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    • Algorithm [draft] [#digitalkeywords] Jun 25, 2014

      “What we are really concerned with when we invoke the “algorithmic” here is not the algorithm per se but the insertion of procedure into human knowledge and social experience. What makes something algorithmic is that it is produced by or related to an information system that is committed (functionally and ideologically) to the computational generation of knowledge or decisions.”

      The following is a draft of an essay, eventually for publication as part of the Digital Keywords project (Ben Peters, ed). This and other drafts will be circulated on Culture Digitally, and we invite anyone to provide comment, criticism, or suggestion in the comment space below. We ask that you please do honor that it is being offered in draft form — both in your comments, which we hope will be constructive in tone, and in any use of the document: you may share the link to this essay as widely as you like, but please do not quote from this draft without the author’s permission. (TLG)


      Algorithm — Tarleton Gillespie, Cornell University

      In Keywords, Raymond Williams urges us to think about how our use of a term has changed over time. But the concern with many of these “digital keywords” is the simultaneous and competing uses of a term by different communities, particularly those inside and outside of technical professions, who seem often to share common words but speak different languages. Williams points to this concern too: “When we come to say ‘we just don’t speak the same language’ we mean something more general: that we have different immediate values or different kinds of valuation, or that we are aware, often intangibly, of different formations and distributions of energy and interest.” (11)

      For “algorithm,” there is a sense that the technical communities, the social scientists, and the broader public are using the word in different ways. For software engineers, algorithms are often quite simple things; for the broader public they name something unattainably complex. For social scientists there is danger in the way “algorithm” lures us away from the technical meaning, offering an inscrutable artifact that nevertheless has some elusive and explanatory power (Barocas et al, 3). We find ourselves more ready to proclaim the impact of algorithms than to say what they are. I’m not insisting that critique requires settling on a singular meaning, or that technical meanings necessarily trumps others. But we do need to be cognizant of the multiple meanings of “algorithm” as well as the type of discursive work it does in our own scholarship.

      algorithm as a technical solution to a technical problem

      In the scholarly effort to pinpoint the values that are enacted, or even embedded, in computational technology, it may in fact not be the “algorithms” that we need be most concerned about — if what we meant by algorithm was restricted to software engineers’ use the term. For their makers, “algorithm” refers specifically to the logical series of steps for organizing and acting on a body of data to quickly achieve a desired outcome. MacCormick (2012), in an attempt to explain algorithms to a general audience, calls them “tricks,” (5) by which he means “tricks of the trade” more than tricks in the magical sense — or perhaps like magic, but as a magician understands it. An algorithm is a recipe composed in programmable steps; most of the “values” that concern us lie elsewhere in the technical systems and the work that produces them.

      For its designers, the “algorithm” comes after the generation of a “model,” i.e. the formalization of the problem and the goal in computational terms. So, the task of giving a user the most relevant search results for their queries might be operationalized into a model for efficiently calculating the combined values of pre-weighted objects in the index database, in order to improve the percentage likelihood that the user clicks on one of the first five results.[1] This is where the complex social activity and the values held about it are translated into a functional interaction of variables, indicators, and outcomes. Measurable relationships are posited as existing between some of these elements; a strategic target is selected, as a proxy for some broader social goal; a threshold is determined as an indication of success, at least for this iteration.

      The “algorithm” that might follow, then, is merely the steps for aggregating those assigned values efficiently, or delivering the results rapidly, or identifying the strongest relationships according to some operationalized notion of “strong.” All is in the service of the model’s understanding of the data and what it represents, and in service of the model’s goal and how it has been formalized. There may be many algorithms that would reach the same result inside a given model, just like bubble sorts and shell sorts both put lists of words into alphabetical order. Engineers choose between them based on values such as how quickly they return the result, the load they impose on the system’s available memory, perhaps their computational elegance. The embedded values that make a sociological difference are probably more about the problem being solved, the way it has been modeled, the goal chosen, and the way that goal has been operationalized (Reider).

      Of course, simple alphabetical sorting may be a misleading an example to use here. The algorithms we’re concerned about today are rarely designed to reach a single and certifiable answer, like a correctly alphabetized list. More common are algorithms that must choose one of many possible results, none of which are certifiably “correct.” Algorithm designers must instead achieve some threshold of operator or user satisfaction — understood in the model, perhaps, in terms of percent clicks on the top results, or percentage of correctly identified human faces from digital images.

      This brings us to the second value-laden element around the algorithm. To efficiently design algorithms that achieve a target goal (rather than reaching a known answer), algorithms are “trained” on a corpus of known data. This data has been in some way certified, either by the designers or by past user practices: this photo is of a human face, this photo is not; this search result has been selected by many users in response to this query, this one has not. The algorithm is then run on this data so that it may “learn” to pair queries and results found satisfactory in the past, or to distinguish images with faces from images without.

      The values, assumptions, and workarounds that go into the selection and preparation of this training data may also be of much more importance to our sociological concerns than the algorithm learning from it. For example, the training data must be a reasonable approximation of the data that algorithm will operate on in the wild. The most common problem in algorithm design is that the new data turns out not to match the training data in some consequential way. Sometimes new phenomena emerge that the training data simply did not include and could not have anticipated; just as often, something important was overlooked as irrelevant, or was scrubbed from the training data in preparation for the development of the algorithm.

      Furthermore, improving an algorithm is rarely about redesigning it. Rather, designers will “tune” an array of parameters and thresholds, each of which represents a tiny assessment or distinction. In search, this might mean the weight given to a word based on where it appears in a webpage, or assigned when two words appear in proximity, or given to words that are categorically equivalent to the query term. These values have been assigned and are already part of the training data, or are thresholds that can be dialed up or down in the algorithm’s calculation of which webpage has a score high enough to warrant ranking it among the results returned to the user.

      Finally, these exhaustively trained and finely tuned algorithms are instantiated inside of what we might call an application, which actually performs the functions we’re concerned with. For algorithm designers, the algorithm is the conceptual sequence of steps, which should be expressible in any computer language, or in human or logical language. They are instantiated in code, running on servers somewhere, attended to by other helper applications (Geiger 2014), triggered when a query comes in or an image is scanned. I find it easiest the think about the difference between the “book” in your hand and the “story” within it. These applications embody values as well, outside of their reliance on a particular algorithm.

      To inquire into the implications of “algorithms,” if we meant what software engineers mean when they use the term, could only be something so picky as investigating the political implications of using a bubble sort or a shell sort — setting aside bigger questions like why “alphabetical” in the first place, or why train on this particular dataset. Perhaps there are lively insights to be had about the implications of different algorithms in this technical sense,{2] but by and large we in fact mean something else when we talk about algorithms as having “social implications.”

      algorithm as synecdoche

      While it is important to understand the technical specificity of the term, “algorithm” has now achieved some purchase in the broader public discourse about information technologies, where it is typically used to mean everything described in the previous section, combined. As Goffey puts it, “Algorithms act, but they do so as part of an ill-defined network of actions upon actions.” (19) “Algorithm” may in fact serve as an abbreviation for the sociotechnical assemblage that includes algorithm, model, target goal, data, training data, application, hardware — and connect it all to a broader social endeavor. Beyond the technical assemblage there are people at every point: people debating the models, cleaning the training data, designing the algorithms, tuning the parameters, deciding on which algorithms to depend on in which context. “These algorithmic systems are not standalone little boxes, but massive, networked ones with hundreds of hands reaching into them, tweaking and tuning, swapping out parts and experimenting with new arrangements… We need to examine the logic that guides the hands.” (Seaver 2013) Perhaps “algorithm” is just the name for one kind of socio-technical ensemble, part of a family of authoritative systems for knowledge production or decision-making: in this one, humans involved are rendered legible as data, are put into systematic / mathematical relationships with each other and with information, and then are given information resources based on calculated assessments of them and their inputs.

      But what is gained and lost by using “algorithm” this way? Calling the complex sociotechnical assemblage an “algorithm” avoids the need for the kind of expertise that could parse and understand the different elements; a reporter may not need to know the relationship between model, training data, thresholds, and application in order to call into question the impact of that “algorithm” in a specific instance. It also acknowledges that, when designed well, an algorithm is meant to function seamlessly as a tool; perhaps it can, in practice, be understood as a singular entity. Even algorithm designers, in their own discourse, shift between the more precise meaning, and using the term more broadly in this way.

      On the other hand, this conflation risks obscuring the ways in which political values may come in elsewhere than at what designers call the “algorithm.” This helps account for the way many algorithm designers seem initially surprised by the interest of sociologists in what they do — because they may not see the values in their “algorithms” (precisely understood) that we see in their algorithms (broadly understood), because questions of value are very much bracketed in the early decisions about how to operationalize a social activity into a model and into the miniscule, mathematical moments of assigning scores and tuning thresholds.

      In our own scholarship, this kind of synecdoche is perhaps unavoidable. Like the journalists, most sociologists do not have the technical expertise or the access to investigate each of the elements of what they call the algorithm. But when we settle uncritically on this shiny, alluring term, we risk reifying the processes that constitute it. All the classic problems we face when trying to unpack a technology, the term packs for us. It becomes too easy to treat it as a single artifact, when in the cases we’re most interested in it’s rarely one algorithm, but many tools functioning together, sometimes different tools for different users.[3] It also tends to erase the people involved, downplay their role, and distance them from accountability. In the end, whether this synecdoche is acceptable depends on our intellectual aims. Calling all these social and technical elements “the algorithm” may give us a handle with which to grip we want to closely interrogate; at the same time it can produce a “mystified abstraction” (Striphas 2012) that, for other research questions, it might be better to demystify.

      algorithm as talisman

      The information industries have found value in the term “algorithm” in their public-facing discursive efforts as well. To call their service or process an algorithm is to lend a set of associations to that service: mathematical, logical, impartial, consistent. Algorithms seem to have a “disposition towards objectivity” (Hillis et al 2013: 37); this objectivity is regularly performed as a feature of algorithmic systems. (Gillespie 2014) Conclusions that can be described as having been generated by an algorithm come with a powerful legitimacy, much the way statistical data bolsters scientific claims, with the human hands yet another step removed. It is a very different kind of legitimacy than one that rests on the subjective expertise of an editor or a consultant, though it is important not to assume that it trumps such claims in all cases. A market prediction that is “algorithmic” is different from a prediction that comes from an expert broker highly respected for their expertise and acumen; a claim about an emergent social norm in a community generated by an algorithm is different from one generated ethnographically. Each makes its own play for legitimacy, and implies its own framework for what legitimacy is (quantification or interpretation, mechanical distance or human closeness). But in the context of nearly a century of celebration of the statistical production of knowledge and longstanding trust in automated calculation over human judgment, the algorithmic does enjoy a particular cultural authority.

      More than that, the term offers the corporate owner a powerful talisman to ward off criticism, when companies must justify themselves and their services to their audience, explain away errors and unwanted outcomes, and justify and defend the increasingly significant roles they play in public life. (Gillespie 2014) Information services can point to “the algorithm” as having been responsible for particular results or conclusions, as a way to distance those results from the providers. (Morozov, 2013: 142) The term generates an entity that is somehow separate, the assembly line inside the factory, that can be praised as efficient or blamed for mistakes.

      The term “algorithm” is also quite often used as a stand-in for its designer or corporate owner. When a critic says “Facebook’s algorithm” they often mean Facebook and the choices it makes, some of which are made in code. This may be another way of making the earlier point, that the singular term stands for a complex sociotechnical assemblage: Facebook’s algorithm really means “Facebook,” and Facebook really means the people, things, priorities, infrastructures, aims, and discourses that animate them. But it may also be a political economic conflation: this is Facebook acting through its algorithm, intervening in an algorithmic way, building a business precisely on its ability to construct complex models of social/expressive activity, train on an immense corpus of data, tune countless parameters, and reach formalized goals extremely efficiently.

      Maybe saying “Facebook’s algorithm” and really meaning the choices and interventions made by Facebook the company into our social practices is a way to assign accountability (Diakopoulos 2013, Ziewitz 2011). It makes the algorithm theirs in a powerful way, and works to reduce the distance some providers put between “them” (their aims, their business model, their footprint, their responsibility) and “the algorithm” (as somehow autonomous from all that). On the other hand, conflating the algorithmic mechanism and the corporate owner may obscure the ways these two entities are not always aligned. It is crucial that we discern between things done by the algorithmic system and things done in other ways, such as the deletion of obscene images from a content platform, which is sometimes handled algorithmically and sometimes performed manually. (Gillespie 2012b) It is crucial to note slippage between a provider’s financial or political aims and the way the algorithmic system actually functions. And conflating algorithmic mechanism and corporate owner misses how some algorithmic approaches are common to multiple stakeholders, circulate across them, and embody a tactic that exceeds any one implementation.

      algorithmic as committed to procedure

      In recent scholarship on the social significance of algorithms, it is common for the term to appear not as a noun but as an adjective. To talk about “algorithmic identity” (Cheney-Lippold), “algorithmic regulation” (O’Reilly), “algorithmic power” (Bucher), “algorithmic publics” (Leavitt), “algorithmic culture” (Striphas, 2010) or the “algorithmic turn (Uricchio, 2011) is to highlight a social phenomenon that is driven by and committed to algorithmic systems — which include not just algorithms themselves, but also the computational networks in which they function, the people who design and operate them, the data (and users) on which they act, and the institutions that provide these services.

      What we are really concerned with when we invoke the “algorithmic” here is not the algorithm per se but the insertion of procedure into human knowledge and social experience. What makes something algorithmic is that it is produced by or related to an information system that is committed (functionally and ideologically) to the computational generation of knowledge or decisions. This requires the formalization of social facts into measurable data and the “clarification” (Cheney-Lippold) of social phenomena into computational models that operationalize both problem and solution. These are often proxies for human judgment or action, meant to simulate it as nearly as possible. But the “algorithmic” intervenes in terms of step-by-step procedures that one (computer or human) can enact on this formalized information, such that it can be computed. This process is automated so that it can happen instantly, repetitively, and across many contexts, away from the guiding hand of its implementers. This is not the same as suggesting that knowledge is produced exclusively by a machine, abstracted from human agency or intervention. Information systems are always swarming with people, we just can’t always see them. (Downey, 2014; Kushner 2013) And an assembly line might be just as “algorithmic” in this sense of the word, or at least the parallels are important to consider. What is central is the commitment to procedure, and the way procedure distances its human operators from both the point of contact with others and the mantle of responsibility for the intervention they make. It is a principled commitment to the “if/then” logic of computation.

      Yet what does “algorithmic” refer to, exactly? To put it another way, what is it that is not “algorithmic”? What kind of “regulation” is being condemned as insufficient when Tim O’Reilly calls for “algorithmic regulation”? It would be all too easy to invoke the algorithmic as simply the opposite of what is done subjectively or by hand, or of what can only be accomplished with persistent human oversight, or of what is beholden to and limited by context. To do so would draw too stark a contrast between the algorithm and something either irretrievably subjective (if we are glorifying the impartiality of the algorithmic) or warmly human (if we’re condemning the algorithmic for its inhumanity). If “algorithmic” market predictions and search results are produced by a complex assemblage of people, machines, and procedures, what makes their particular arrangement feel different than other ways of producing information, which are also produced by a complex assemblage of people, machines, and procedures, such that it makes sense to peg them as “algorithmic?” It is imperative to look closely at those pre- and non-algorithmic practices that precede or stand in contrast to those we posit as algorithmic, and recognize how they too strike a balance between the procedural and the subjective, the machinic and the human, the measured and the ineffable. And it is crucial that we continue to examine algorithmic systems and their providers and users ethnographically, to explore how the systemic and the ad hoc coexist and are managed within them.

      To highlight their automaticity and mathematical quality, then, is not to contrast algorithms to human judgment. Instead it is to recognize them as part of mechanisms that introduce and privilege quantification, proceduralization, and automation in human endeavors. Our concern for the politics of algorithms is an extension of worries about Taylorism and the automation of industrial labor; to actuarial accounting, the census, and the quantification of knowledge about people and populations; and to management theory and the dominion of bureaucracy. At the same time, we sometimes wish for more “algorithmic” interventions when the ones we face are discriminatory, nepotistic, and fraught with error; sometimes procedure is truly democratic. I’m reminded of the sensation of watching complex traffic patterns from a high vantage point: it is clear that this “algorithmic” system privileges the imposition of procedure, and users must in many ways accept it as a kind of provisional tyranny in order to even participate in such a complex social interaction. The elements can only be known in operational terms, so as to calculate the relations between them; every possible operationalized interaction within the system must be anticipated; and stakeholders often point to the system-ness of the system to explain success and explain away failure. The system always struggles with the tension between the operationalized aims and the way humanity inevitably undermines, alters, or exceeds those aims. At the same time, it’s not clear how to organize such complex behavior in any other way, and still have it be functional and fair. Commitment to the system and the complex scale at which it is expected to function makes us beholden to the algorithmic procedures that must manage it. From this vantage point, algorithms are merely the latest instantiation of the modern tension between ad hoc human sociality and procedural systemization — but one that is now powerfully installed as the beating heart of the network technologies we surround ourselves with and increasingly depend upon.


      1. This parallels Kowalski’s well-known definition of an algorithm as “logic + control”: “An algorithm can be regarded as consisting of a logic component, which specifies the knowledge to be used in solving problems, and a control component, which determines the problem-solving strategies by means of which that knowledge is used. The logic component determines the meaning of the algorithm whereas the control component only affects its efficiency.” (Kowalksi, 424) I prefer to use “model” because I want to reserve “logic” for the underlying premise of the entire algorithmic system and its deployment.

      2.See Kockelman 2013 for a dense but superb example.

      3.See Brian Christian, The A/B Test: Inside the Technology That’s Changing the Rules of Business.” Wired, April 25.


      Barocas, Solon, Sophie Hood, and Malte Ziewitz. 2013. “Governing Algorithms: A Provocation Piece.” Available at SSRN 2245322.

      Beer, David. 2009. “Power through the Algorithm? Participatory Web Cultures and the Technological Unconscious.” New Media & Society 11 (6): 985-1002.

      Bucher, T. 2012. “Want to Be on the Top? Algorithmic Power and the Threat of Invisibility on Facebook.” New Media & Society 14 (7): 1164-80.

      Cheney-Lippold, J. 2011. “A New Algorithmic Identity: Soft Biopolitics and the Modulation of Control.” Theory, Culture & Society 28 (6): 164-81.

      Diakopoulos, Nicholas. 2013. “Algorithmic Accountability Reporting: On the Investigation of Black Boxes.” A Tow/Knight Brief. Tow Center for Digital Journalism, Columbia Journalism School.

      Downey, Gregory J. 2014. “Making Media Work: Time, Space, Identity, and Labor in the Analysis of Information and Communication Infrastructures.” In Media Technologies: Essays on Communication, Materiality, and Society, edited by Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A Foot, 141-66. Cambridge, MA: The MIT Press.

      Geiger, R. Stuart. 2014. “Bots, Bespoke, Code and the Materiality of Software Platforms.” Information, Communication & Society 17 (3): 342-56.

      Gillespie, Tarleton. 2012a. “Can an Algorithm Be Wrong?” Limn 1 (2).

      Gillespie, Tarleton. 2012b. “The Dirty Job of Keeping Facebook Clean.” Culture Digitally (Feb 22).

      Gillespie, Tarleton. 2014. “The Relevance of Algorithms.” In Media Technologies: Essays on Communication, Materiality, and Society, edited by Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A Foot, 167-93. Cambridge, MA: The MIT Press.

      Gitelman, Lisa. 2006. Always Already New: Media, History and the Data of Culture. Cambridge, MA: MIT Press.

      Hillis, Ken, Michael Petit, and Kylie Jarrett. 2013. Google and the Culture of Search. Abingdon: Routledge.

      Kockelman, Paul. 2013. “The Anthropology of an Equation. Sieves, Spam Filters, Agentive Algorithms, and Ontologies of Transformation.” HAU: Journal of Ethnographic Theory 3 (3): 33-61.

      Kowalski, Robert. 1979. “Algorithm = Logic + Control.” Communications of the ACM 22 (7): 424-36.

      Kushner, S. 2013. “The Freelance Translation Machine: Algorithmic Culture and the Invisible Industry.” New Media & Society 15 (8): 1241-58.

      MacCormick, John. 2012. 9 Algorithms That Changed the Future. Princeton: Princeton University Press.

      Mager, Astrid. 2012. “Algorithmic Ideology: How Capitalist Society Shapes Search Engines.” Information, Communication & Society 15 (5): 769-87.

      Morozov, Evgeny. 2014. To Save Everything, Click Here: The Folly of Technological Solutionism. New York: PublicAffairs.

      O’Reilly, Tim. 2013. “Open Data and Algorithmic Regulation.” In Beyond Transparency: Open Data and the Future of Civic Innovation, edited by Lauren Goldstein and Lauren Dyson. San Francisco, Calif.: Code for America Press.

      Rieder, Bernhard. 2012. “What Is in PageRank? A Historical and Conceptual Investigation of a Recursive Status Index.” Computational Culture 2.

      Seaver, Nick. 2013. “Knowing Algorithms.” Media in Transition 8, Cambridge, MA. 

      Striphas, Ted (2010) “How to Have Culture in an Algorithmic Age” The Late Age of Print June 14.

      Striphas, Ted (2012) “What is an Algorithm?” Culture Digitally Feb 1.

      Uricchio, William. 2011. “The Algorithmic Turn: Photosynth, Augmented Reality and the Changing Implications of the Image.” Visual Studies 26 (1): 25-35.

      Williams, Raymond (1976/1983) Keywords: A Vocabulary of Culture and Society. 2nd ed. Oxford: Oxford University Press.

      Ziewitz, Malte. 2011. “How to think about an algorithm? Notes from a not quite random walk,” Discussion paper for Symposium on “Knowledge Machines between Freedom and Control”, 29 September 29.

      -Contributed by ,  Cornell University Department of Communication-

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      Prototype [draft] [#digitalkeywords] Jun 19, 2014

      “…the material, technical and organizational elements of prototypes are always also potentially symbolic. Advocates within an engineering firm or a political campaign can turn them into stories. Outsiders such as journalists can also take them up and turn them into the elements of national or even global memes. In each case, particular sociotechnical configurations become available as potential visions of a larger and presumably better way of organizing society as a whole.”

      The following is a draft of an essay, eventually for publication as part of the Digital Keywords project (Ben Peters, ed). This and other drafts will be circulated on Culture Digitally, and we invite anyone to provide comment, criticism, or suggestion in the comment space below. We ask that you please do honor that it is being offered in draft form — both in your comments, which we hope will be constructive in tone, and in any use of the document: you may share the link to this essay as widely as you like, but please do not quote from this draft without the author’s permission. (TLG)


      Prototype — Fred Turner, Stanford University

      Silicon Valley is a land of prototypes. From cramped, back-room start-ups to the glass-walled cubicle farms of Apple and Oracle, engineers labor day and night to produce working models of new software and new devices on which to run it. These prototypes need not function especially well, or even hardly at all. What they have to do is make a possible future visible. With a prototype in hand, a project ceases to be a pipedream. It becomes something an engineer, a manager, and a marketing team can get behind.

      But this is only one kind of prototype, and in many ways, it’s the easiest to describe. Silicon Valley produces others, sometimes alongside software and hardware, in the stories salesmen tell about their products, and sometimes well away from the digital factory floor, in the lives that engineers and their colleagues lead. When salesmen pitch a new iPhone or, say, new software for mapping your local neighborhood, they often also pitch a new vision of the social world. Their devices Will Change Human History For The Better – and you can glimpse the changes to come right there, these hucksters suggest, in the stories they tell. As they enter the marketplace, the technology-centered worlds these storytellers have talked into being become models for society at large. Likewise, when engineers and their colleagues gather at festivals like Burning Man, or even when they huddle in the tiny, under-financed, hyper-flexible teams that drive start up development, they engage in modeling and testing new forms of social organization, often self-consciously. Like the constellations of people and machines described in marketing campaigns, these modes of gathering have technologies at their center, but they are also prototypes in their own right – of an idealized form of society.

      These social prototypes present a puzzle for those who take “prototype” to be a digital key word: How is it that a term so closely wedded to engineering practice should also be so clearly applicable to the non-technical social world? Much of the answer depends on the work of hardware and software engineers, who have exported their modes of thinking and working far beyond the confines of Silicon Valley. But much also depends on the peculiarly American context in which these engineers work. In the United States, the concept of the “prototype” has a dual history. It is rooted in engineering practice, but it is also rooted in Protestant and especially Puritan theology. By briefly tracing these two traditions, I hope not only to excavate the history of the term, but through it, to begin to explain how and why Silicon Valley has itself become a model metropolis in the minds of many around the world.

      The Prototype in Software Engineering

      Within the world of software and computer engineering, the prototype is a relatively new arrival. In other industries, three-dimensional models of forthcoming products have been the norm for generations. Architects have long built scale models of houses, for instance, just as ship-makers have built scale models of their vessels. These models give three-dimensional life to measurements first defined on a blueprint, just as the blueprint gives two-dimensional form to ideas that emerged in conversations between the architect, the ship-maker, and their clients. For industries such as these, prototypes have long constituted an ordinary link in a chain of activities by which ideas become defined, modeled, and built.

      Until the late 1980s, most software architects approached a new project simply by attempting to define its features on paper in something called a “requirements document.”[1] Many still do today. One technical writer describes the process thus: “Take a 60-page requirements document. Bring 15 people into a room. Hand it out. Let them all read it.” [2] This process has a number of advantages. First, such documentation produces very precise specifications in a language that all developers can understand. Second, the document can be edited as the project evolves. Third, because it lives on paper and usually in a binder somewhere in an office, the continuously updated requirements document can serve as a repository, a passive reminder of what the team has agreed to do.

      Unfortunately, requirements documents can also leave developers unable to see their work whole. After handing out a large requirements document and letting everyone read it, the technical writer above says, “Now ask them what you’re building. You’re going to get 15 different answers.” Requirements documents can confuse developers as well as inform them. They can also leave out users. Developers routinely talk with their clients before drafting requirements documentation, but they often discover that users’ actual needs change as systems come online. Translating these changes into the requirements documents and then back again into the product can be complicated and time-consuming. Finally, diagrams do little to help systems developers and clients create a shared language in which to discuss these changes.[3]

      Enter the prototype. In a 1990 manual for developers entitled Prototyping, Roland Vonk argued that building a working if buggy software system could transform the requirements definition phase of system development. The prototype could become an object, like an architect’s model, around which engineers and clients could gather and through which they could articulate their needs to one another. It would speed development, improve communication, and help all parties arrive at a better definition of requirements for the system.

      It would also be fun. “Prototypes encourage play,” wrote one developer.[4] In the process, they also allow various stakeholders to make an emotional investment in the future suggested by the model at hand. Being by definition incomplete, prototypes encourage stakeholders to work at completing the object. Playing with prototypes helps stakeholders not only imagine, but to a limited degree, act out the future the prototype exemplifies. The experiential aspect of prototypes also renders the projects they represent especially available to the kinds of performances and stories out of which marketing campaigns are made. Consider this brief account, penned by the designer of a computer joystick:

      Our first prototypes gave [the client firm] Novint and its investors a first peek at what was an exciting, yet nascent, concept. We started with sexy prototypes (we call them appearance models) that captured a vision for what the product might become down the road. By sexy, I mean models in translucent white plastic and stainless steel that took their cues from the special effects found in science fiction movies that gamers enjoy. This created a target for what the final product could be and also helped the company build investor enthusiasm around the product idea.

      With…our first prototypes in hand, Novint could create a narrative about where it was headed with this product. It was a story that now had some tangible components and emotional appeal, thanks to the physical models prototyped by [our] designers. That was a promising start.[5]

      As Lucy Suchman and others have pointed out, information technologies represent “socio-material configurations, aligned into more or less durable forms.” [6] Prototypes represent sites at which those configurations come into being. Prototypes simultaneously make visible technical possibilities and actively convene new constituencies. These stakeholders can help bring the technology to market, but they also represent new social possibilities in their own right. The pattern in which they’ve gathered can itself become a model for future gatherings, within and even beyond the industry in question.

      Daniel Kreiss has put this point succinctly: “While most of the literature on prototypes focuses on small-scale artifacts and research labs, there is no theoretical reason why prototypes do not also exist at the field level.”[7] Kreiss has tracked the use of what he calls “prototype campaigns” across several presidential voting cycles. In a 2013 paper for Culture Digitally, he explored two: the Howard Dean and Barack Obama campaigns of 2004.[8] The Dean campaign took exceptional advantage of digital technologies. It recruited leading consultants and computer scientists, built powerful databases of voters, and established a visible web presence. Dean staffers called their work an “open-source” campaign. In the process, as Kreiss explains, they not only aligned various stakeholders around computers and data; they also turned their use of computers and data into evidence that they belonged at the center of a much larger cultural story. Through that story, they claimed the kind of cultural centrality and national legitimacy that most outsider candidates can only dream of.

      When the Dean campaign imploded, the Obama campaign was only too happy to adopt key members of his technology team and to claim that Obama too was running a bottom-up, technology enabled campaign. As Kreiss has shown, they were not. On the contrary, the Obama campaign used computers to centralize and manage the same kinds of data and power on which elections have always depended.[9] But as a symbol, the Obama campaign seemed to model a world emerging simultaneously in the computer industry, a world that Americans could imagine would be open, networked, individualistic and free.

      Change by Design

      There is a tension here between the sense of the campaign itself as a prototype and its depiction as a prototype. In Suchman’s account, information technologies generate social arrangements. In Kreiss’s, the sociotechnical arrangements of campaigns become elements of stories that in turn legitimate future actions. For the designers of the Novint joystick, prototypes play both roles. Taken together, these three accounts remind us that the material, technical and organizational elements of prototypes are always also potentially symbolic. Advocates within an engineering firm or a political campaign can turn them into stories. Outsiders such as journalists can also take them up and turn them into the elements of national or even global memes. In each case, particular sociotechnical configurations become available as potential visions of a larger and presumably better way of organizing society as a whole.

      Within Silicon Valley, there are a host of organizations devoted to identifying and promulgating promising social prototypes. These include futurist outfits, research firms, and venture capitalists, among many others. Few firms transform engineering prototypes into social prototypes more self-consciously or more visibly than the Palo Alto-based design firm IDEO. Founded in 1978, the firm applies what it calls “design thinking” to every aspect of its client organizations, including individual products and brands, as well as software development, communication strategy, and organizational structure. For any given product, the firm can coordinate every aspect of the prototyping process at the engineering level and at the same time, it can link the devices and processes that emerge to new kinds of stories.

      To get a feel for how IDEO transforms engineering prototypes into social prototypes, one need only consult CEO and President Tim Brown’s 2009 book, Change by Design: How Design Thinking Transforms Organizations and Inspires Innovations. Part business how-to, part advertisement for IDEO, the book outlines the firm’s philosophy of “design thinking” and shows how it has worked in a variety of specific cases. Within design thinking, prototyping occupies two places. The first would be easy for most anyone in Silicon Valley to recognize as an ordinary part of manufacturing. Prototyping stands as the opposite of “specification lead, planning driven abstract thinking.”[10] IDEO founder David Kelly calls it “thinking with your hands.”[11]As Tim Brown points out, prototyping can be cheaper and faster than simply drawing diagrams, and it can engage users in shaping products as they emerge. Brown also argues that to enable prototypes to have real impact, designers need to embed them in stories. These “plausible fictions,” says Brown, help designers keep their end users in mind and help potential customers, within and outside the firm, imagine what they might do with the objects and processes being prototyped.[12]

      Thus far, Brown’s discussion of prototypes echoes conversations in most any prototype-oriented engineering space. But toward the end of his book, Brown takes a millenarian turn. “We are in the midst of an epochal shift in the balance of power,” he argues. Corporations have turned from producing goods to producing services and experiences. Customers have become something more than mere buyers. According to Brown, they have become collaborators, co-constructors of the product-experiences they acquire. Lest the reader imagine this to be a purely commercial transformation, Brown argues that “What is emerging is nothing less than a new social contract” – a contract so revolutionary that it could save the planet: “Left to its own, the vicious circle of design-manufacture-marketing-consumption will exhaust itself and Spaceship Earth will run out of fuel. With the active participation of people at every level, we may just be able to extend this journey for a while longer.”[13]

      The notion that consumer choice and political choice can be fused and that together, they can save humanity from itself, has haunted the marketing of digital media for more than twenty years. But there is more than marketing at stake in Change by Design. For Brown, prototyping has become a way to transform the local, everyday work of engineering into a mode of personal spiritual development. “Above all, think of life as a prototype,” writes Brown:

      We can conduct experiments, make discoveries, and change our perspectives. We can look for opportunities to term processes into projects that have tangible outcomes. We can learn how to take joy in the things we create whether they take the form of a fleeting experience or an heirloom that will last for generations. We can learn the reward comes in creation and re-creation, not just in the consumption of the world around us. Active participation in the process of creation is our right and our privilege. We can learn to measure the success of our ideas not by our bank accounts but by their impact on the world.[14]

      For engineers, prototypes must be things or stories. For analysts like Suchman and Kreiss, as well as for engineers, they can be constellations of people and things that become elements in narratives that in turn have marketing or political force. But for Brown, prototyping is something much more. Prototypes as he describes them belong to a way of looking at the world in which individuals constantly remake themselves, in which they test themselves against the world and if they find themselves wanting, improve themselves. Their quest for self-improvement in turn models the possibility of global transformation. In this vision, making a better product in the factory models and justifies the process of making a better self in everyday life. Making both together, through the process of participation and with proper attention to metrics and measurement, might even prevent the apocalyptic crash of Spaceship Earth.

      Puritan Typology

      Brown’s world-saving rhetoric is a staple of Silicon Valley. But it did not originate there. To understand how Brown and his readers could imagine themselves as prototypes, we need to turn backward in time, trek three thousand miles to the east, and revisit the Puritans of colonial New England. When the Pilgrims landed on Cape Cod, they brought with them an extraordinarily rich practice of Biblical exegesis that they called “typology.” In their view, as in the view of Biblical scholars all the way back to Saint Augustine, events in the Old Testament served as “types” – which we would now call “prototypes” – of events in the life of Christ recounted in the New Testament.[15] When Jonah spent three days in the belly of a whale, for example, he foreshadowed Christ’s burial and resurrection.[16] For the Puritans, types were not simply symbols in stories; rather, they represented God’s efforts to speak to fallen man through his limited senses. In this view, Jonah really did go down under water and when he rose up, he sent word out through time that soon Christ himself would go down under the earth and rise up too. The Bible simply recorded these facts.

      For the Puritans, typology did not stop at the level of the text. Rather, it offered them a vision of the world as a text. In the typological view, God had written his will into time. History consisted of a series of prophecies, rendered in the world as prototypical events, and fulfilled by later happenings. The Biblical exodus of the Israelites, for instance, foreshadowed the migration of the Puritans themselves from England to the New World. To their congregants, the Puritan ministers of Boston and Cambridge seemed to have been prefigured by the saints of the Bible and to serve as types of saints yet to come. Each individual’s life was little more than a single link in a chain of types. On the one hand, an individual such as Cotton Mather might see himself as the fulfillment of a mode of sainthood prophesied in the Bible. And on the other, his congregation might see him as an example to follow into a heavenly future. For the Puritans, history moved ever forward toward the completion of divine prophecy. But the type – or, again, prototype – pointed both forward and backward in time. The Puritan type was a hinge between past and present, mortal and divine.

      For individual Puritans, the ability to read the world as a series of types carried enormous meaning. The doctrine of predestination, to which all New England Puritans subscribed, asserted that God had already decided whom to save and whom to send to hell. There was nothing anyone could do about their fate. This belief however, set off an extraordinary effort among living Puritans to spot signs of their possible election.[17] After all, what God could be so cruel as to curse in life those He was about save for all eternity? By the early 1700s, the signs of likely salvation included most prominently to read the natural world of New England as a series of types, written into history by God.

      By now, you might have begun to wonder what, if anything, seventeenth and early eighteenth century theology might have to do with contemporary science and engineering. One answer is that it was in early eighteenth century New England that Newtonian physics met Puritan theology and it was there that American scientists and engineers first linked scientific progress and Puritan teleology. No one did this more gracefully than the minister Jonathan Edwards. Though many remember Edwards today as the author of the quintessential fire-and-brimstone sermon “Sinners in the Hands of an Angry God,” Edwards also wrote widely on science and philosophy. Throughout his life he kept a notebook in which he recorded his struggles to fuse the scientific and the divine. Published under the title Images or Shadows of Divine Things in 1948, the notebook simply records the types that Edwards believed he saw in nature.

      Consider the following, fairly typical entry:

      The whole material universe is preserved by gravity or attraction, or the mutual tendency of all bodies to each other. One part of the universe is hereby made beneficial to another; the beauty, harmony, and order, regular progress, life, and motion, and in short all the well-being of the whole frame depends on it. This is a type of love or charity in the spiritual world.[18]

      For Edwards, gravity explicitly modeled God’s love for man. But implicitly, Newton’s discovery of gravity and Edwards’ own ability to recognize gravity as a type, marked Newton and Edwards as potential member’s of God’s elect. In Edwards’ typological history, theology and science marched hand in hand toward the end of time, each illuminating God’s will and each producing saints to do that work.

      Which brings us back to Tim Brown, IDEO, and Silicon Valley. For some time now, analysts have suggested that the digital utopianism that continues to permeate Northern California came to life only there. In fact, an archeological exploration of the term “prototype” reveals that the habit of linking scientific and engineering practice to a historical teleology rooted in Christian theology can be traced back to New England, if not farther. As he declaims the power of design thinking to save the world, Tim Brown echoes the Puritan divines of centuries past. They too called on their readers to see their lives as prototypes and to see prototyping as a project that might save their souls and perhaps even the fallen world. Though Brown nowhere refers to God, his volume fairly aches with a longing to find a global meaning in his life and work, to know that he and IDEO are on the side of the angels, that they are not just fallen souls, marketing their wares as best they can, in the corrupt metropoles of capitalism.

      So What Are Prototypes?

      With this brief history of Puritan typology in hand, we can begin to complicate the picture of prototypes that we have received from engineering. In computer science and many other disciplines, engineers build prototypes to look forward in time. They hope to anticipate challenges, reveal user desires, and engage stakeholders in the kinds of experiences that will generate buzz about the product, within and beyond the boundaries of the firm. In Silicon Valley, as elsewhere, intermediaries such as IDEO turn these constellations of technologies and people into elements in stories which can in turn serve to legitimate and even model new social forms. To the extent that we see prototypes as exclusively forward looking, then the process of turning engineering and its products into models of ideal social worlds may look simply like another stage in the conquest of everyday life by the information industries.

      Yet, as Puritan typology reminds us, prototypes always look backward in time as well as forward. The means by which they gather society and technology have their roots in worlds that precede and prefigure the futures they will call out for. And the particular mode of prototyping practiced by Tim Brown and many others in Silicon Valley has its roots not only in the world of engineering, but in the theology of Puritan New England. When he and others turn individual products and processes into prototypes of an ideal social world, they are following in the footsteps of Puritan divines like Jonathan Edwards. They are hardly Puritans in any theological sense. Yet they too are seeking to reveal a hidden order to everyday life. They too hope to uncover a hidden road to heaven and to take their place as saints along the way. They too are wondering whether they have been chosen. And they are offering prototyping to their readers as a method by which they too might discover their own election.

      The affordances of engineering prototypes assist in this process. Because prototypes are incomplete, half-cooked, in need of development, they solicit the collaboration of users and others in the building of a particular future. Because prototypes emerge from the laboratory or the office, they can seem to have no politics. They become enormously difficult to recognize as carriers of a particular teleology. Even as they begin to shadow forth a new social order, one in which engineers and marketers become ministers and the marketplace a kind of congregation, the sheer a-historicity of the prototype shields its makers and their structural ambitions from recognition.

      As scholars then, we need to ask new questions of the prototypes we encounter. We need to ask, How does a given prototype summon the past, as well as foreshadow a particular future? For what purposes? What sort of teleology does it invoke? And what sort of historiography does it require? How do prototypes leave the lab bench and the coder’s cubicle to become elements in stories about the world as a whole? How do engineering prototypes become social prototypes? And who wins when they do?

      By answering these questions, we might finally begin to stop thinking of our lives as prototypes and of new technologies as foreshadowings of a divine future.


      1.  Vonk, Roland. Prototyping: The Effective Use of CASE Technology.  New York: Prentice Hall International, 1990, X-XI.

      2. Warfel, Todd Zaki. Prototyping. Rosenfeld Media; November 1, 2009; Safari Books Online, accessed May 12, 2014; section 1.3.

      3.  Vonk, Prototyping, X.

      4.  Warfel, Prototyping, 1.3

      5.  Edson, John. Design Like Apple: Seven Principles For Creating Insanely Great Products, Services, and Experiences; John Wiley & Sons; July 10, 2012; Safari Books Online, accessed May 12, 2014; section “Prototype and the Object.”

      6.  Suchman, Lucy, Randall Trigg, and Jeanette Blomberg. “Working Artefacts: Ethnomethods of the Prototype.” British Journal of Sociology 53, no. 2 (June 2002): 163-79; 163.

      7.  Kreiss, Daniel. “Political Prototypes: Why Performances and Narratives Matter,” Culture Digitally,; posted November 22, 2013; accessed May 12, 2014.

      8.  Ibid.

      9.  Kreiss, Daniel. Taking Our Country Back: The Crafting of Networked Politics from Howard Dean to Barack Obama.  New York: Oxford University Press, 2012.

      10.  Brown, Tim, and Barry Katz. Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation. New York: Harper Business, 2009, 89.

      11.  Kelly, quoted ibid.

      12.  Brown, Change by Design, 94.

      13.  Ibid., 178.

      14.  Ibid., 241.

      15.  Brumm, Ursula. American Thought and Religious Typology.  New Brunswick, N.J.: Rutgers University Press, 1970, 26

      16.  Perry Miller, “Introduction,” in Edwards, Jonathan, and Perry Miller. Images or Shadows of Divine Things.  New Haven: Yale Univ. Press, 1948, 1-42; 6.

      17.  Ibid., 27.

      18.  Edwards, Jonathan, Images or Shadows of Divine Things, entry 79, page 79.

      -Contributed by ,  Stanford University Department of Communication-

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      Memory [draft] [#digitalkeywords] Jun 16, 2014

      “…increasingly ubiquitous digital data storage has had a profound effect on contemporary practices of history and remembrance – and even on the way humans construct and perceive their identities. Discussions of a ‘modernity that forgets’ or an ‘Internet that remembers’ …risk conflating individual cognitive memory, collective and cultural memory, history, storage media, and the archive. ”

      The following is a draft of an essay, eventually for publication as part of the Digital Keywords project (Ben Peters, ed). This and other drafts will be circulated on Culture Digitally, and we invite anyone to provide comment, criticism, or suggestion in the comment space below. We ask that you please do honor that it is being offered in draft form — both in your comments, which we hope will be constructive in tone, and in any use of the document: you may share the link to this essay as widely as you like, but please do not quote from this draft without the author’s permission. (TLG)


      Memory — Steven Schrag, University of Pennsylvania

      “If men learn this, it will implant forgetfulness in their souls; they will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks. What you have discovered is a recipe not for memory, but for reminder.”

      - Plato, The Phaedrus

      “Reminders. Now nothing slips your mind.”

      - Apple Inc., “OS X Apps”

      Memory – from the Latin memoria (the faculty of remembering, remembrance, a historical account), and “mnemonic” from Mnemosyne, mother of the nine Muses in Greek myth – is one of the most fundamental concepts of human identity, and one of its oldest technologies. It is a process, at both the individual and collective level, of narrating and making sense of experience, of storage and recovery. While computer memory (itself an expansive category of devices used to store and recall data or programs) is but one technology of memory among many, increasingly ubiquitous digital data storage has had a profound effect on contemporary practices of history and remembrance – and even on the way humans construct and perceive their identities. Discussions of a “modernity that forgets” or an “Internet that remembers,” however, often risk conflating individual cognitive memory, collective and cultural memory, history, storage media, and the archive.

      Memory, like identity, is a polysemic term expressed as a series of dualities. Both publicly and privately constructed, it comprises the particular and the universal, the natural faculty and the artificial mnemonic, the internal and the external. Historically construed as an art, practiced as a technique in oral societies, retained in objects and architectures, sites and realms, it both mediates (and is mediated by) the analog structures of the brain and the digital records of the hard drive. This essay will outline several of these dualities – the paradoxical relation between remembrance and archival of the past, the tension between technologically-induced amnesia and hypermnesia, and the emergent/everpresent gaps between mnemonic persistence and ephemerality that shape social structures of domination and control – and address the question of whether digital memory intersects cognitive and cultural memory as a surrogate or as a symbiote.

      Paradox and Prosthetic

      “The paradox of a culture which manifests so many symptoms of hypermnesia and which yet at the same time is post-mnemonic is a paradox that is resolvable once we see the causal relationship between these two features. Our world is hypermnesic in many of its cultural manifestations, and post-mnemonic in the structures of the political economy. The cultural symptoms of hypermnesia are caused by a political-economic system which systemically generates a post-mnemonic culture – a Modernity which forgets.”

      - Paul Connerton, How Modernity Forgets

      ”The most common transformation of memory concerns what has been regarded generally as memory undone – amnesia or forgetting. How memories are erased, forgotten, or willed absent has come to be seen as equally important to the ways in which memories are set in place”

      - Barbie Zelizer, Reading the Past Against the Grain: The Shape of Memory Studies

      Conversations about the relationship between technology and memory stretch back to Plato’s injunction in the Phaedrus. The act of archival (of an email on a server, a file in a cabinet, or the commitment of an argument to paper) is fundamentally an act of forgetting, of “externalizing memory” via storage media rather than committing it to biological memory. Walter Ong, who considers Plato’s polemic within a larger history of literacy, casts the mnemonic technology of writing as the catalyst for a fundamental epistemic shift between cultures of orality and literacy; however, unlike Plato, he claims that writing can be both destructive and reconstitutive of memory (1982). Ong highlights a contradiction inherent to prosthetic memory: the same process that Derrida pathologizes as an endless reiteration akin to the death-drive, which he called “archive fever.” Memory, an active process that revives and recreates, calls to mind from the archive that which it archives. Thus the act of remembering, in (re)constructing and (re)mediating the present, traps us paradoxically in the past.

      This paradox of memory replicates the ambiguity of the science-fictional “prosthetic,” perceived either as a liberating cybernetic extension of the self or the dangerous, disembodied Other of cyberpunk. The cyborg, whose embodied and machine-prosthetic memory function as a holistic ubiquitous-feedback mechanism, forms a hybrid communication-control system – the endpoint of which would be, perhaps, a transcendent, McLuhan-esque global consciousness. In striking contrast, the postmodern mythology of cyberpunk asks: are the memories we experience actually ours? For a scholarly understanding of memory, the answer is always both yes and no – as uncertain as Deckard’s status as human or Replicant at the conclusion of Blade Runner – but unlike the hopeful hybridity of Haraway’s cyborg, the cyberpunk myth (epitomized by William Gibson’s foundational novels) separates the “consensual hallucination” of cyberspace from “meatspace.” Scholars of memory studies describe uniquely modern forms of cultural amnesia: the loss of the art of memory amid the displaced rush of liquid modern life. Pierre Nora places history and memory in conflict, narrating the “conquest” of memory by an ever-accelerating history, a vast standing-reserve of documents piled skyscraper-high, burying the past in an act of archival “terrorism”. These fears of amnesia, (dis)embodied in “neuromantic” cyberpunk mythology, confronts the ‘otherness’ of prosthetic memory (Landsberg 1996; Csicsery-Ronay 1988). In a Cartesian schism of virtualized mind and subjugated meat, the cyberpunk myth depicts the self as “the victim…helpless and sad, against the powers of exteriorized mind” (Csicsery-Ronay p277).

      Oblivion and the Archive

      “Who controls the past controls the future; who controls the present controls the past.”

      - George Orwell, 1984

      “The dead past is just another name for the living present. What if you focus the chronoscope in the past of one-hundredth of a second ago? Aren’t you watching the present?”

      - Isaac Asimov, “The Dead Past”

      Discussions of digital memory often begin with the vision of Vannevar Bush, the “memex” (memory-index) – a permanent, electromechanical archive, that would link documents to each other by means of associative trails and annotations resembling the hyperlinked structure of today’s Internet. But Bush’s own position on whether the documents within the memex should be permanent changed over time; his unpublished “Memex II” addresses the need for “a readily alterable record” whose entries can be rewritten or deleted. But with alterability comes the threat of revisionism, whose purest incarnation is the infinitely alterable “memory hole” of Orwell’s 1984: a granular control mechanism into which every inconvenient document is deposited and made to disappear – or reappear – in service of an official historical narrative. Specters of genocide and trauma haunt us, imploring that we “never forget,” yet Avishai Margalit calls for an “ethics of memory” that ensures that the descendants of genocidal trauma do not find themselves shackled by the duty to commemorate (2002). Such concerns echo Plato’s condemnation of writing: that the text can only repeat its “one unvarying answer” to future questioners, lacking the fluidity of transitory orality, unable to evolve and learn. These benefits of forgetting – its potential for redemption/regeneration/reconciliation, its hope for radical change that “escapes” the past, and its evolutionary capacity for public deliberation and production of knowledge – create tension at the ambiguous interface between the transitory individual and the enduring collective.

      Jeffery Rosen and Viktor Mayer-Schönberger similarly argue the “virtue” of forgetting in counterposition to the threat of permanent “comprehensive memory”: “all citizens face the difficulty of escaping their past now that the Internet records everything and forgets nothing” (Mayer-Schönberger 2009; Rosen 2010). Individuals’ past preferences and actions, archived by ubiquitous computing technologies – imperfectly contextualized, in ways that often prove misleading or even inaccurate – haunt them in the present, exposing previous transgressions to public and state scrutiny, and foreclosing on the possibility of rehabilitation or even of change. Rosen and Mayer-Schönberger thus characterize forgetting as a vital form of information control: specifically, individual control over one’s personal information. Their anti-archival policy prescriptions (expungement, in legal terms, or Mayer-Schönberger’s “expiration dates” on some types of archival data) seek to protect this allegedly disappearing faculty of forgetting because of its importance for personal privacy and autonomy. “Comprehensive memory” (rather, comprehensive history) suggests the creation of a “temporal panopticon,” such as that allegorized in Asimov’s short story “The Dead Past”: a fictional “chronoscope,” built for looking into the past, actually functions to eradicate present privacy. Le droit à l’oubli - the “right of oblivion” – creates a legal separation between past crime and present identity by denying our chronoscope-analogues full access to history, allowing a fresh start: the chance to escape one’s past.

      Persistence, Ephemerality, and Power 

      “A major source of forgetting…is associated with processes that separate social life from locality and from human dimensions: superhuman speed, megacities that are so enormous as to be unmemorable, consumerism disconnected from the labour process, the short lifespan of urban architecture, the disappearance of walkable cities. What is being forgotten in modernity is profound, the human-scale-ness of life, the experience of living and working in a world of social relationships that are known. There is some kind of deep transformation in what might be described as the meaning of life based on shared memories, and that meaning is eroded by a structural transformation in the life-spaces of modernity.”

      - Paul Connerton, How Modernity Forgets

      “Quite obviously, remembering has become the norm, and forgetting the exception. Four main technological drivers have facilitated this shift: digitization, cheap storage, easy retrieval, and global reach.”

      - Viktor Mayer-Schönberger, Delete: The Virtue of Forgetting in the Digital Age

      The purported “comprehensive memory” of the digital age is, in fact, neither comprehensive nor permanent. “The World Wide Web still is not a library,” concludes Wallace Koehler after conducting a longitudinal study of the “half-life” of online documents – much less the universal archive of the memex (2004). “Link rot” (hyperlinks whose destination pages are no longer available) introduces significant decay into the associative trails we build through hypertext, complicating access and retrieval; “bit rot” and “data rot” similarly force us to grapple with the degeneration of software through the accumulation of errors over time, and the fragility of the physical discs and drives that comprise our storage media; website providers can go out of business, causing thousands of pages to disappear overnight. The “dark Internet” and the “Deep Web” remind us that our means of indexing even the archival data we have are incomplete and impermanent.

      Much of the Internet’s content is still characterized by its practical ephemerality: in one striking example, the average thread on 4chan’s popular /b/ message board spends just five seconds on the first page, and five minutes on the site in total, before its content vanishes (Bernstein et al. 2011). “Ephemeral technologies” like Snapchat, which delete information shortly after its receipt, once again make forgetting rather than remembering the default. While these software solutions are defeated by a “hack” as simple as a screenshot, requiring users to rely on social convention for the privacy and security of their correspondence, the lack of a persistent, searchable archive of data in such applications demonstrates the development of new social norms and technological architectures in which experiences are fleeting by design.

      But the temporal gaps and untraceable depths of our networked archives intensify, rather than diminish, the need for ongoing critical scrutiny of historical and archival practices. Asymmetries in information control and “information flux,” as well as the ability to analyze and interpret, affect power dynamics between individuals and institutions. David Brin’s unrealizable “transparent society,” in which individuals and organizations have equal access to each other’s data, “postulates the end of privacy,” according to Bossewitch and Sinnreich, “but it fails to adequately account for the differential access to analytic processing power available to different individuals and organizations in making sense – and use – of this data” (2013). In turn, however, the lacunae in archival memory are shaped by these power dynamics; as Susan Brison notes, “As a society, we live with the unbearable by pressuring those who have been traumatized to forget and by rejecting the testimonies of those who are forced by fate to remember” (1996). The desire for recovery and forgiveness, the hidden virtues of ephemerality, can also reflect institutional power – resulting in the erasure of trauma or systemic injustice not only from archives, but from societal and individual memory as well. In the absence of a symmetrically transparent utopia, crucial questions remain, bound up with traditional concerns about selective cultural amnesia, surveillance, and power: who controls the archives, the official histories that modulate collective memory? Who surveils the past, who is surveilled, and who has the capacity to evade surveillance? How can we disrupt hegemonic narratives of the past – violent impositions of identity akin to the “memory implants” of Total Recall – and create new and emancipatory narratives?

      Surrogacy or Symbiosis?

      “Because we do not understand the brain very well we are constantly tempted to use the latest technology as a model for trying to understand it. In my childhood we were always assured that the brain was a telephone switchboard. (‘What else could it be?’) I was amused to see that Sherrington, the great British neuroscientist, thought that the brain worked like a telegraph system. Freud often compared the brain to hydraulic and electro-magnetic systems. Leibniz compared it to a mill, and I am told some of the ancient Greeks thought the brain functions like a catapult. At present, obviously, the metaphor is the digital computer.”

      - John R. Searle, Minds, Brains and Science

      The way we conceive of natural symbol systems depends to a large degree on the computational metaphors we use to understand them, and machine learning suggests an understanding of symbolic thought that is very different to traditional views…Our analysis of [predictive, probabilistic symbolic communication] arose out of the idea that the mind can be modeled as a kind of learning machine.”

      - Michael Ramscar, “Computing Machinery and Understanding”

      Our understanding of the mind, and thus of memory, remains in flux. In practice, individuals’ everyday use of mnemonic technologies is contingent, subject to constant change in the form and function of their devices (Kalnikaite and Whittaker 2007). The relationship between organic and prosthetic memory appears to be one of synergy and symbiosis rather than surrogacy. Our metaphors for mind have historically modeled cognition as a pneumatic system, a clockwork automaton, a helmsman steering a ship, an enchanted mechanical loom; today, we may more readily compare the mind to a search engine, algorithmically retrieving stored data from a disorganized network, “learning” from each new delve into its archive.

      But even as we embrace this new metaphor of memory, and use it to imagine both our individual and our collective identities, we derive meaning from the mind-metaphors of past eras, which possess their own political and poetic histories. Contemporary “cloud computing” extends cyberpunk notions of disembodied mind into the present day, while proliferating “augmented reality” technologies reinvigorate hopes and fears about the potential of cyborg remembrance either to emancipate or dehumanize. Digitally reconstructed memory and forgetting continue to exist in a state of paradox and plurality, inviting continued conversation about our archives, our histories, and ourselves.

      New mnemonic technologies revitalize timeless questions about the contradictory nature of memory – constantly reconstructing the past while prospecting potential futures, in acts as simple as reading old letters from a friend or writing a shopping list – and resurrect familiar specters as well. But as individuals and corporations alike increasingly seek out professional reputation management services to influence their archival afterimages (at least, those who can afford to do so), and the European Court of Justice navigates the tension between privacy and free expression implicated in a (limited) “right to be forgotten” from the index of search engines, these questions and anxieties gain urgency and force. By tracing prevalent themes of information control, surveillance, and power against the background of prosthetic memory, we may hopefully remind ourselves that the term “memory” itself represents more than either synapses or hard disks – that, far from signaling either the end of memory or the end of forgetting, our shifting metaphors for memory and mind represent the complex and multivalent interplay of future and past.

      Works Cited

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      Event [draft] [#digitalkeywords] Jun 12, 2014

      “While events are essential for individuals, societies and media, they are not the sweet hearts of media scholars. Events are like ill-behaved teenagers: they are hard to fit in any rigid system of thought. Many events are idiosyncratic, contour-less and quite resistant to typification, while others are too often repeated to attract scholarly attention.”

      The following is a draft of an essay, eventually for publication as part of the Digital Keywords project (Ben Peters, ed). This and other drafts will be circulated on Culture Digitally, and we invite anyone to provide comment, criticism, or suggestion in the comment space below. We ask that you please do honor that it is being offered in draft form — both in your comments, which we hope will be constructive in tone, and in any use of the document: you may share the link to this essay as widely as you like, but please do not quote from this draft without the author’s permission. (TLG)


      Event — Julia Sonnevend, University of Michigan

      An event – not life, as John Lennon put it – is what happens when you are busy doing other things. Some events happen expectedly, for instance weddings and presidential inaugurations, while other events are sudden shocks, like cancer diagnoses and assassinations. Certain events gain significance beyond a family or a community and become public events. Events can even turn into global iconic events that international media cover extensively and remember ritually. These events produce peaks and crashes on social media and massive global viewing audiences for television. But be planned or unplanned, minor or earthshattering, all these events do the same thing: they structure our social and public lives; give reference points for our life narratives and national histories.

      While events are essential for individuals, societies and media, they are not the sweet hearts of media scholars. Events are like ill-behaved teenagers: they are hard to fit in any rigid system of thought. Many events are idiosyncratic, contour-less and quite resistant to typification, while others are too often repeated to attract scholarly attention. What then might be the purpose of an essay on the relationship between media research and events? Is the task simply impossible?

      Possibly. But some disciplines have already tried the impossible. Sociology, that according Daniel Bell specializes in generalization, has considered the general within the singular in its own burgeoning event literature (Abbott, 1983, 1990, 2001; Abrams, 1982; Alexander, 2002, 2009, 2012; Eyerman, 2011; Jacobs, 2000; Mast, 2012; Vinitzky-Serroussi, 2002, 2011; Wagner-Pacifici, 2010). History, otherwise dedicated to singularity, has also detected repetitive features in the narration of events (Bailyn, 1963, 1982; White, 1973; Sewell, 1996). And philosophy has produced a small bookshelf of literature on the elusive concept of events (Badiou, 2005; Danto, 1985; Hegel 1831; Ricoeur, 1984).

      Some media researchers too have wrestled with events. For instance, Amit Pinchevski and Tamar Liebes (2010) wrote about the media coverage of the Eichmann trial as a public event. Daniel Hallin (1986) and Marita Sturken (1997) analyzed the media constructions of the Vietnam War. Barbie Zelizer (1992) examined the media representations and retellings of the Kennedy assassination. Some scholars have moved beyond the particular and singular to define whole genres of media events: these genres include for instance media scandals (Lull & Hinerman, 1997), disaster marathons (Liebes, 1998), media spectacles (Kellner 2003), social dramas of apology (Kampf, 2009; Kampf & Löwenheim, 2012), rituals of excommunication (Carey, 1998), live-covered events (Scannell, 2014) and mediatized rituals (Cottle, 2006).

      But very few studies in media research put the concept of “event” in the center of their analysis. In most cases, events are taken-for-granted entities, simply ready for narration or identical with their narratives. An important exception is Daniel Dayan and Elihu Katz’s Media Events: The Live Broadcasting of History (1992). Inspired by the television coverage of a major historic event, Egyptian President Anwar el-Sadat’s peace-making visit to Israel in 1977, Media Events developed a taxonomy for “media events.” A “media event” had to (1) be broadcast live, (2) constitute an interruption of everyday life and everyday broadcasting, (3) be preplanned and scripted, and (4) be viewed by a large audience. There should also be (5) a normative expectation that viewing was obligatory and (6) a reverent narration. Moreover, the event had to be (7) integrative of society and (8) mostly conciliatory (Dayan & Katz, 1992; Katz & Liebes, 2007).

      Building on Max Weber’s concept of rational-legal, charismatic and traditional authority, Dayan and Katz also presented three scripts of media events. These were contests (for instance the Olympic Games and the Watergate hearings), conquests (such as the landing on the Moon and Pope John Paul II’s visit to Communist Poland) and coronations (for example the funeral of President Kennedy and the Royal Wedding of Prince Charles). Many scholars have subsequently critiqued and built on Dayan and Katz’s understanding of media events (Rothenbuhler, 1988; Zelizer, 1992; Scannell, 1996, 2014; Schudson, 1993; Price & Dayan, 2008; Couldry, Hepp & Krotz, 2010).

      Dayan and Katz provided us with a strong concept of a “media events” genre, but they also somewhat limited the scope of the general theoretical discussion on “events in media.” What about events that do not have live coverage (like the Cambodian genocide), events that are not covered by television (like the Eichmann trial in Israel) and events that are celebrated in one country but not in the other (the fall of the Berlin Wall in American and Soviet media)? In other words, what about events that are covered by media but not by the canonic Media Events?

      In this keyword essay I will consider “events in media,” including but not limited to the narrow genre of “media events.” I focus on four aspects of events in media: (1) the power of the occurrence vis-à-vis its narrative as an “event,” (2) the witnesses who tell the story of an “event,” (3) the embodiments of the “event” in various media, and (4) the travel of “events” through cultural and geographic boundaries.

      (1) The power of the occurrence vis-à-vis its narrative as an event

      Every event consists of some happening on the ground and a related narrative of an event. Four planes were deliberately crashed in the United States on September 11, 2001, these happenings altogether received the name “9/11.” On November 9 in 1989, after the desperate East German leadership mistakenly announced a new travel regulation in immediate effect, West German broadcast media convinced people to test the border in Berlin – an awkward occurrence that quickly precipitated the event later called “the fall of the Berlin Wall.” Or, to take another example, the systematic mass murder perpetrated during the WWII, originally narrated as an “atrocity,” became a moral universal in the West described over time as the “Holocaust” (Alexander, 2002). In all these cases a myriad of occurrences were pulled together in a narrative of an “event.”

      But while narratives seem powerful tools in shaping events, they are not omnipotent. Consider the example of terrorist attacks. Seemingly they can be narrated in opposing ways, as acts of wanton destruction or as acts in observance of a higher moral order. A good example of framing a terrorist attack as a regrettable but unavoidable must is presented by a plaque on the King David Hotel in Jerusalem: “The hotel housed the Mandate Secretariat as well as the Army Headquarters. On July 22, 1946, [Zionist paramilitary] Irgun fighters at the order of the Hebrew Resistance Movement planted explosives in the basement. Warning phone calls had been made urging the hotel’s occupants to leave immediately. For reasons known only to the British, the hotel was not evacuated and after 25 minutes the bombs exploded, and to the Irgun’s regret and dismay, 91 persons were killed.” This original wording infuriated the British for suggesting that the British, not the Irgun, were responsible for the attack. Although the wording was subsequently revised, the final sentence of “regret and dismay” remained.

      This excerpt shows the power of narratives in shaping occurrences into certain types of events, but it does not prove that narratives are capable of everything. We can narrate a terrorist attack as a crime or as an accident, but not as a wedding. Our narratives are flexible, but we cannot do whatever we want with them.  As Michael Schudson summarized the limits of our narrative power: “there are events in the world we can shape, distort, reinterpret but not fundamentally change. President Kennedy was killed by an assassin. There are lots of ways to read this fact but none of them restore John F. Kennedy to life. He really died” (Schudson, 2008, p. 92). There are many limited ways to read events.

      (2) The witnesses of the event

      Who sees and tells the story of an event, who writes its “birth certificate,” is central to every event’s existence. Storytellers are required to bind occurrences together and elevate them into an “event.” In other words, events need witnesses (Peters, 2001). Media witnessing occurs in three distinct forms: witnesses in media (when witnesses of the occurrence share their experiences in media), witnessing by media (when media bear witness to occurrences) and witnessing through media (when audiences are positioned by media as witnesses to occurrences) (Frosh & Pinchevski, 2009). These diverse forms of witnessing all shape the boundaries of events and communicate them to distinct primary and secondary audiences. Events also have competing witnesses, leading to contrasting counter-narratives. All events have diverse witnesses: even interpretations of events that some scholars call “hegemonic” are more multi-colored than they seem to be. Competition among witnesses and among narratives can keep events alive and can destabilize their meanings.

      (3) The embodiments of the event in media 

      Events are more vulnerable than we would think. We easily forget them. We do this not only with wedding anniversaries, but also with major historic events. Each generation has its own events that it regards as earthshattering. For instance, certain generations have flashbulb memories of the atomic bombing of Hiroshima or the Kennedy assassination, other generations never forget the moment they received the news about the attacked Twin Towers. But an iconic event of one generation often appears nothing but boring history for the next. Events are heavy: it is hard to carry them across time, space, and media.

      Therefore, in order to last and get recited across generations, occurrences need memorable narratives that construct them as mythical, resonant “events.” These narratives will also need to be carried by a diversity of media. Even the seemingly most powerful and visually spectacular event cannot survive the passing of time without substantial narrative efforts. A lasting narrative needs to be simple and universal, removed from the event’s original complexity, and transportable through diverse media platforms.

      For instance, consider all the efforts of commemoration to keep the memory of 9/11 alive. Names of the victims are read aloud at Ground Zero at every anniversary, a huge cosmopolitan museum has recently opened in New York, and the event’s story is embodied in social media campaigns, souvenirs, documentaries and history books. Those who remember the day of September 11, 2001 may think it is unforgettable, but it is not. Few college freshmen today have acute personal memories of the event that took place over a decade ago; its lasting resonance will require promotion of the event’s simple narrative and spectacular imagery across “old” and “new” media alike.

      (4) The travel of events across cultural and geographic boundaries 

      Some events have to be narrated “only” on the national, regional or social group level. But global iconic events, that resonate internationally and over time, obviously need transnational media narration. There are five dimensions of their narration in transnational contexts: (1) foundation: the events’ narrative prerequisites; (2) universalization: the development of the event’s mythical message; (3) condensation: the event’s encapsulation in a brand of a simple phrase, a short narrative, and a recognizable visual scene; (4) counter-narration: competing stories about the event; and (5) diffusion, when the event’s brand travels across multiple media platforms and changing social and political contexts (Sonnevend, 2013b).

      Let’s take the example of the fall of the Berlin Wall.

      (1) Its story had narrative prerequisites: the story of the Berlin Wall itself, the global resonance of the city of Berlin, the Berlin airlift, Kennedy’s “Ich bin ein Berliner” speech, among others. The lasting transnational story of the fall of the Berlin Wall has built on these narrative “foundations.”

      (2) The happenings of November 9, 1989 were initially confusing, contradictory, and complex, although soon after the mythical message of the “end of division” turned those happenings into an “event.” In other words, the story went through the narrative process of simplification and universalization.

      (3) This mythical “event” over time got condensed into a branded phrase (“the fall of the Berlin Wall”), a short narrative of freedom, and a recognizable visual scene. This brand became ready for global travel and trading.

      (4) Unlike most global iconic events, the fall of the Berlin Wall is an exceptionally consensual event. Few deny its importance. But at its own time, in 1989, East German and Soviet media counter-narrated it as a minor occurrence, a small happening in a substantial and deliberate reform process they were championing. This counter-narrative did not survive the passing of time.

      (5) The fall of the Berlin Wall as a global iconic event is now embodied in a diversity of media: it travels from mass media to social media to monuments, memorials, exhibitions, souvenirs, and many other media embodiments. The simple and universal narrative of the fall of the Berlin Wall has permeated the world from China to Israel to the United States, providing us with a contemporary social myth.

      Through the above five-dimensional process of transnational storytelling, a global iconic event comes into being. Some global iconic events are more universal than others, some have more counter-narratives than others, but these five dimensions are generally present in their narration.

      In sum, this brief sketch has examined four aspects of “events in media:” (1) the power of the occurrence vis-à-vis its narrative as an “event,” (2) the variable witnesses who tell the story of an “event” and (3) the embodiments of the “event” in various media and (4) the travel of “events” across cultural and geographic boundaries. Events are diverse and tricky creatures. Capturing their elusive meaning remains a challenge. Events also move in and out of public memory, gaining or losing significance and meaning. Nonetheless, events keep shaping our international and personal relations, and continue to occupy our media. While scholarship may fall short of fully capturing global events in media, they continue all the while to engage our imagination.


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      Cyber-activism [draft] [#digitalkeywords] Jun 9, 2014

      “Certainly, in popular discourse, terms like cyber-activism, online activism, and digital activism are used to mean so many different things that they lose their specific meaning. In this way, they can be used conveniently by critics and proponents alike for whatever purposes they want them to serve.”

      The following is a draft of an essay, eventually for publication as part of the Digital Keywords project (Ben Peters, ed). This and other drafts will be circulated on Culture Digitally, and we invite anyone to provide comment, criticism, or suggestion in the comment space below. We ask that you please do honor that it is being offered in draft form — both in your comments, which we hope will be constructive in tone, and in any use of the document: you may share the link to this essay as widely as you like, but please do not quote from this draft without the author’s permission. (TLG)


      Cyber-activism — Guobin Yang, University of Pennsylvania

      In the English language, cyber-activism is a compound word that came into currency in the early 1990s. Although the first half of the word, cyber, appeared later than the other half “activism,” in their current meanings, both components were 20th-century inventions. Cyber- is traced to Norbert Wiener’s Cybernetics: Or Control and Communication in the Animal and the Machine (1948), but is often associated with the science fiction of William Gibson, who is credited with popularizing the word “cyberspace” in his novel Neuromancer (1984). This origin gives cyber-activism, as opposed to the interchangeable terms “online activism” and “digital activism,” the special connotation of magical new possibilities associated with cyberspace in science fiction (Jordan 1999).

      Since the 1990s, a host of synonymous terms has appeared to make cyber-activism part of an extended linguistic family. It includes: electronic activism, online activism, internet activism, web activism, and digital activism. Because  the word “protest” is often used interchangeably with “activism,” the family also includes cyber-protest, electronic protest, internet protest, online protest, and digital protest.

      In addition, there are many other terms of kith and kin, such as tactical media (Garcia and Lovink 1997), radical media (Downing 2000), new media activism (Kahn and Kellner 2004; Lievrouw 2011), alternative media (Couldry and Curran 2003; Lievrouw 2011), hacktivism (Denning 1999; Jordan and Taylor 2004), and networked social movements (Juris 2004; Castells 2012).

      Although these terms are often used interchangeably, they have slightly different shades of meaning.  Terms that were used more often in the 1990s, such as radical media and tactical media, seem to have more radical connotations than later coinages. Although digital activism has not replaced other synonymous terms, it now appears more often than cyber-activism, but it does not have the sci-fi and magical connotations of cyber-activism.

      That there are so many words for describing what purports to be comparable phenomena suggests that something of magnitude is at stake. It betrays deep ambiguities and anxieties concerning the meaning and significance of cyber-activism and its cognates. This essay identifies four ambiguities and traces how these ambiguities are an integral part of a set of discourses about cyber-activism that produces political effects distinct from the effects of cyber-activism as political praxis.


      The first type of ambiguity concerns the very objects of inquiry.  What is meant by cyber-activism, online activism, or digital activism? The difficulties of defining cyber-activism is reflected in the approach adopted by one of the few books with “cyber-activism” in its title. Recognizing that “defining cyberactivism is as difficult as defining activism before the internet,” the editors of the volume Cyberactivism: Online Activism in Theory and Practice decide not to offer a definition (McCaughey and Ayers, 2004, 14). One author represented in the volume, however, defines online activism “as a politically motivated movement relying on the Internet” (Vegh 2003, 71). He then goes on to distinguish among three types of online activism: awareness/advocacy; organization/mobilization; and action/reaction.” (Vegh, 2003, p.72) This often cited definition takes into account both the content of online activism and its technological method. Howard (2011) takes a similar approach when he defines cyberactivism as “the act of using the internet to advance a political cause that is difficult to advance offline.” (p.145).

      In both these definitions, the emphasis on the political nature of cyber-activism begs the question of exactly what counts as political and what not. Vegh’s notion of online activism as a politically motivated movement further complicates the issue by raising the additional question of what exactly counts as a movement. Is it a protest event? A series of events? A campaign? A particular condition of being active? A mode of action? A process? Or does it refer to social movement actors and organizations?

      There are others who view cyber-activism as mainly a set of methods, tactics, and practices associated with the use of new technologies without stressing its political nature. The literature on advocacy in social work, for example, views cyber-activism as methods: “New advocacy methods that use technology to change public policy have been developed and provide us with new avenues to address the changed political economy of social welfare. Collectively called cyberactivism, these techniques can be used to advantage by social work advocates.” (McNutt & Menon, 2008, 33). Yang (2009, p. 3) defines online activism as “contentious activities associated with the use of the Internet and other new communication technologies,” but stresses it as a cultural and political form. Earl and Kimport (2011) propose a continuum of online activism ranging from e-movements that happen purely online to e-mobilization that uses the internet to organize offline protest. For Lievrouw (2011, p. 19), “alternative/activist new media employ or modify the communication artifacts, practices, and social arrangements of new information and communication technologies to challenge or alter dominant, expected, or accepted ways of doing society, culture, and politics.”

      There is a long-time debate about whether social movements are phenomena or meaning (McGee 1980; Melucci 2006). Is cyber-activism meaning or phenomenon? Current discourse seldom asks this question, assuming instead that cyber-activism and its varieties are phenomena existing objectively outside of human consciousness. Without asking the question about subjective meanings and social constructions, what might be a bias (objectivity) becomes natural and a taken-for-granted truth. Certainly, in popular discourse, terms like cyber-activism, online activism, and digital activism are used to mean so many different things that they lose their specific meaning. In this way, they can be used conveniently by critics and proponents alike for whatever purposes they want them to serve. Critical reflexivity about the subjective meanings of cyber-activism will at least make clear that what are taken as natural and objective phenomena may not always be the case and may often be a matter of interpretation.


      The second type of ambiguity arises out of the first part of the term.  Cyber, online, internet, and digital – these are mostly used to refer to the spatial features of these technologies. Cyber- or online activism is often thought of in spatial terms. Because these technological spaces are different from conventional spaces, there are persistent efforts to dichotomize cyber-activism and offline activism, with clear preference given to offline activism.

      This distinction was useful in the earlier stage of cyber-activism, when the technology was still limited in its reach and the use of the internet not yet a routine part of activism. Today, however, the internet, social media, and smart phones are much more prevalent than in the 1990s. Online and offline action becomes highly interfaced. In this new digital environment, it is hard to imagine street protest activities taking place without at least some use of digital media communication. Activism of all varieties, it might be argued, is now digitized to some degree.

      A more serious consequence of the spatial bias in the cyber-activism family is a hidden bias against time. Whether the internet as a technology has a space bias or a time bias is open to debate and not my concern here (see Frost 2003 for an argument in favor of internet’s space bias). But the discourse about cyber-activism clearly has a spatial bias. By fixating our attention on the dichotomy of online vs offline spaces, this discourse reifies the differences between the two and prevents us from asking other important questions. It is generally recognized that new communication technologies decouple time from place. This allows cyberactivism to happen in ways that are not limited by time-space as street protests were in earlier times. People in different time zones and continents now routinely take part in the same online protest event at the same time. Another consequence of the spatial bias is that it neglects that cyber-activism itself has a temporal and historical dimension – today’s cyber-activism is not the same as twenty years ago. If cyber-activism has been accused of turning into slacktivism, is it an inherent attribute of cyber-activism or is it the outcome of historical political struggles? If contemporary cyber-activism is not living up to the revolutionary potential envisioned by its radical advocates in the earlier days, is it due to its inherent weaknesses or is it because it is up against forces far more powerful?


      The third type of ambiguity derives from the word activism. What is the boundary between activism and non-activism? Where does activism begin and end? In social movement studies, high-risk protests have been called activism (McAdam 1986), but so has everyday behavior with purportedly activist motivations (Almanzar, Sullivan-Catlin and Deane 1998). There seems to be a tendency to conflate the more radical types of cyberactivism with its moderate varieties.

      The etymology of activism contains such ambivalence. Activism came from the German word Aktivismus, which was first used by the German philosopher Rudolf Eucken in his 1907 book The Fundamentals of a New Philosophy of Life to refer to “the theory or belief that truth is arrived at through action or active striving after the spiritual life.” (OED, 3nd ed.). In continental Europe during World War I, activism meant “advocacy of a policy of supporting Germany in the war; pro-German feeling or activity” (OED, 3rd ed.). Only by 1920 did activism come to mean active participation or engagement in a particular sphere of activity; spec. the use of vigorous campaigning to bring about political or social change.” The earlier usage in this sense stresses its “vigorous” character. OED’s 1920 quotation for activism is: “Above these people is the ‘brain proletariat’, restless, alert, dissatisfied, repressed… The thought of this brain proletariat has many aspects-from Buddhist passivism to Bolshevist activism.” And its 1960 quotation: “The sizzling flame of activism is visible in both the agricultural and pastoral districts.” In the same way, OED defines an activist as “A person engaged in or advocating vigorous political activity.

      Activism thus had several different meanings in its early history – an orientation to life in Rudolf Eucken’s philosophy, a pro-German activity during WWI, and a vigorous political activity.  Activism and activists could be oppositional to the state, but could also be supportive of it (Hoofd 2008).

      Current discourse about cyber-activism retains both the “vigorous” and radical meanings of activism and the less vigorous and more moderate meanings. The moderate type of activism has been called civic action. As opposed to protest, civic action such as community festivals events have only implicit (or latent) purposes, no explicit claims (Samson, McAdam, MacIndoe, & Weffer-Elizondo 2005, 685). Thus cyber-activism may refer to conflictual direct action such as hacking and denial of service attacks, but it may also mean consensus action of the civic type, such as the use of Twitter by non-profit organizations for community building or information sharing.

      The conflation of radical with consensus cyber-activism is an important feature of a history of domesticating and institutionalizing cyber-activism.  A subtle historical shift takes place whereby the more radical elements of cyber-activism are underplayed or even dislodged. On the one hand, there are government efforts to criminalize radical cyber-activists or corporate efforts to co-opt them. Thus over time, hacktivism takes on connotations of illegality as opposed to its early meanings of countercultural creativity and individual heroism (Jordan 1999).  Radical cyber-activist organizations and practices like Indymedia and the Occupy Wall Street movement were subject to policing (Downing 2001; Pickard 2006; Sullivan, Spicer & Böhm 2011; Gillham, Edwards, and Noakes, 2011). On the other hand, a discourse is produced about the necessity of channeling cyber-activism into institutional politics. “The digirati needs to learn how to make friends and win influence in Washington,” Richard F. O’Donnell warned in 1996 . Otherwise they would be “courting irrelevance.” (O’Donnell 1996). Thus, important cyber movements like eventually becomes member-based non-profit organizations. Like mirror images, these two tendencies (and two sets of discourses) have the same effect of undercutting the potency of cyber-activism as an extrainstitutional praxis and absorbing it into normal institutional politics. This might be called the institutionalization bias.


      This leads to the last ambiguity I will address, namely, the confusion about the political efficacy of cyber-activism. There is, to say the very least, an obsession with causation in the discourse about cyber-activism. Social movement scholars recognize the importance of studying outcomes (Giugni 1998; Amenta et al 2010), but they are also aware that specifying the causes of outcomes is methodologically more challenging than identifying the conditions of the emergence of a social movement. If social movement organizers and activists at least exert some control over the shape of their movement by designing strategies, framing issues, and shaping identities, they cannot directly control the outcomes of their movements (Amenta et al 2010). Furthermore, beyond their pronounced goals, social movements may have unintended consequences and may incur repression and backlashes. Consequently, most works in this area subscribe to the theory that the outcomes of social movements are mediated by multiple factors (Amenta, Caren and Olasky 2005). Outcomes are indirect, not direct. Although in the communication field, there is a fine literature on the mediated effects of internet use on civic participation (e.g., Xenos and Moy 2007), to my knowledge, this literature has not received the attention it deserves in the discourse about the impact of cyber-activism.

      A second confusion concerns the spurious specification of causes and outcomes. Although cyber-activism consists of multiple varieties, there is a curious tendency to cherry-pick the types of cyber-activism and then reject cyber-activism wholesale by claiming that that particular type does not cause an anticipated effect, such as democratization. Thus, email petitions and online comments become clicktivism (Shulman 2009), which is alleged to be politically ineffective. Clicktivism then becomes a synecdoche for cyber-activism, and cyber-activism is then rejected on the ground that it is merely clicktivism. Meanwhile, the more radical manifestations of cyber-activism are omitted.

      The third confusion reflects an ideological imprint in current discourse about cyber-activism. In the debate about cyber-activism and democratization, a question that often arises concerns China and is about whether cyber-activism weakens or strengthens authoritarianism. The logic of this argument runs as follows: China has an authoritarian government. Cyber-activism in China makes the authoritarian government more aware of its vulnerabilities, forcing it to improve governance and therefore making it more resilient. Conclusion: cyber-activism is good to authoritarianism. The problem with this argument is that it not only simplifies the meanings and practices to cyber-activism in China, but also presumes that authoritarian governments are incapable of change while implicitly putting the blame on citizens and activists seeking change. Here, the workings of a hidden efficacy bias turns cyber-activism into its own enemy.


      How to account for these ambiguities? Certainly, they reflect the difficulties of understanding rapid social and technological change.  We should also recognize that cyber-activism is so diverse and fluid that it inevitably comes with ambiguities. Yet insofar as we can identify hidden biases underlying these ambiguities and confusions, I would argue that the existence of these ambiguities is not accidental, but political. Ambiguities serve political purposes.

      The four types of ambiguities are roughly associated with four hidden biases, which I have called the objectivity bias, the space bias, the institutionalization bias, and the efficacy bias. The objectivity bias hinders a more reflexive approach to  cyber-activism. The space bias diverts attention from seeing cyber-activism as a historically contingent political struggle. The institutionalization bias favors consensus and institutionalized over radical cyber-activism by first lumping together the radical with the moderate and then omitting the history of a parallel process of policing, institutionalization, and co-optation. The efficacy bias dismisses cyber-activism as ineffective by focusing on its palmy side and ignoring its radical wing. Ironically, when cyber-activism does seem to have clear political impact, as in China, this efficacy bias is then turned around to serve the argument that the effectiveness of cyber-activism actually works to stabilize rather than subvert authoritarian rule. Efficacy undoes itself.

      What does an account of the ambiguities of cyber-activism as politics tell us about the nature of cyber-activism? More than anything else, it shows the importance of understanding cyber-activism and its family of words as a set of discourses with political effects of their own, distinct from the effects of cyber-activism as political praxis.  “There was a steady proliferation of discourses concerned with sex,” Foucault wrote, “…an institutional incitement to speak about it, and to do so more and more; a determination on the part of the agencies of power to hear it spoken about, and to cause it to speak through explicit articulation and endlessly accumulated detail” (History of Sexuality, Vol. 1, p. 18) As Foucault wrote of sex, so we can write the same about cyber-activism or the internet. The steady proliferation of discourses concerned with cyber-activism, I have argued, has weakened rather than strengthened it as a political practice. The ambiguities about cyber-activism are elements of a discursive formation that undercuts the power of cyber-activism. Such a discursive formation is, in proper Foucauldian fashion, a formation of power.


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