the arts with cultural diplomacy. The conversation sought to further encourage the development of this incipient global network of the “applied arts,” in the process asking what it means when the arts are incorporated into the work of other sectors and put to other ends, like diplomacy.

In addition to the opportunity to witness this effort of network-building, the meeting served as further evidence of increased attention to partnering, collaboration, and reciprocity as the basis for global outreach by often U.S.-based non-profit and other agencies of non-governmental and citizen diplomacy. In a sense, through a variety of diverse endeavors across the applied humanities and arts, we are seeing the spirit of “mutualism” enacted – less emphasis on the pursuit of national self-interest and more pursuit of closer inter-relationships – a concept taken up here and there in the policy discussion about public diplomacy but, at least so far, not robustly pursued in practice. This appears to be changing.

Organizers Derek Goldman and Cynthia Schneider set the tone for this meeting by comparing the efforts currently underway with past U.S. programs like the Jazz Ambassadors during the Cold War. Although that program was highly successful then, times have changed and now it is neither appropriate nor effective simply to take your show on the road, as it were, to demonstrate one’s “culture in a monolithic way.” Nowadays it is necessary to “work more collaboratively” and to ask, “What story do we want to tell together?” Theater is one richly expressive avenue for collaboration. Goldman summarized this trend during the meeting as a “movement away from models of display to imparting agency to others.”

Throughout the meeting “performance” was discussed as a methodology to the ends of: amplifying local voices, enabling people to find ways to tell their stories, creating contexts for public dialogue, enabling social critique, transforming conflicts, or pursuing reconciliation. Art was discussed not as a medium of message delivery so much as “a part of the agenda of others,” where, along with the transfer of skills such as choreography, a collaborative goal is to better appreciate how other people express themselves and what this might mean for how they are currently thinking about themselves, their circumstances, and their worlds.

The Georgetown meeting provided multiple examples of this sort of collaboration, such as Theatre Without Borders, which facilitates global theater exchange among people and institutions. Theatre Without Borders is currently collaborating with the Peacebuilding and the Arts program at Brandeis University to use performance creatively to transform understandings of conflict in chronic conflict zones around the world. Utilizing the tools of community-based performance, this project seeks to nourish and to restore peoples’ expressive capacities as a way to help them better address publicly questions of justice, memory, identity and resistance, but also complicity. This is a collaboration, in other words, that enables dialogue among the participants in, and victims of, chronic violence. But it does not impose an agenda on that conversation.

And this emerging network around socially—engaged applied artists who work globally is just one corner of a larger international environment in which a mixture of cultural producers, workers, and agencies – including non-profits, museums, archives, and libraries – are pursuing parallel applied and humanitarian work with partners. What I will call “applied humanities networks” now comprise a growing diversity of creative collaborations leveraging the knowledge, expertise, and creativity of U.S. cultural professionals, in the service of a variety of international partnerships well beyond the traditional work of arts management.

By and large these activities are not on the radar of decision-makers in international affairs, but they include such efforts as: participatory curation, applications of new social media, archival training, oral history and public memory projects, cultural heritage conservation, digital game design, documentary film, culture mapping, the negotiation of cultural copyright and building of cultural commons, and the management and exhibition of antiquities and other national cultural collections, among other activities. One feature of this work is cultural diplomacy, though not as we conventionally understand it.

A collaboration between U.S.-based folklorists and like professionals concerned with intangible cultural heritage and their Chinese counterparts, the China-US Forum on Cultural Sustainability, is another case of an incipient transnational applied humanities network that has direct implications for cultural diplomacy. On the one hand, the Forum contributes to the internationalization of folklore studies. On the other, it directs comparative attention to the often differing theoretical, policy, and practical frames that inform what is, nevertheless, shared attention to the sustainability of intangible cultural heritage (hereafter, ICH) in both countries. And, the Forum sets out from a shared commitment among scholars and practitioners in both countries to identify, document, present and safeguard ICH, as critical to their “national interest and well-being.”

The Forum facilitates collaborative U.S.-China efforts to chart, compare, analyze, communicate widely, and to generate shared products focused on “tradition-based cultural expressions” through a variety of related initiatives. In the course of their collaboration, ICH practitioners from the U.S. and China have to work through different underlying assumptions and theories that shape and define the scope, meaning and location of ICH in both countries, including different challenges posed for national culture industries, community development, cultural tourism, and for the status of cultural minorities.

One difference is distinct time horizons bounding attention given to ICH among scholars: recent popular culture is given regular attention by U.S. practitioners while Chinese counterparts direct their attention to much older forms of traditional cultural expression. Part of the purpose of the Forum, therefore, is to engage such differences through the encompassing goal of professional development among ICH specialists in both countries.

Notably, the Forum is a model for how to take up what can be potentially explosive bilateral questions (e. g. the status of religious or cultural minorities in China) without also imposing any particular agenda. In fact, collaborators on the U.S. end, like the American Folklore Society and Vanderbilt’s Curb Center, are actively engaging with the Chinese Folklore Society and other counterparts, with the stated goal of establishing a “field of folklore studies with Chinese characteristics.”

A final example is a recently constituted applied humanities network, now working in the humanitarian context of disaster relief, organized around the Haiti Cultural Recovery Project. An effort coordinating many partners and led by the Smithsonian, the project has mobilized applied cultural practitioners from the U.S. and elsewhere to support the efforts of Haitian cultural professionals to rescue, safeguard, and restore the country’s national cultural heritage in the aftermath of the 2010 earthquake. The rescue of key expressions of Haiti’s heritage has provided continuity to Haitian cultural identity by saving artifacts of collective cultural memory, helping to maintain a cultural basis for Haiti to address its post-disaster national identity going forward.

Incorporated into the overall disaster relief effort, the Cultural Recovery Project is primarily composed of museum professionals – conservators and curators – engaged in the work of stabilizing, documenting and restoring artwork, including: paintings, murals, artifacts, documents, media, architectural features, and historical and archival items. Smithsonian conservators also train their Haitian counterparts in the skills of conservation and restoration, to help build and promote a sustainable Haitian-led center.

The work of rescuing Haiti’s threatened art evolved into an opportunity to relationship-build, to share “common values” around heritage conservation, and also an opportunity for new shared creative cultural expressions. Understood by Haitian counterparts as “arts for survival” that activate the relationship between culture and resilience through the interconnections between art, healing and community, so far these include a documentary film, considerable media coverage, a website, as well as new museum exhibitions focused on the recovery effort.

Notable is the kind of U.S.-Haitian relationship this project represents. A cultural recovery base was set up in Haiti, rather than bringing the artworks to the U.S. for treatment. Capacity-building of Haitian counterparts is one major feature of the project going forward. Cultural conservators from the Smithsonian and other U.S. institutions have taken a supporting role in helping Haiti consolidate its own efforts. All decisions about relative cultural value in the work of identifying, inventorying, and prioritizing individual items of cultural heritage are made by Haitians. The guiding question of the collaboration is “What do Haitians want to do?” A basic goal of the project is to preserve the ability of the Haitian people “to tell their own story to future generations.”

This collaborative work is making the case that effective cultural diplomacy need not aspire to control the message. It is not best deployed when closely linked to the priorities of policy makers or defined national interests. Nor is it always desirable for acts of cultural diplomacy to be framed in terms of the goal of the representation of a people. The development of new applied humanities networks, which feature the efforts of U.S.-based cultural producers and workers, suggests another approach, which we might take note of as a means to rethink conventional wisdom about cultural diplomacy.

The new approach includes: working through collaboration rather than exchange, ceding authority while bringing skills, promoting the agency of others, and pursuing shared creative outcomes, while seeking to address the needs of others in humanitarian terms. This approach avoids trying to convert people into receptive audiences for our own story—however much we happen to like it.

Note: This post originally appeared on the Center for Public Diplomacy blog site: http://uscpublicdiplomacy.org/index.php/newswire/cpdblog_detail/international_applied_humanities_networks_and_global_cultural_engagement/

As the Obama Administration’s new “Big Data Research and Development Initiative” has made clear, the “big data” era is officially upon us. The term – “big data” has been used in multiple ways, but most generally refers to the avalanche of “raw data” generated by the internet and other new kinds of data-capturing sensor and digital technologies. Or, as one big data guru more pithily put it, it is “all the stuff we do online” – and more. With the “big data revolution” comes unflagging optimism regarding more comprehensive methods for the collection of vast new stores of technologically-produced data, enabling the pursuit of previously unanswerable questions, and carrying the promise of breakthroughs in how we access and understand the information composing our world. Time will tell.

The turn to “big data” represents a potentially exciting set of developments along multiple frontiers of advanced supercomputing, new software tools, other information collection technologies such as GIS, database management systems, and massive data sets, such as the exponentially expanding corpus of information generated by Web 2.0 social media. Government funding has followed a corporate lead, where in recent years the likes of Google, Facebook, Apple, and Amazon have turned a pursuit of “big data” into a major business proposition focused on gathering increasingly nuanced information about consumer behavior to better service and target customers. Making sense of the implications of all this will preoccupy us for some time.

Techno-Optimism

As the press release from the White House Office of Science and Technology Policy explains, “big data” projects hold great promise for “scientific discovery, environmental and biomedical research, education, and national security.” The very early returns on “big data”-derived research are already turning heads, from predicting political upheavals like the Arab Spring, market volatility, or new epidemic outbreaks, to mapping emerging cultural trends or the evolution of languages.

And the attraction of “big data” hits a number of sweet spots. Most generally, “big data” is now carrying the torch for the whiz bang potential of the next Silicon Valley-derived infotech revolution for enhancing “innovation” – whatever that might specifically mean. For universities, it is a readily available advert for a more technologically-enabled higher education, which also happily relieves budgetary pressures to expand the physical holdings of campus libraries and other facilities.

“Big data” also has mass appeal: leveraging big medical data promises to help fix our broken healthcare system by making it less expensive; it has been presented as the newest super tool to combat global poverty; it also helps to power the imagination of urban planners hoping to incentivize new creative economies; for the security community, it beckons by offering “crystal ball”-like certainties of greater information dominance and more precise prediction; and in the spirit of C. P. Snow, it confers legitimacy on the so-called digital humanities in a cost-conscious era, as an apparent collaborative bridge for the “hard” scientists to bring more rigor to their colleagues in the humanities and “soft” (or social) sciences. Among other frontiers.

The “big data” train has left the station, with all the concomitant hyperbole and hoopla that so often appears to accompany promising new developments in science heralding paradigm shifts in research. However, from my perspective missing from the enthusiastic rush to adoption is a critically grounded accountability regarding what big data advocates are claiming as opposed to actually doing: attention not only to the benefits but also the costs, to its potential but also its limits. Unrelenting techno-futurist optimism does not nurture this.

Trained as a sociocultural anthropologist, I have been most interested in how “big data” has intersected with efforts to better leverage sociocultural information to different ends. Most notably, this includes the Google-powered development of the new “field” of culturomics, elliptically defined by some of its founding practitioners as “the application of high-throughput data collection and analysis to the study of human culture.”

This sounds promising, if not altogether clear. The novelty of culturomics is its potential “to investigate cultural trends quantitatively” by generating previously hidden “suitable data” from hitherto unavailable massive databases. Despite this potential, breathless claims about the unprecedented access offered by culturomics to our own cultural history or for the Isaac Asimov-style prediction of future cultural events have derailed more grounded attention to what the “culture” of culturomics actually corresponds to and what kind of knowledge it provides. More on culturomics presently.

Critically Engaging Data

In this era of teraflops, terabytes, and cloud computing, big data represents the future. But the field has so far also displayed a notable lack of interest in addressing what the term fundamentally references, what it’s relationships might be to other sorts of disciplinary and scientific pursuits, what these related developments might helpfully enable but – perhaps more importantly and most neglected – what “big data” either obscures or cannot meaningfully address.

The biggest problem with our conversation so far about the potential of “big data” efforts is that we are spending too much time enamored of the “big” – the prospect of the unprecedented and vast volume and scale of the collection, organization, and processing of mostly digital information, primarily through new data mining applications that rapidly amass unique digital data sets – and virtually no time thinking about what the “data” part might consist of – what the data essentially are. Often exhibiting a naïve digital positivism vis-à-vis “data,” in many ways the turn to “big data” is more like a return to the past. But we need to be much more scrupulous about what we mean by “data” here. What, in short, are the data of “big data” and what, basically, is their value?

What we mean by “data” for emerging “big data” fields like culturomics is an important question for a number of reasons. Big data projects are notably cross- or interdisciplinary. For example, the affiliated researchers at Harvard’s Cultural Observatory, where culturomics has been pioneered, include: several computer scientists and Google software engineers, mathematicians, evolutionary biologists, and one doctoral student in history.

Absent from the team is balance on the cultural end, or a range of disciplinary expertise likely to sustain fruitfully interdisciplinary back-and-forth, say, that might usefully problematize specific, perhaps directly competing, frameworks, perspectives, and characteristic forms of producing and evaluating knowledge, across different communities of computational and cultural research. Understandably, most computer scientists are at best only passingly aware of the characteristic methods and relationships to data among colleagues from the social sciences or humanities.

Its apparent “interdisciplinarity” is a big part of the enthusiasm the turn to “big data” has generated. Big data projects using computational techniques often involve carrying over methods from one disciplinary environment (e. g. the computer sciences) and applying them to often long-standing problems in other disciplines such as economics, hydrology, or in the applied humanities. Sometimes this is a good fit. But sometimes it is not. And, it is often hard to tell, since big data researchers often treat data questions as straightforward, with data presented as unproblematically readily available to collect and to manipulate.

However, when a computer scientist develops a new data mining tool to systematically harvest often vast quantities of online digital information, s/he is not simply collecting data. S/he is also carrying over specific assumptions about what “data” is, how it is identified and recognized, where it sits in a larger context or field of endeavor, how it is determined by an encompassing information ecology of concern to computer scientists, how it can be made legibly available for analysis, and what sorts of conclusions can be derived from it. We might say that this data carries a particular signature identifying it with its disciplinary source — a signature with technical, methodological, and meaningful consequences.

When asked about this, the Harvard team’s response was, “It’s irrelevant. What matters is the quality of the data…” But “data” is not all of a piece, varying simply in quality and quantity. Particular disciplines understand their knowledge production and their relationship to data in often starkly different – or even incompatible — ways. And culturomics relies upon a conception of data that makes particular sense for computer scientists but is not necessarily consistent with the ways different social sciences deal with the cultural data with which they work.

Different disciplines have historically specific relationships to data, and which significantly express that discipline’s unique development and characteristic pursuit of problems. And “data” are not self-evident, universally fungible, straightforwardly equivalent or comparable across these pursuits, say, in the same way as we might think of the circulation of currency in the global economy. But this is exactly how the NSF is talking about the “big data revolution.”

The data of “big data” are in fact a particular kind of data: largely digital in nature. And this has definite consequences. Early adopters of the techniques of culturomics are so far spending little time with the implications of this, instead opting to promote the seemingly limitless potential of such techniques. In part, the reason is because for them questions about data are more often than not technical problems to be solved (e. g. about building the platform architecture, writing computer codes and algorithms, or compatibility with one or another digital database) instead of more fundamental questions about the identity of “data,” the sources of knowledge, and – for culturomics – the relationship of culture to meaning.

Simply “plugging in” data collected and understood for use by one community of practitioners might, from another’s point of view, simply add up to: “garbage in, garbage out.” This problem can quickly lead to fundamental misunderstandings about what is being done with such work and about the potential it offers for better understandings of cultural questions.

Culturomics and Data

As the “big data” trend gains momentum, the concerns that have been raised have primarily revolved around two issues: privacy and transparency. On the one hand, primarily in the U.S. legal debates have focused on the potential negative implications of the increased vulnerability of personal information as a result of the tremendous improvements in online data mining and technological surveillance. On the other hand, researchers have pointed to the lack of public availability of these massive data sets, often because they are corporately owned, which makes restudies or assessments of results based on these data almost impossible.

These are legitimate and important concerns, deserving attention. But, in themselves, they do not add up to a nearly robust enough discussion of these data. Culturomics is not the only “big data” front to apply comparable techniques to trying to make sense of sociocultural knowledge. We can also point to the rapid growth of attention to computational sociocultural modeling and simulation on the part of the security sector, which uses similar techniques. Given this incredible enthusiasm, much more critical scrutiny of these tools is required so that users can better determine their appropriate niche.

For the universe of culturomics, if we were briefly to characterize its “data” – to identify its particular disciplinary signature – we might point to a variety of factors. First, culturomics pursues a quantitative content analysis but on a colossal scale, using automated forms of collection derived from algorithms – computer code – designed to look for, and to sort through, particular properties of information already identified as a relevant data set, like Google Books, financial market indicators, twitter feeds, or country surveys. Its goal, in other words, is to record the frequencies or associations of key words and phrases over time and across these already structured sets.

A “culturome” (yes, arrived at via analogy to the “genome”) has, therefore, been described as “the mass of structured data that characterizes a culture.” Like a “gene” or a “meme,” it seems to be largely taken for granted that the data of culturomics are standard, and comparable, bits of information. This claim is controversial for a contemporary sociocultural anthropology engaged with a diversity of forms of cultural expression, and for which cultural meanings are not generated in just one way.

Digitally, the data of culturomics largely are standard bits of information: they are frequency counts of 0’s and 1’s, that is, variables processed according to particular search and classification criteria that are themselves written into the search algorithm of the data mining phase of work. And yet, in the results stage, these variables are re-presented as “data,” but with an empirical and even positivist sensibility. They are presented as if preexistent “stuff” out there in the world waiting to be extracted, processed, and explained. This is a sleight-of-hand. They are in fact “variables.”

For the case of culturomics we might point to a close, even closed, relationship between a specific data mining and processing tool and the data it generates. Any work with Google Books, including Google’s N-gram viewer – created to allow researchers to generate frequency counts and distribution curves of words or phrases from the Google Books archive – of course ignores non-written, non-published words, and all non-linguistic expressions of culture. It is also limited to those books which have been scanned and digitized (approximately 4% of all published books), and works only where a book has been digitized with adequately extractable metadata tags (e. g. indicating publishing date, author, genre, etc.). Too, the Google Books project has been limited by other prevailing factors, such as legal limitations upon public dissemination presented by intellectual property restrictions.

Why, then, would we even suppose that any results from a culturomics study using Google Books could “roughly represent the larger culture that produced it”? Or, more ridiculously, why are we hearing talk about the promise of culturomics to help identify “power laws for culture”? Books are particular kinds of cultural artifacts not simply ciphers for them. But experts seem willing to suspend disbelief. Part of this suspension includes a lack of attention to the ways that culturomics data are notably prefigured – even determined – by the technical choices made, the platforms used, the algorithmic codes written to mine the data, as well as the digital availability and legibility of the already-formatted data in the first place.

Another way to say this is that, even as researchers treat culturomics data as interchangeable, we might suggest that the data of culturomics more accurately express the world view of culturomics. Culturomics researchers have acknowledged that their work is not intended to replace existing varieties of cultural analysis. But they refer only to the “close reading of texts,” presumably the activity of historians, literary critics, some semioticians or cultural studies scholars. This is a kind of interpretive work also conversant with the largely digital textual landscape with which culturomics is concerned, but in no way exhaustive of other cultural research methods and kinds of interpretive attention. Minimally, we need more regular reminders of the partiality of such projects.

Culturomics: Market Trend

One of the techniques culturomics researchers are using is “tone analysis” or “tone mining.” The object is to establish whether a particular word, phrase, or text possesses a positive, negative, or neutral tone. Terms like tone, mood, style, or texture have long been mainstays of the lexicon of literary criticism, in particular for the “new critics” inspired by the work of I. A. Richards. Tone has also come to inform other interpretive approaches, including contemporary attention to “voice.” Often associated with the work of Michael Bakhtin, such work is distinguished by attention to the dialogic interactions between a speaker in a text and multiple other points of view, for which any particular utterance is always multi-voiced. In other words, tone has been a doorway for appreciating the ways that texts are variously embedded in and animate different social and cultural contexts.

But culturomics treats tone as a “metric,” which can be turned into computable numeric data. A recent project funded in part by NSF’s Extreme Science and Engineering Discovery Environment program used a database from the Open Source Center and Summary of World Broadcasts of approximately 100 million news articles between 1979 and 2011 to measure shifts in the “global news tone,” which retroactively appears to forecast the recent Arab Spring. Such forecasting tricks are impressive.

But it is exactly at this juncture that much more scrutiny of what is involved in “tone mining” (also called “sentiment” or “opinion mining”) is needed, if we hope to come to terms with what such forecasting or trend data in fact mean in cultural terms. Here it is important to understand where this computational attention to tone comes from – what the genealogy of this kind of data is.

Amazon, among others, pioneered the proliferation of digital apps which transmit an increasing variety and volume of consumer preference data back to retailers. And for several years now many Fortune 500 companies have utilized tone mining to monitor news coverage and social media activity associated with their products. These companies, of course, have an interest in learning as much as possible about what consumers are saying about their products and in identifying new demographics. Most often they would like to be able to map or to anticipate consumer responses to particular products.

The work of data mining for tone, sentiment or opinion – incorporated into so-called culturomics 2.0 – basically works like this: 1. First, identify precompiled dictionaries of “positive” and “negative” words against which other digital texts can be compared and scored; 2. Develop an algorithm as the basis for an automated computational method for mining tone data; 3. Record frequencies of these properties across so-called “opinionated texts,” as comparable items that compose an already “structured” online database or archive; 4. Assign a “value” to each so that it can used as a variable to plot trend data; 5. For culturomics, take a leap of faith by treating these plots as meaningfully indicators of cultural trends of one sort or another, often spanning decades or centuries.

However, in the enthusiasm for culturomics we have been too quick to shake off the origins or history of these data. They are certainly not “raw data” of some sort. They are, instead, specific artifacts of digital business practice. Attention to “tone” or “sentiment” – as data – works well if you are invested in trying to figure out peoples’ preferences. But its meaningful or representative relationship to culture, or as any sort of expression of culture, requires much more unpacking and qualification than we are getting so far.

In interdisciplinary terms, this kind of quantitative knowledge about culture (read: products) might not be usefully complementary to other forms of cultural research, data, or analysis. It might simply be an entirely different sort of information, for which use of the word – “culture” or field “culturomics” – is in fact misleading and unconstructive.

I have emphasized briefly some of the ways that tone mining generates not “data” but a very particular kind of data significantly prefigured by the technological architecture of the tools used, organization of existing digital databases, and computer code supporting such tools. These are preconditions that queer the game, as it were, as doorways encouraging certain kinds of attention to information while rendering other kinds illegible or marginal. In their very form, we might say, culturomics data already answer the possible questions to ask.

But there’s more. Culturomics relies on an alarmingly consumerist, or neoliberal, theory of meaning, for which tone or sentiment is the product of choices by cultural agents (originally, consumers), only insofar as they take the form: pro/con, either/or, positive/negative, or similar variant. This makes perfect sense if you want to know what people think of a toaster or if you want to record distributions of “thumbs up” among Facebook or Twitter users – after all, the impetus for collecting such information in the first place.

Contesting Culture, Data, Meaning

The “culture” of culturomics expresses the organization of available, countable, compilable information, which can be systematically extracted from digitizable texts like books, newspapers, maps, and twitter feeds. In this way culturomics is itself an often very creative exercise in selective choice-making. But it is not in any way describing the shapes of previously undescribable macro-cultural landscapes.

Whatever “culture” is, to proceed as if it can be assembled from discrete and comparable units derived from algorithmically-assigned “values” of machine-processed digital information is to emphasize very particular structured properties available for a technically and commercially specific prior purpose. And it equates culture with consumer choice. But to reduce the meaning of cultural trends to the prodigious mass of opinion data generated online by consumers is to grossly reduce what “culture” is to a narrow market calculus. We are better off leaving the question of the sources for cultural meaning open-ended.

Despite frequent assertions to the contrary, “more – and better – data” does not automatically lead to “more robust results.” We need to temper our techno-futurist optimism with basic questions: What is meant by cultural data in the first place? What is significant about frequency counts of cultural “stuff”? How do we attribute meaning to cultural data? And what is their relationship to real-world referents? Among other relevant questions. Such a constructively skeptical approach should inform “big data”-type projects of all sorts.

Some early critiques of culturomics have complained that it cannot address the humanist “search for meaning.” But I have suggested that, with their focus on the interpretation of texts, such concerns are still located well within the culturomics world view. They represent a latter day revival of C. P. Snow’s “two cultures” debate about science and the humanities, which sets up a goal of interdisciplinarity that assumes a pride of place for the technologically-enabled “sciences” (specifically, computer science) to make sense of the world.

Developments like culturomics have intriguing potential. But the claims associated with them – in this case about “culture” – can obfuscate and confuse. Sociocultural anthropologists also aspire to make sense of cultures. They typically do this ethnographically, and where cultural meanings are not simply latent and extractable, but instead emergently negotiated with counterparts (people we encounter “in the field” who we used to call “informants”). The data are usually multivocal, polysemic and perspectival, and not simply reducible to a pro/con or either/or-type choice.

The often serendipitous open-endedness of ethnography also contrasts with the technological and other prefigurements of the method of culturomics. More proximate to different specific contexts of meaning-making, ethnography is likely better located to apprehend emergent ground truths, other cultural points of view, and the diverse ways difference travels through the world. It is not clear at all that culturomics is even compatible with, let alone complementary to, ethnographic apprehensions of culture. And this raises serious questions about the celebratory interdisciplinarity with which big data projects continue to be met.

Note: This post first appeared on the blog site Ethnography here: http://www.ethnography.com/2012/06/culture-in-the-science-fictional-universe-of-big-data/

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