The Waiting Room: Rethinking Latency after COVID-19

Building on the recent literature on waiting and “temporal inequality,” this essay studies three categories of latency laid bare by the coronavirus pandemic: photogenic, infrastructural, and emotional. This triad analysis dismantles the myth that on-demand culture enables seamless, global access to information and that therefore our lives could be easily moved online. Pushing against this technological solutionism, it posits the waiting room as a timely metaphor for corona-capitalism.

Absolute power is the power to place other people in total uncertainty by offering no scope to their capacity to predict… The all-powerful is he who does not wait but who makes others wait.
Pierre Bourdieu

Zoom’s “waiting room”—where users patiently wait to join a meeting or a webinar—is a perfect metaphor for corona-capitalism. We anxiously wait for a job interview in a time of crippling recession; for an elementary school teacher with no formal training in remote teaching to babysit our child; for a video conversation with our elderly parents who we might kill IRL. We are confronted with an uncanny degree of self-awareness as we stare at ourselves through our webcams. Desperately trying to direct the mise-en-scene, we rearrange books on the shelf behind us to make our bedroom-turned-office look more professional.

The coronavirus pandemic transformed Zoom—a video conferencing platform established in 2011 and initially marketed to global businesses—into a heaven-sent solution for quarantine anxiety. This “Zoomtopia,” to use company parlance, ignores the limitations of the digital infrastructure, the ubiquity of internet trolls, and the unexpected disruptions that pop into the frame in the form of pets, children, or partners. The company’s ability to provide seamless video is now doubtful as an exponential influx of users encounter buffering issues, frozen screens, and any other digital noise once mocked by Zoom in its commercial from 2015.[1] While Zoom has promoted a discourse of seamlessness, it is latency and waiting that have come to define our pandemic lives.

Building on my previous work on buffering as producing and sustaining “perpetual anxiety”—the oft-denied realization that we increasingly rely on machines and infrastructures whose logic is not clear or accessible to us (Alexander 2017)—I wish to explore three categories of buffering laid bare during the pandemic: pathogenic, infrastructural, and emotional. Informed by the recent interest in the history and regimes of waiting as an antidote to business models that hail speed and instant gratification (Tawil-Souri 2017; Farman 2018; Janeja and Bandak 2018), this triad analysis demonstrates why the study of latency regains a new urgency in a post-COVID world.

The Buffering Pathogen

Buffering, as I argued elsewhere, is a digital specter: it is a moment of lag and disconnect whose length is unknown (Alexander 2017). As such, it opens up a liminal space of activity and passivity, where users are unsure how to react. Since digital technology is based on black box design, proprietary algorithms, and opaque infrastructure, internet users tend to blame themselves for any encounter with technical friction. In the case of buffering, this can take the form of frantically restarting the router, shouting at your flatmate to stop “stealing bandwidth,” or upgrading your device or data package.

The ways in which the unknown length of the encounter produces anxiety and helplessness, alongside the tendency to recast structural failure as a personal failure, make buffering a productive metaphor for the study of the coronavirus, the pathogen causing COVID-19. This pathogen is not only contagious and hard to detect, it also manifests itself differently in every human body: asymptomatic patients might never know they contracted the virus, while “long haulers” suffer from a wide range of debilitating symptoms for weeks or even months (Yong 2020).

Reporting on the differences between SARS and the new coronavirus, The New York Times explains that, “SARS Classic settled quickly into human lung cells, causing a person to cough but also announcing its presence. In contrast, its successor tends to colonize first the nose and throat, sometimes causing few initial symptoms… The virus replicates quietly, and quietly spreads” (Burdick 2020). Combined with the relatively high percentage of asymptomatic carriers, this pattern enabled the global spread of the coronavirus.

This pathogenic buffering—an inherent delay between exposure and traceable symptoms—turned public health policy into a frustrating, costly game of waiting: “sheltering in place” or strictly imposed lockdowns can only show results after two or three weeks; “super-spreaders” could only be detected a week or so after the initial encounter. In the US, the UK, and many other countries, this pattern of delay was worsened by a belated response to the outbreak. Despite early warning from China, where the pandemic first broke, the Trump administration failed to order and manufacture ventilators, protective gear, or testing kits.

The pandemic necessitates waiting: for new guidelines, for testing, for “reopening.” Much like buffering, whose ubiquity and unknown length are being denied by using graphic tools like a colorful spinning wheel, the deadliness of the virus was quickly reframed as data visualizations. These “flattening the curve” graphics played a crucial role in convincing millions to stay at home. Anxiety inducing as they may be, they also allay our fear by transforming uncertainty into two familiar narratives: linear progression from “bad” to “good,” and a three-act structure consisting of outbreak, peak, and decline.

We thus anticipate and deploy traditional narrative structures whereas the pandemic’s progress has a different, prolonged structure. The virus (at least in the early stages) was seen as a sudden, unexplained break from reality, forcing millions to ask when can they finally “return to normal.” It was quickly recast as a digression, a once-in-a-century event that, once resolved, will leave no trace. Flocking to streaming services, millions were re-watching Hollywood pandemic films such as 12 Monkeys (1995) or Contagion (2011). In lieu of happy endings, viewers found solace in these familiar detective stories, where the protagonists expose the chain of events leading to the deadly outbreaks. When uncertainty reigns, causality is an antidote.

Both on-demand culture and data visualization helped belittle the ongoing, devastating toll of COVID-19. New quarantine-based podcasts, columns, and lifestyle sections sprouted tips for gardening, sourdough bread baking, home schooling, or exercising (“your books could be your yoga blocks!” announces a suspiciously joyful instructor in a fitness app).

Waiting, however, is never equally dispersed. In her study of “temporal inequality,” Helga Tawil-Souri (2017) alerts us to the ways in which waiting under conditions of uncertainty can invoke anxiety, depression, and a paralyzing notion of precarity—the kind of emotional states needed to support existing systems of power and prevent acts of resistance. This uncertainty, which buffering and COVID-19 have in common, replaces political rage with a constant state of alertness. If we’re unsure when a technology, or a human body, might collapse, we must protect ourselves by endlessly upgrading both. A more expensive data package, a daily capsule of vitamin C—we are eager to solve problems caused by a series of structural failures by changing our own behavior.

Infrastructural Latency

We might think about the anxiety-inducing pandemic time as the antithesis of on-demand culture and its allure of instant gratification. But my goal is to show that there is more in common between these temporalities than we might imagine.

While we were asked to divide the world into “home” and “non-home,” creating “isolation bubbles” and recasting the public sphere as potentially deadly, our tech-driven society has increasingly shifted online. The demand for remote work ignores the struggle of those who either have fallen sick or had to care for their loved ones. It also downplays the extent of the digital divide: limited access to high-speed internet; lack of digital literacy; and inability to pay for data packages or premium services, to name but few examples.

Much like it exposed the fragility of the American health system, the coronavirus has put the idea of seamless internet to the test. In March 2020, the European Union Commissioner Thierry Breton requested that streaming platforms change their default setting to “standard definition” in order to trim bitrates. In response, both YouTube and Netflix announced that they would automatically adjust their systems to use less network capacity by switching from high definition to standard definition.[2]

Outsourcing this responsibility to tech conglomerates, however, was not sufficient. In the US, rural towns suffered from lack of broadband that, amid the spread of the virus, limited their ability to remain informed. Even tech workers in urban centers experienced more buffering: “As people have hunkered down to contain the spread of the coronavirus, average internet speeds all over the world have slowed. Some broadband providers are feeling crushed by the heavy traffic. And dated internet equipment can create a bottleneck for our speeds,” reported The New York Times (Chen 2020). With the shift to telehealth services, buffering and disconnections exacerbate feelings of isolation and, worse still, might delay medical treatment when patients are unable to effectively communicate with their remote providers.

Even with access to high-speed internet, the fantasy of online life denies the extent to which the digital ecosystem relies on Big Tech and its five mammoths: Apple, Google, Amazon, Facebook, and Microsoft. While I cannot provide an analysis of net neutrality in such a short essay, it is crucial to remember that all of these companies monetize slowness in a plethora of ways by asking their designers to incorporate waiting into their gadgets and applications. As Jason Farman (2018) demonstrates, “false latency” is a prevalent business model used by tech companies to establish trust or maximize profits. This commodification of waiting is part of, for example, Apple’s annual launch of the latest version of its iPhone, or Facebook’s decision to slow down a “security check” feature to convince users that it is thorough and therefore trustworthy. False latency is therefore a feature, rather than a bug, of the digital infrastructure.

Emotional Buffering

Pathogenic and infrastructural latency laid the ground for emotional buffering. While essential workers such as nurses and doctors suffered from burnout, those working from home encountered “zoom fatigue.” In an interview with BBC, Gianpiero Petriglieri explained that being on a video call requires more focus than a face-to-face chat: “Video chats mean we need to work harder to process non-verbal cues like facial expressions, the tone and pitch of the voice, and body language; paying more attention to these consumes a lot of energy. Our minds are together when our bodies feel we’re not. That dissonance, which causes people to have conflicting feelings, is exhausting.” (Jiang 2020).

Technical desynchronization between video and audio breeds a deeper sense of psychological and cognitive desynchronization. While the world became unprecedentedly synchronized—fighting a similar health crisis with a limited set of tools—class and racial disparities created entirely different realities for those asked to shelter in place or report to their “essential work” (while others escaped to their vacation houses).

Zoom fatigue might be mitigated by taking breaks, limiting our screen time, and switching to phone conversations. These tips, however, ignore the other manifestations of emotional buffering during the lockdown. First, it took days, weeks, or months to come to terms with the severity and scale of the global crisis. China detected its first COVID-19 case in December 2019. Yet, Americans were shocked to discover they were asked to “shelter in place” once the virus hit the coasts in early March. Second, natural processes of grieving and healing have been put on hold as a result of travel bans and social distancing. While thousands died in isolation units, funerals and memorials were either postponed or took place on zoom. Third, the frustration and rage induced by delay in testing and ventilator manufacturing in the US and the racial disparities shaping the toll of the virus in different communities were mostly denied by its administration (and, eventually, fed the Black Lives Matter protests that erupted across the world).

These different forms of buffering birthed a reality in which white-collar workers cannot idly wait for improvement (or vaccine); instead, they were asked to remain on their toes, ready to spring into action once a colleague appears on Zoom’s screen or the economy can “reopen.” This perpetual waiting room requires workers or workers-to-be to become not only alert but evermore “flexible,” as became clear once colleges started preaching to their faculty about the need for “hybrid teaching.”

Much like a patient awaiting a doctor, corona-capitalism has forced us to maintain a high level of alert for an unknown length of time. If, and when, we fail, this structural failure will be quickly recast as a personal one. To resist this, we must study how the nascent “pandemic time” shapes our ability to grieve amidst the aftershocks of the coronavirus. The pathogen itself presents us with the challenge of a gap between exposure and sickness, yet it is also crucial to understand the infrastructural and emotional latencies it exposes.

References

Alexander, Neta. 2017. “Rage against the Machine: Buffering, Noise, and Perpetual Anxiety in the Age of Connected Viewing.” Cinema Journal 56: 1–24.

Bannerman, Natalie. 2020. “Netflix and YouTube downgrade due to COVID-19.” Capacity. March 20. Accessed June 15, 2020. https://www.capacitymedia.com/Articles/3825139/netflix-and-youtube-downgrade-due-to-covid-19

Bourdieu, Pierre. 2000. Pascalian Meditations, translated by Richard Nice. Stanford: Stanford University Press.

Burdick, Alan, 2020. “Monster or Machine? A Profile of the Coronavirus at 6 Months.” The New York Times, June 2. Accessed June 10, 2020. https://nyti.ms/2zWusqV

Chen, Brian X.  2020. “Everything You Need to Know About Slow Internet Speeds.” The New York Times, May 20. Accessed June 10, 2020. https://nyti.ms/3fPcDZZ

Farman, Jason. 2018. Delayed Response: The Art of Waiting from the Ancient to the Instant World. New Haven: Yale University Press.

Janeja, Manpreet K., and Bandak, Andreas., eds. 2018. Ethnographies of Waiting. New York: Bloomsbury Publishing.

Jiang, Manyu. 2020. “The Reason Zoom Calls Drain your Energy.” BBC, April 22. https://‌‌www.bbc.com/worklife/article/20200421-why-zoom-video-chats-are-so-exhausting

Tawil-Souri, Helga. 2017. “Checkpoint Time,” Qui Parle: Critical Humanities and Social Sciences 26, no. 2: 388-422.

Yong, Ed. 2020. “COVID-19 Can Last for Several Months,” June 4. The Atlantic: https://www.theatlantic.com/health/archive/2020/06/covid-19-coronavirus-longterm-symptoms-months/612679/

Notes

^[1] Available on YouTube, the commercial tellingly features a conference meeting of four suited executives and one woman, all of whom are white, as they encounter a series of technological glitches while trying to use non-Zoom video services. See https://www.youtube.com/watch?time_continue=1&v=JMOOG7rWTPg&feature=emb_logo

^[2] In March 2020, Netflix issued a statement saying: “Following the discussions between commissioner Thierry Breton and Reed Hastings—and given the extraordinary challenges raised by the coronavirus—Netflix has decided to begin reducing bit rates across all our streams in Europe for 30 days. We estimate that this will reduce Netflix traffic on European networks by around 25% while also ensuring a good quality service for our members.” (Bannerman 2020).