Smooth Effects: The Erasure of Labour and Production of Police as Experts through Augmented Objects

Michelle Stewart


It’s a cool autumn morning and I am grateful for the sun as it warms the wet concrete. I have been told we will be spending some time outside later, so I am hopeful it will remain sunny. When everyone arrives, we go directly to the principal’s office. Once inside, someone points at the PA system. People pull out their cameras and take a quick photo—we were told the PA system in each school can be different so information about the broadcasting mechanism could be helpful in an emergency. I decide to take a photo as well.

Orange PA

Figure 1: PA system inside the principal's office (Photo by Michelle Stewart)

The principal joins us and we begin the task of moving through the school: a principal, two plain clothes police officers, two uniformed police officers, two police volunteers and an anthropologist researcher. Our goal is to document the entire school for a police program called School Action For Emergencies (SAFE) that seeks to create emergency plans for each school on a national Canadian police database. It is a massive undertaking to collect the data necessary to create the interactive maps of each school. We were told that potential hiding spaces were one focus alongside the general layout of the school; the other focus is thinking about potential response routes and staging for emergency responders.

We snap photos based on our morning training. Broom closets and cubbyholes are now potential hiding spots that must be documented with a photo and narrated with a strategy. Misplaced items present their own challenges. A large gym mattress stored under the stairs. The principal comments that the mattress needs to be returned to the gym; a volunteer crouches down and takes a picture in the event that it remains permanently and creates a potential hiding spot.

Gym Mat

Figure 2: Documenting gym mat in hallway/potential hiding spot (Photo by Michelle Stewart)

We emerge from the school, take a photo of the door, and enter the schoolyard. We move along the fence line: some individuals take notes about the physical characteristics of the property, others jot down the height of the retaining wall, still others take photos of the neighboring properties. Everyone is taking notes, taking photos, or comparing notes and photos.  Soon we will be back at the police station for the larger project of harmonizing all the data into a massive mapping database.

Locating the State in Its Objects

Focusing on a Canadian police program called School Action for Emergency (SAFE), this article discusses the material labour practices required to create a virtual object—an augmented map. This mapping program provides a venue through which to consider the ways augmented objects come into the world. In this article, I discuss the labour practices necessary to create this map and then illustrate how labour practices are erased as part of this production and consumption of an augmented technology meant to facilitate an effective emergency response. In so doing, I will also discuss the production of authority and expertise through deployment of these police aids.

As someone concerned with the ways in which the state instantiates itself into the lives of its subjects, I look at the particular enrollment practices of citizen and state agents as part of statecraft  (Stewart). From Weber we are told about the role of police as they relate to state power, “state is a human community that (successfully) claims the monopoly of the legitimate use of physical force within a given territory. Note that 'territory' is one of the characteristics of the state. Specifically, at the present time, the right to use physical force is ascribed to other institutions or to individuals only to the extent to which the state permits it” (Weber, 34 my emphasis). I would argue that part of this monopoly involves cultivating citizen consent; that the subordination of citizens is equally important to police power as is the state’s permission to act. One way citizen consent is cultivated is through the performance of expertise such that subjects agree to give police power because police appear to be experts. Seen this way, police aids can be critical in cultivating this type of consent through the appearance of police as experts when they appear all knowing; what is often forgotten are the workers and aids that support that appearance (think here of dispatchers and databases).

Becoming SAFE

The SAFE project is an initiative of the Royal Canadian Mounted Police (RCMP), the national police force in Canada. The goal of the program is to “certify” every school in the country, meaning each school will have documentation of the school that has been uploaded into the SAFE computer program. As illustrated in the introduction, this is a time-consuming process requiring not only photos and other data be collected but also all of this data and material be uploaded into the RCMP’s centralized computer program. The desired effect is that each school will have a SAFE program so police and dispatchers can access this massive collection of the data in the event of an emergency.

During my time conducting research with the RCMP, I attended training sessions with John, a young corporal in the national police force. One of John’s duties was to coordinate the certification of the SAFE program that included training sessions. The program was initiated in 2007, and within one year, the province we were working in began the process of certifying approximately 850 of its 1700 schools; it had completed over 170 schools and identified 180 local SAFE coordinators. In that first year alone over 23,000 photos had been uploaded and 2,800 school layouts were available. In short, SAFE was a data heavy, labour-intensive process and one of John’s jobs was to visit police stations to get them started certifying local schools. Certification requires that at least one police officer be involved in the documentation of the school (photos and notes). After all the data is collected it must be articulated into the computer program through prompts that allow for photos and narratives to be uploaded.

In the session described in the introduction, John worked with a group of local police and police auxiliaries (volunteers). The session started with a short Power Point presentation that included information about recent school tragedies, an audio clip from Columbine that detailed the final moments of a victim as she hid from killers, and then a practical, hands-on engagement with the computer software. Prior to leaving for on-site data collection, John had the trainees open the computer program to become familiar with the screens and prompts. He highlighted the program was user-friendly, and that any mistake made could be corrected. He focused on instilling interest before leaving for the school to collect data.

During this on-site visit, as I trailed behind the participants, I was fascinated by one particularly diligent volunteer. He bent, climbed, and stretched to take photos and then made careful notations. Back at the police station he was just as committed to detail when he was paired up with his partner in front of the computer. They poured over their combined notes and photos; making routes and then correcting them; demanding different types of maps to compare their handwritten notes to the apparent errors in the computer map; demanding a street map for one further clarification of the proposed route. His commitment to the process, I started to think, was quite substantial. Because of his commitment, he had to engage in quite a bit of labour.  But it was in this process of refining his data that I started to see the erasure of labour. I want to take some time now to discuss the process of erasure by turning attention to feminist and labour theory emerging from science and technology studies as means to articulate what was, and was not, taking place during the data entry. 

Maria Puig de la Bellacasa highlights the role of care as it relates to labour. In so doing, she joins a literature that draws attention to the ways in which labour is erased through specific social and material practices (see for example works in Gibson-Graham, Resnick and Wolf). More specifically, Puig de la Bellacasa investigates care in labour as it effects what she calls “knowledge politics” (85).  In her work, Puig de la Bellaca discusses Suchman’s research on software design programs that produce virtual “office assistants” to assist the user. Suchman’s work reveals the ways in which this type of “assistant” must be visible enough to assist the user but not visible enough to require recognition. In so doing, Suchman illustrates how these programs replicate the office (and domestic servant) dynamics. Seen this way, labour becomes undervalued (think for example interns, assistants, etc.) and labour that is critical to many offices (and homes). Suchman’s work in this area is helpful when thinking about the role of augmented objects such as the augmented police map because in many ways it is a type of office assistant for police officers, handing over virtual notes and information about a location that police would otherwise not necessarily know thereby replicating the office dynamic of the boss that appears all knowing because, in part, s/he has a team that supports every aspect of their work. This devalued work (the lower paid intern or assistant) facilitates the authority—and ultimately the higher wage of the boss—who appears to earn this status. Let me layer this analysis of the “office assistant” with the similar phenomena in scientific knowledge production.

Steven Shapin, a sociologist of science, discusses Robert Boyle’s 17th century laboratory and the various technicians in the background that assisted in experiments but remained ignored. Shapin argues contemporary scientific practice has changed little in this regard as technicians remain unaccounted for in the scientific record. He points out “science could not be made if this technician’s work were not done, but it is thought that anyone can do it” (Shapin, 557). Without these workers and their labour, scientific knowledge would not be possible, and yet they are ignored and their labour contribution erased (for example not included in formal discussion about the research, or more recently not included as authors in articles). Of course many technicians are/were paid, but nevertheless their role in the experiment erased. One figure emerged as the expert, the scientist, whose work appeared to be solely configured and created.

Programs such as the SAFE project illustrate ways in which the police officer can emerge as an authority figure; but the authority rests on labour practices that move around in the background and go unacknowledged. Much like the lab, there are many ignored figures that produce the necessary objects of police work.  In the case of the SAFE program, the ideal is that a police officer will respond to a call for service and with the click of a computer screen will be immersed in this augmented map. One click reveals data about the PA system, another click offers a full layout of the school, instructions about the design of the exits, notes about potential hiding spots inside, the list goes on. Each click is a product of labourer(s) that compiled the data. But these individuals, much like Boyle’s laboratory technicians, fade into the background and are erased as the police officer emerges as an authority. The map, an augmented object, may be credited with the data it holds, but the data collectors are long forgotten as the police officer stands alone as the subject of authority because of the smooth effects of the augmented map.

Smooth Effects

In an era of big data and data-intensive experiences, augmented objects are increasingly present in our daily lives—with expanded tolerance and appetite. When engaging an augmented object, there is a built-in expectation that the object will "work;" meaning it will run smoothly and effectively. Take Google Maps as an example: one expects the program will run on different scales, offer the capacity to map directions, and perhaps most importantly to be accurate. When these augmented objects run smoothly they appear to be a self-contained and organized object in and of themselves. This paper intervenes on these assumptions to illustrate that this “smooth effect” can serve to erase the labour necessary to produce the effect. Thinking here of the commodity fetish, one can recall Karl Marx’s intervention that illustrated how objects, commodities, permeate our social worlds in such ways that we can see the object—that we only see the object. This concept, commodity fetishism, argues that we erase the labour and social relations involved in the production of the objects, that we forget all that was required to create the object, and we don’t see all that was destroyed in its making.  An example is to think of a cup of coffee. As you sip and consume it, do you think of the commodity chain? Do you think of the worker, the working conditions necessary to plant, harvest, roast and distribute the beans; do you think about the production of the bag the beans were transported in; do you think of the warehouse or coffeehouse from which the bag of beans came from? You more likely think about how it tastes—as an object in and of itself, how it is, rather than how it came into being in the world. Similarly, I want to think about this augmented map and how attention turns to it, not how it came into the world.

Thinking about labour as it relates to computer programs and computer worlds, social scientists have investigated the necessary work of computer programmers and other labourers (see for example Kelty). Tiziana Terranova discusses the immaterial and affective labour that makes online communities thrive as individuals lend their labour (often unpaid) to create an online “world” that appears to organically come together—she argues these online communities are a product of free labour.  Although the police are not working for “free” the volunteers are and the valorization of labour, if erased, still results in the similar outcome.  Terranova is concerned about online communities that don’t simply come into being, but rather are the product of free labour. In the case of the SAFE program, labour practices are rendered invisible when augmented objects appear to be running smoothly —when in fact this appearance of smoothness necessarily requires labour and the commodity being exchanged is the claim to authority.

Figure 3: Cross referencing hardcopy map (Photo by Michelle Stewart)

Figure 4: Using a hand-drawn map to assist data entry (Photo by Michelle Stewart)

Moving in a different direction, but still thinking about labour, I want to turn to the work of Chris Kortright. In his work about agricultural scientists, Kortright carefully details the physical practices associated with growing an experimental crop of sorghum. From the counting and washing of the seeds, to the planting and harvesting of the seeds, he delivers rich ethnographic stories from experimental fields and labs. He closes with the story of one researcher as she enters all the data into the computer to generate one powerpoint. He explains her frustration:

“You can’t see all the time we spent. The nights we slept here. All the seeds and plants. The flooding and time at the greenhouse. All the people and the labour.” I nodded, these things had disappeared. In the table, only numbers existed. (Kortright, 20)

Kortright argues for the need to recognize the social relations carved out in the field that are erased through the process of producing scientific knowledge—the young researcher ultimately knowing her labour did have a place on the slide.

In much the same way, the police and volunteers engaged in a practice of removing themselves from the map. There was not enough space for long sentences explaining the debate about the best route to take; longer sentences were replace with short-phrased instructions. Conjuring the image of the police officer looking for fast, quick information, quick data was what they would deliver. The focus of the program was to place emergency icons (police cars, ambulance, fire engines and helicopters) onto the map, outline response routes, and offer photos as the evidence. Their role as individuals and their labour and creativity (itself a form of labour) was erased as the desired outcome was ease and access to data—a smooth effect. I was often told that many of the police cars don’t yet have a computer inside but in an idealized future world, police cars would be equipped with a computer console. In this world, officers could receive the call for service, access the program and start to move through layers of data rapidly while receiving the details of the call. This officer would arrive informed, and prepared to effectively respond to the emergency.

Thinking back to labour required to create the SAFE map for each school (photographing, mapping, writing instructions, comparing details, etc.) and then the processes of hiding that labour (limited photos and short instructions) so that the program would appear to run smoothly and be user-friendly, the SAFE program, as an object, serves to abstract and erase labour.  Indeed, the desired result was a smooth running program that operated much like Suchman’s office assistant who should be just visible enough to provide the needed help but otherwise remain invisible; similar in many ways to Shapin/Boyle’s scientific technician who is critical to knowledge production and yet remains formally unrecognized.


This article investigated a map as an entry point to understand the ways in which labour can be erased in augmented objects and, concurrently, how authority figures or experts instead emerge. My goal was to discuss the labour necessary to make one augmented map while also describing the process by which the labour necessary for the map was concurrently erased. Central to this article are the ways in which labour is erased as one clicks between these layers of data and, in the process, thinks the smoothly operating computer program is a measure of the strength of program itself, and not the labour required therein. By focusing on this augmented object, I am pointing out the collective labour needed to co-produce the map but how that map then helps to produce the police officer as authority figure. My intention is to look at the map as an unexpected entry point through which to understand how consent and authority is cultivated.

Accordingly, I am concerned with the labour that is erased as this police figure emerges and authority is cultivated on the ground. I focus on the labour that necessarily to produce the police officer as expert because when that labour is erased we are left only with the authority figure that appears to be self-evident—not co-constructed. To understand state practices, as practices and not magical phenomena, we must look for the ways in which the state comes into being through particular practices, such as policing and to identify the necessary labour involved


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Kelty, Chris. Two Bits: The Cultural Significance of Free Software. Durham: Duke University Press, 2008.

Kortright, Chris. “On Labour and Creative Transformations in the Experimental Fields of the Philippines.” East Asian Science, Technology and Society: An International Journal 7.4 (2013). 

Marx, Karl. Capital: A Critique of Political Econony Vol. 1. New York: Penguin Books, 2004.

Puig de la Bellacasa, Maria. “Matters of Care in Technoscience: Assembling Neglected Things.” Social Studies of Science 41.1 (2011): 85-106.

Shapin, Stephen. “The Invisible Technician.” Scientific American 77 (1989): 554-563.

Stewart, Michelle. “The Space between the Steps: Reckoning in an Era of Reconciliation.” Contemporary Justice Review 14.1 (2011): 43-63.

Suchman, Lucy. Human-Machine Reconfigurations. New York: Cambridge University Press, 2007.

Terranova, Tiziana. “Free Labour: Producing Culture for the Digital Economy.” Social Text 63 (2000): 33-58.

Weber, Max. The Vocation Lectures: "Science as a Vocation", "Politics as a Vocation." Indianapolis: Hackett Publishing Company, 2004.


police, Science and Techology Studies; augment; Canada; anthropology; labor

Copyright (c) 2013 Michelle Stewart

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