CHAPTER TWO

REVIEW OF LITERATURE

Media infrastructure studies

Media infrastructure studies

On the most basic level, every material thing on Earth comes from a mixture of finite and renewable resources of the planet itself. Material things rely on resources for both their composition and their function, and this is particularly true of media infrastructures. Historically, media infrastructure studies have beginnings, like much of the Communication field, in Greek and early Roman origins. Beyond lenses of “Greek cultural techniques,” media infrastructure studies really emerged out of periods of war, with Friedrich Kittler and German media theory during World War II launching “the next evolutionary step in media studies” (Peters, 2015, pp. 24-25). In addition to Kittler, scholars like Marshall McLuhan, Harold Innis, Lewis Mumford, Paul Edwards, Leigh Star, Geoffrey Bowker, Bruno Latour, Michel Foucault, and Martin Heidegger, for example, each forwarded the ontological, phenomenological, and epistemological foundations and lenses of studying media as infrastructure (Peters, 2015). The term infrastructure has moved beyond being a military term, with scholarship continuing to acknowledge how media have “something both ecological and existential to say” (Peters, 2015, p. 52). Media infrastructure studies are important because, as Edwards (2003) argued, “to be modern means to live within and by means of infrastructures” (p. 186).

Daily life in the digital age of the 21st century involves various and complex infrastructures. For example, using a cell phone to access the Internet often requires a WiFi network. Beyond this, the undersea cables, the satellites, the routers, wires, data centers, electricity, water, and other finite resources comprising the cell phone, etc. are all part of an infrastructural assemblage. An assemblage is a concept that Grossberg (2010) describes as the result of building relationships between concepts that may “not be readable from its appearance” (p. 53). Using the metaphor of an everchanging group of puzzle pieces or toy blocks, Grossberg (2010) argued that there may be multiple ways various pieces can fit together, and the fit between pieces often depends on “its own contextuality” (p. 53). Taken together, the contextuality or “possibilities of the context” create an assemblage of the concepts at hand (Grossberg, 2010, p. 53). To relate this back to the aforementioned infrastructural assemblage, energy, undersea cables, and data centers are all infrastructural puzzle pieces that fit together in dependent ways; these infrastructures work together to enable Internet functionality. However, while this infrastructural assemblage is important, the various pieces are often hidden, invisible, or unknown. Cables, wires, and warehouses full of server hardware are the essential elements of functioning technologies users rely on are often hidden or camouflaged. Starosielski’ s (2015) research on undersea cables revealed that “many people in the cable industry perceive a general lack of public interest in their infrastructures” (p. 4). Another engineer who Starosielski (2015) interviewed “pressed” her “interest in making cables visible” by asking questions like: “Why would you want to know?” and “When you turn on a computer and you send an email, do you really care how it works?” (p. 5). However, such invisibility leaves little room for activism or decision-making, especially within communities who are directly impacted by the infrastructures (Starosielski, 2015).

The physical makeup of media infrastructures not only facilitates human communication, they communicate something themselves. From an architectural perspective, media infrastructures are often found running along train tracks as old telegraph wires transitioned to electric wires, or as landscape pieces like old television towers are built into iconic skylines in German cities, or as data centers in fields or near small towns in the Carolinas, or as satellites situated in the greenery along mountainsides (Mattern, 2017). Historically, media technologies like televisions entering the home radicalized the design of spaces, like living rooms (Spiegel, 1992). As Communication scholar Rich Ling (2012) has explored, technologies like telephones, automobiles, and cell phones have all relied on processes of making new and ostensibly strange infrastructures appear normal and even banal. For many new communication technologies over the last two centuries, being materially plugged-in to media infrastructures like telephone cables is an important first step, in addition to learning protocols, manners, and etiquette associated with usage (Marvin, 1992). As these technologies became domesticated, questions of how air waves and signals interact with one another did not and does not have to consume users’ minds (Silverstone, 1994).

Scholars like Starosielski (2015) and Cubitt (2017) acknowledge that, with media infrastructure, it is possible to use the tangible devices and not consider the vast infrastructure that makes ordinary use possible until they cease to function properly. For example, it is possible to use a cell phone and never consider the finite materials comprising it that are being excavated at rates that are on the verge of depleting the planet forever (Cubitt, 2017). Similarly, it is possible to use a cell phone and never consider the ramifications of purchasing the latest model of the iPhone every year or two. It is possible to use Google Drive, back up documents, and never consider the ramifications of cloud storage on the environment. It is possible and acceptable to ‘binge-watch’ television shows and movies through streaming services like Netflix. When media infrastructure becomes ordinary, it becomes far less alarming and essentially invisible. Since technology has progressed to a point where WiFi and “cloud storage” are now part of the everyday for users in developed countries, they embody the invisibility of media infrastructure; users may not understand, be aware of, or know about. When users fail to understand the very infrastructure that makes their everyday possible, they therefore miss out on opportunities to advocate for ecologically-smart innovation, sustainable practices, or the awareness that they contribute to the environmental problems associated with finite resources being used up in the production process of the devices they know, love, and use.

To better explain these ideas, it is helpful to consider the related example of the fashion industry. It could be argued that tangible devices are no different from a vast array of other consumer products that stimulate and sustain capitalism in the United States. If one considers the environmental implications of fashion manufacturing and merchandising (Arrington, 2018), the invisibility of the behind-the-scenes process of creating and getting an item to the consumer is very similar to the invisibility of communication infrastructure. Consumers rely on these products, and like communication technologies and the infrastructure it takes to make them function, they are not going anywhere in the foreseeable future and are continuing on their current design of planned obsolescence, part of the ordinariness of each day of consumer demand (Arrington, 2018).

There is a power dynamic to communication infrastructures, in that in the invisibility of the ordinary use is the result of corporate powers who are responsible for the various articulations that together, form an assemblage of ordinariness (Felski, 2000). Consumers who conduct a Google search may not consider how they are using data centers around the globe, how those data center sites have negotiated energy contracts with the local power grid or renewable energy projects within the grid. Rather, conducting a Google search, though it involves all those articulations, is something so ordinary and part of the everyday. Infrastructures are the visible traces of functionalities that may be considered invisible. They matter because without them, the Internet would not exist. Communication infrastructures matter because they are the core, the crux of every form of digital or mediated communication that scholars study and humans use in technologically developed areas. In this regard, infrastructures are also reflexive; to research and understand them, to write about them, authors and users depend on their function (Stokes, 2002). Infrastructures are the extraordinary doing the ordinary.

Conversations surrounding media infrastructure studies also acknowledge that there are historical and current infrastructures which deserve to be studied. In some literatures, infrastructures are typically associated with sidewalks, bridges, or various things that make public transportation or public life possible (De Certeau, 1984). Technological infrastructures are a shift from this line of thinking, in that they deal with similar possibilities in a mediated format. For scholars like John Durham Peters (2015), media studies should involve “infrastructuralism,” ensuring that “the basic, the boring, the mundane, and all the mischievous work done behind the scenes” are highlighted and represented because they make media possible (p. 33). Peters builds off other scholars, including Geoffrey Bowker and Susan Leigh Starr (1999), to assess the way such crucial, often hidden, background operations of media are critical parts of how they serve as “crafters of existence” (p. 15) and the importance of “the call to make environments visible” (p. 38). Such behind-the-scenes operations are thus imperative components of media theory.

#### Data Centers

Broadly, data centers are one of the most important media infrastructures in the current conjuncture (Grossberg, 1992). They are the physical houses of the ethereal Internet cloud, the “physical clouds of cloud computing” (Roach, 2018, para. 14). As Google asserts on their dedicated website, data centers are “where the Internet lives” (Google Data Centers, 2018, para. 1). Data centers are vastly and holistically more complex than a simple abode or dwelling. When a company like Google uses a house metaphor, they are essentially glossing over the processes that enable functionality and instead creating a comparison that users are more inclined to understand. On the earth’s surface and underneath the oceans, data centers are literally physical warehouses situated in communities and regions. These large warehouses are filled with a multitude of technologies working simultaneously to power and cool the servers which they contain. Data centers contain millions of servers which are ultimately the operational center, of the ethereal Internet (Cubitt, 2017). Each server functions as a type of “bulked-up”computer containing the chips that process all the data collected (Glanz, 2012, para. 1). Additionally, other standby and backup servers are always powered in case of malfunction to continuously produce the storage space required to maintain documents, photos, posts, and essentially everything users rely on their Internet to do (Glanz, 2012). Data centers also store media that are accessed through streaming services like Netflix, YouTube, Hulu, and Amazon Prime, while Microsoft heavily relies on them for their vast gaming empire in addition to their Office Suite and SharePoint functionalities.

Establishing what data centers are is simpler when it is done on the physical, material level. Definitions of data centers get even more complex. Data centers contain a multitude of physical structures, like wires, water piping, lights, electricity and servers and beyond these structures are a myriad of other factors. Larkin (2013) asserts the “duality of infrastructures;” infrastructures cannot simply be defined by their physicality and technologies (p. 329). Rather, infrastructures are not the technologies they contain. Instead, data centers are infrastructures in which other infrastructures and technology operate while simultaneously being themselves operated within external systems and infrastructures (Larkin, 2013).

Most broadly, researchers have classified data centers as the current day “factories” (Cook & Van Horn, 2017; Pickren, 2017). Data centers function in a model that reflects elements of agriculture; they are physical locations that require the same finite resources of water and potentially wind or solar power to function, or other nonrenewable energy sources, to produce an outcome of storage. Servers do the work of recording, sorting, organizing, and storing information that consumers want to back-up, are seeking, and creates records of those items. Thus, data servers are part of labor that also relies on natural resources. Understanding data culture through this lens is possible in cultural studies, especially since “Agri-culture was born of a dependency on the natural world and thus of a precarious situation” (Striphas, 2019, p. 7). Data centers, an agricultural component of the Internet, offer a variety of connections between the environment and objective of their existences: to produce, store, and keep data accessible.

Without data centers, Internet usage in developed regions of the world would not be possible. Such Internet access broadly has societal and cultural implications. Scholars like Raymond Williams wrote that “culture is ordinary … every human society has its own shape, its own purposes, its own meanings” and that “every human society expresses these, in institutions, in arts and learning” (1959, pp. 92-93). In much of the 21st century United States, such ordinary cultural expressions are performed through the Internet, which is, in turn, enabled by such crucial infrastructures. However, such mundanity has its costs, especially as often these hidden or taken-for-granted communication technologies and infrastructures can lack accountability for the controlling entities since the public is largely unaware of their existence unless malfunction occurs (Starosielki, 2015; Graham & Thrift, 2007). To understand the reality of data centers and the Internet requires an analysis of its “usually just forgotten infrastructure” (Peters, 2015, p. 38). The operations data centers allow are the direct result of the infrastructure and technologies contained inside of them, and yet, data centers, like undersea cables and hidden wiring, can go unnoticed by users not physically located near them (Starosielki, 2015). Additionally, Internet users are vastly unaware they are even utilizing cloud storage; one survey found that 95 percent of users believed they were not using cloud storage when they were (Holt & Vonderau, 2015). Such gaps in public knowledge and understanding are problematic in numerous ways, such as consumers being unaware of the ecological ramifications of their technology usage, ultimately revealing a gap in public awareness of such seemingly essential technology.

One way to understand the various connections between infrastructures and environments is through a framework of articulation and assemblage described earlier. Articulations have duality. In one use, articulations can be helpful in understanding the relationship to “historical conjuncture” of that which is being analyzed (Slack, 2006). In another use, articulations reveal the “sociocultural conjunctures” that demonstrate what is or is not valued, who are and who are not valued, and where and by who the benefits are received (Slack, 2006). Ultimately, Slack and Wise (2005) argued that the articulations of technologies should be considered “among the physical arrangements of matter…and a range of contingently related practices, representations, experiences, and affects” (p. 128). Articulations are the particular connections between different elements, revealing specific unity – or difference – between them (Slack, 2005). Articulations are the puzzle pieces that can fit together in particular ways of tension (Grossberg, 2010, p. 53).

Thus, by such a definition of data centers, one must go beyond mere materiality to assess the various working articulations of articulations within the ultimate assemblage of communication technologies. Doreen Massey (1993) argued that “what gives a place its specificity is not some long internalized history but the fact that it is constructed out of a particular constellation of relations, articulated together at a particular locus” (p. 67). With data centers, for example, one constellation revolves around electricity that powers the data centers. Electricity is an assemblage of articulations on its own, as the various wires and infrastructure work together to join a larger grid, controlled by corporate interests and situated in different regions, which are also powered by some form of energy source, whether that may be coal, nuclear, or now renewable sources. Another interesting aspect of electricity is its synonym, power, almost as though there is an acknowledgement that those who can harness, create, or experience luminance, have the true power, and those who can afford it or live in developed areas that have access to it also have a smaller power. However, data centers seem to exist in a type of diffuse way, like a rhizome (Deleuze & Guattari, 1987). For data centers specifically, tubes, wires, and infrastructure interact with one another in regions around the globe, though they are now corporately and privately owned. Because data are constantly re-routed through various servers located at different geographies, it can seem impossible to truly identify where specific data is stored, where personal computers have been, and where all the various components leading to functionality are created. Such power relationships are another crucial aspect of media infrastructure studies, as starting analysis on the ground – and in the dirt – often reveals what Innis would describe as “a hidden history of power and conflict” (Young, 2017, p. 235). This thesis explores such power and conflict through the concepts of renewable energy.

Digital media technologies are not sustainable. The various working components of digital media innovation come with a price, both financially and ecologically. As a result, there are also many conversations among researchers about the ecological conditions of technology use since the Internet relies on so many natural resources (Offenhuber, 2017). One conversation involves the of the price of the newest model of the iPhone in a store (i.e., a price tag of $999) and the obsolescence of the technology in the current model (i.e., upgrading a device every few years). Another conversation could juxtapose the price of the iPhone on the price placed on the villages from which the precious minerals required were mined, with the toll on both the physical environment, the mistreatment of the workers and the lack of protective policies in place by the governments in countries involved (Cubitt, 2017). The way that digital media requires perpetual discarding of models of technology to make way for newer, supposedly more innovative ones is not sustainable (LeBel, 2016). Digital media are engineered to be discarded; they only perform for a few years and need to be updated on cyclical (and unsustainable) timelines. The networks that are required for digital media to function are not sustainable. The very ways that media sustain themselves and store information are not sustainable. Herein lies the true irony of messages of green initiatives and publicfacing sustainability missions: they are often commissioned and perpetuated by connecting to the Internet, which is itself not sustainable. It is far easier for consumers to understand sustainability in tangible ways, like carpooling to work to reduce a carbon footprint, eliminating straw usage to save the sea turtles, or to clean up trash in the ocean and beaches. It is much more difficult to discuss sustainability of “the cloud,” especially when very few even understand how cloud computing works or what happens behindthe-scenes to make it possible for the functionalities they rely on to occur. Because of the ethereality of their production and of the ways they work beyond basic commands or connections to WiFi, the ecological ramifications of their existence largely cease to be questioned or understood. The specific irony of not understanding something like data centers is especially striking because they make possible online sustainability messaging, and yet, public scrutiny of the massive energy and water consumption required, let alone the finite minerals and materials needed for the servers, is minimal by comparison.

The ecological issues specifically related to data centers hinge on many assemblages. Energy consumption of data centers is the most notable. As a country in 2017, the United States ranked second highest in total energy consumption at 3,808 terrawatt hours (TWh), trailing behind first ranked China at 5,683 TWh (Enerdata, 2018). In 2012, a yearlong investigation revealed that globally, data centers were consuming nearly 30 billion watts of electricity, or enough energy produced by 30 nuclear power plants (Glanz, 2012). In 2017, it was reported that Alphabet alone ingested “5.7 terawatt-hours of electricity, about as much as the city of San Francisco uses in a year” (Irfran, 2017). Additionally, it is estimated that data centers on their own consume up to 3 percent of the overall national energy consumption, which on surface level may not seem that much, but is truly enormous when one considers 3 percent of 3,808 TWh (Irfran, 2017).

In addition to electricity consumption, one must not overlook another critical aspect of keeping data centers functioning: water. In order to cool and power their infrastructures, data centers guzzle water. In more technical terms, data centers used 626 billion liters of water in 2016 and are anticipated to consume 660 billion liters by 2020 (Keisling, 2016). In 2017, Facebook reported that its data centers used approximately 300,891,967.6 gallons of water (Facebook Sustainability, 2018). In 2015, data centers in California alone were estimated to have used 250,000 gallons per day (Kassner, 2015). While data centers are cooled by around 165,371,703,299 gallons of water, 2.1 billion people lacked access to safe drinking water in 2017 (United Nations, 2018). Additionally, sometimes water infrastructures involved with corporations fail the humans in the regions they operate in, as evidenced by the current water crisis in Flint, Michigan. In April 2014, the heavy metals of chemical additives from the industry-used water in the Flint River corroded plumbing infrastructure, resulting in widespread lead poisoning and heavy metal leaching, severely and damagingly impacting the locals living in Flint (Anand, Gupta, & Appel, 2018). Therefore, in addition to massive need or inaccessibility to water, the regional water supply can be negatively impacted by industry and infrastructure can fail.

Technology companies have separate websites or blogs dedicated to their data centers that populate search engine results rather than being located on their main company pages. Additionally, companies are reactive rather than proactive about their “sustainability” of data centers. By their design, data centers are wasteful. The servers in data centers performing actual computations were reported in 2012 as only 6-12 percent of the energy users in data centers; this means that nearly 90 percent of the energy used by servers in data centers is not even being used for functions other than idling in case of surges that could impact the servers in use (Glanz, 2012).

Renewable Energy

Renewable Energy involves resources that natural lifeforms inhabiting the earth also require. Panels that use sunlight are modeled after the photosynthesis process in the plants that inhabit the same fields as the solar panels themselves. The end goal of renewable energy is to reduce overall emission totals, in turn helping to limit pollution that is associated with climate change (Wilberforce et. al, 2019). Renewable energy is considered more environmentally friendly because it involves technologies designed to convert the naturally occurring energy as part of the ecosystem to power and produce the energy that is necessary to power other technologies and infrastructures. The newer emerging sources of renewable energy include “marine energy, artificial photosynthesis, cellulosic ethanol, concentrated solar power,” and “enhanced geothermal energy” (Wilberforce et. al, 2019, p. 852). Various solar panel fields are likened to an animal or agricultural farm, even down to the official verbiage used to describe them: solar farms, “concentrating solar power plants,” or fields of “photovoltaic technologies” (Solar Energy Industries Association, 2018, pp. 1-2).

Technology companies are investing in renewable energy because they are becoming more aware of their ecological ramifications and ‘footprints.’ Though companies, especially Facebook, disclose many overall facts and figures for their data centers on their public-facing websites, they still leave things out. Facebook, Microsoft, and Amazon Web Services all publicize various levels of their plans or initiatives regarding renewable energy. Most notably, in an October 2018 blog post, Michael Terrell, Google’s Head of Energy Market Development, reported that Google had become the “world’s largest corporate buyer of renewable energy” and they matched “100 percent of annual energy consumption with renewable energy purchases” in 2017 (Terrell, 2018, para. 3). On their website and all their public-facing materials, Google appears absolutely committed to the overall sustainability mission of the importance of renewable energy. Renewable energy can be described by companies in terms of “matching” versus “converting.” However, it is also important to understand that difference. Both of these concepts will be examined in further sections of this thesis as they relate to Google specifically. Technology companies, like Google, are discursively situating themselves with renewable energy, especially with renewable energy acquisitions.

“Buying” renewable energy

Energy regulations at the state and national level vary, meaning that depending on the locations or regions different companies and their infrastructures are located, they may have different requirements on how they handle their energy consumption. As such, energy is often one of the upwards of 50 different factors for Facebook and around 43 factors for companies like Microsoft when considering where to build their data centers (Fehrenbacher, 2012). North Carolina is one of the bigger hubs for data centers, with Google owning one in both of the Carolinas, because it includes access to reliable power at a low cost, enough rural areas to prevent outcries from populated areas who do not want to intersect, state tax incentives and tax breaks, water access, quick startup timeframes, non-problematic traffic and airport access, and a climate that promotes openair cooling versus reliance on water all year (Fehrenbacher, 2015). Once a big company decides to build a data center in a certain region it is not uncommon for other companies to follow-suit; pitching a new location idea is much easier if a competitor has already successfully built and began operating (Fehrenbacher, 2015). All these factors, especially energy for the focus of this project, are important because, just as Google states, it is helpful to understand where users’ “computers have already been” and “what keeps the Internet up and running” (Google Data Centers, 2018, para. 6).

On their website and all their public-facing materials, Google appears absolutely committed to the overall sustainability mission of the importance of renewable energy. In 2017, however, it was reported that Google began buying renewable energy credits that matched their energy consumption rates, meaning they invested in renewable energy sources that match the energy while not directly powering their technology with it (Irfan, 2017). Over a decade ago, economics journals featured publications describing the process of how a company could “meet its [energy] portfolio standard requirement” (Berry, 2002). There are, according to this literature, three options for utility or retail loads that can ensure the requirement is met: (1) a company can generate their kWh from the eligible resources and then sell those exact kWh at its retail price to its customers, (2) a company can purchase kWh from another party that already generated them from the eligible resources, transmitting or converting those kWh for delivery to the company’s distribution system, or (3) a company can purchase the tradable credits that come from generation of the eligible resources from the owner of the credits without actually needing to transmit the associated energy to the company, a type of matching process (Berry, 2002). In short, companies can generate their own renewable energy, or they can purchase and convert renewable energy from elsewhere, and lastly, they could simply own the tradable renewable energy without converting their consumption. In the last option, companies are still producing energy from fossil fuels or non-renewable sources. In the following discourse analysis, this thesis analyzes what Google’s amassing of renewable energy purchases means to them in how they disclose information about “matching” as opposed to directly converting to sources on site for renewable energy.

However, in 2012, Greenpeace — an independently funded and operated international organization focused on saving the planet — found that, while Microsoft adopted their internal carbon tax, they were buying “renewable energy credits (RECs) and carbon offsets” (Pomerantz, 2012). Microsoft was still relying on energy produced by coal while purchasing these credits to pay other companies who are making renewable energy without truly converting or powering their data centers with renewable energy (Pomerantz, 2012). In turn, despite their bold claims of clean energy conversion, they were not producing or using clean energy after all. Rather, it appears they opted for the third option of Renewable Energy Credits to meet their energy consumption portfolio (Berry, 2002). Google, like Microsoft, currently uses the “matching” verbiage, indicating they too are participating in the third option of Renewable Energy Credits. For publics who are unaware of what this means, it can be incredibly misleading to believe companies are attempting to convert their energy consumption. The analysis section of this thesis reveals arguments about how Google positions themselves, how they describe their role in renewable energy, and the corporate value claims they seek to make for consumers.

Stakes of research

Just as media infrastructures are often embedded in locations out of public attention or view, the environmental ramifications of technological infrastructure like data centers can go unnoticed. Government reports and agencies and news headlines are filled with warnings about an imminent climate catastrophe that is quickly approaching unless rapid and immense countermeasures are taken. However, advocating for corporate responsibility, especially in the technology area, seems unlikely when relatively few people are aware of the immense amounts of finite resources necessary for and consumed by technologies and infrastructures. Researchers, especially in Communication, should care about the environmental impact of data centers because they often partner with advocates; having conversations in both academia and the public are crucial. Researchers should care about the environmental impact of data centers because they communicate a larger issue themselves; their lack of perceived visibility and knowledge creates limits on the public’s consideration or opportunities for political engagement (Starosielski, 2015). As Starosielski (2015) asserts, the insular complexities of communication media infrastructures are more often interlaced with a “privatized and competitive environment that values reliability” rather than “a product of national interests” (p. 92).

Likewise, capitalist economies are interested in creating revenue. In order to power such an economy, technology must meet the demands and innovation needed to drive growth. Data centers, a crucial infrastructure of a global economy, are the sustaining force while they themselves are not sustainable. Data centers have ecological ramifications and repercussions. When corporations fail to act responsibly with resources they are dependent upon in local communities, there are often dangerous ramifications. In his 2013 book, Tom’s River, author Dan Fagin wrote about Tom’s River in New Jersey, carefully telling the story of a chemical plant operating on the river (Fagin, 2013). The chemical plant caused a public health crisis after polluting the waters that the community depended on, with reports of it initially being “easier for managers to ignore or at least downplay signs that the factory was polluting groundwater and the river”(Fagin, 2013, p. 49). Over time, government and regulatory standards even allowed for harmful negligence in this case example, also reinforcing the notion that infrastructure and corporations are articulated to resources, public policy, and power. Earlier examples of the fashion industry, Flint, Michigan crisis, and Tom’s River remind us that corporations rely on infrastructure, and infrastructure is inextricably reliant on material resources. These are complex relationships.

Data centers encapsulate the “surface manifestation of a deep structure of materials and their movements,” and it would be incredibly impoverishing to only consider the tangible or geological layers which data centers comprise (Acland, 2014, p. 9). This research builds on current conversations surrounding data centers in media, technology, and cultural studies. Data centers impact the sustainment of the technology culture, the social media platforms and anything scholars study that involves the Internet. As this thesis began, the ongoing climate crisis requires corporate action towards sustainability. In addition, as this thesis argues, the ongoing climate crisis could be capitalized on by corporations like Google as they mask retroactivity as activism.