Fuzzy Bubbles: Coronavirus Apps and Viral Space-Time

 Find the first of our COVID-19 commentaries here. If you feel moved to critique or expand upon either essay, shoot your submissions to vonstillej@gmail.com, and we'll slap it up on the blog posthaste.

This short series of texts will attempt to sketch the relation between human users and coronavirus tracking apps and the hybrid that emerges therefrom. For the sake of maximal clarity, the series will consist of a numbered and lettered list, according to the content index below:

I. A typology of coronavirus tracking apps according to territorial affinity.

II. A typology of such apps according to the extent of state enforcement of their findings.

III. Understanding the function of tracking apps as “fuzzy logic”

a. Tracking apps as a two-threshold operation of fuzzy logic

IV. The temporal conflict between user and app

a. Fuzzification of causality as a result of this conflict

V. Fuzziness of causality as a result of interfacial time

a. Fuzzy, interfacial time as viral time

b. Brief clarification of the term “interface”

VI. Recastings of governance and territory in the context of viral time at different scales

a. Governance as interfacial and doubly hybridized

VII. Construction of viral space-time

VIII. Final image built of the above

I.              Let us assume that coronavirus tracking apps—including but not limited to those recently rolled-out in South Korea, China, and (underdevelopment in) the UK—, which alert users in various ways when they have come into close contact with someone who later tests positive for the virus, fall into one of two types with relation to geography: (1) Bordered trackers, which use only data from within specific territories, and (2) Generalized trackers, which either aggregate data from various territorial datasets without exclusive partnership with any territoriality or utilize data from a worldwide organization like WHO.

II.            Let us assume that these apps do and will also fall into two types with relation to governmental entities: (A) Compulsive trackers, which alert authorities directly when someone is likely to be infected or has tested positive and legally require quarantine thereafter, and (B) Voluntarist trackers, which gather and provide similar information (contact with a positive-tested individual or a positive test of the user) but leave subsequent action up to the app’s user.

III.          In all these cases, we may view the app’s progression of colored states—e.g. green for healthy, yellow for likely infected, and red for a positive test—as an operation in what, in mathematics, is called “fuzzy logic.” As opposed to classical Boolean logic, where each proposition is given a truth value either of 0 (false) or 1 (true), fuzzy logic allows for intermediate states between false and true, presenting a measurement of certainty. The logician may then pick a number between 0 and 1 as a threshold value: Anything above that number is considered true enough to justify a certain action, and anything below that number is not true enough to justify that action. Once a situation has yielded a certainty value between 0 and 1 and that value has been compared to its threshold, that value can be “crispified,” reduced either to a practical 0 or 1 depending on which side of the threshold it falls. Action then depends upon this crispy result.

a.     We can consider the functionality of coronavirus-tracking apps as a two-step (or two-threshold) operation of fuzzy logic: A green status indicates that the certainty value of infection has not passed either threshold, and the app user is likely healthy. A yellow status indicates a passing of the first threshold: The user has likely come into contact with someone who is sick, and so at least the action testing is now justified (or required, depending on policy). A red status indicates a passing of the second threshold and a crispification to 1, so that the action quarantine is justified.

IV.         Of course, perception is not so simple, and neither is the actual process of infection: The app may not register that a user has come into contact with an infected person until that person has actually tested positive, which introduces a fourfold time-lag dependent on the incubation period of the virus, the time it takes after the emergence of symptoms for someone to get tested, the time it takes for the test to register a positive result, and the time it takes for that positive result to enter into the app’s dataset. And so, by the time someone’s app proceeds to a yellow or red status (or, regardless of the app’s construction, to a fuzzy value that can be crispified to 1 to justify some action), they may have been infected for several days a few weeks—let us say, for the sake of subsequent examples, that the average lag is 14 days.

a.     The app then reaches backward through time-dependent data points to alert those who have come into contact with the affected user, effectively rewriting the perceived causal series of those users’ last two weeks. Once the app’s function has entered into users’ conscious experience, they no longer experience linear time, but fuzzy time, in which each action projects onto a series of fuzzy values between 0 (healthy) and 1 (infected).

V.            The fuzzy time that emerges from the intersection of tracking apps’ time-lag with users’ perception of linear causality is a form of interfacial time: The user experiences time as a more or less linear series of causal successions. The app, on the other hand, perceives time as a networked set of 14-day blocks, so that if something happens on day 13 that affects someone who joined the network on day 1, that event on day 13 now redefines that user’s experience from day 1 onward, in addition to the experiences of all those who have come into contact with that user within that time-frame. On the other hand, the app assumes the causality perceived by the user when it determines how the infection will spread. The fuzzy time produced by tracking apps, then, is the result of the interaction of user-perceived time with app-perceived time such that each determines aspects of the other, and both the app and the user must take this interfacial time into account—rather than either version of time on its own—when making decisions.

a.     The fact that a user must join the network before living in this fuzzy, interfacial time (the combination of which shall henceforth be called viral time) means that viral time is embedded: It is neither the time perceived independently by the app, nor the time experienced independently by the user. Rather, it emerges exclusively from the interaction between the two. Both the user and app can be considered prosthetic to the other, in the sense that each interactively defines the other’s method of being in the world. Viral time is embedded because its effective range, in the frames of reference of both app and user, is a subset of the total time experienced by each.

b.    Note that my usage of “interface” and its variations is not short for “user interface” but refers to a two-sided interaction in which neither side is privileged.

VI.         This section refers to the typology introduced in sections I and II, in addition to the notion of viral time developed in III-V: In the case of 1A, state power has begun to operate on viral time. State operation is fundamentally interfacial in the sense that governance is now performed, not by a governmental bureaucracy, but by the interface of that bureaucracy with the app. This is a step toward the posthumanity—or, more accurately, the hybridization of government as implied by Jorge Luis Borges in “A Weary Man’s Utopia” and made explicit in Benjamin Bratton’s concept of the “stack.” Importantly, government no longer operates on a purely human version of time, but on viral time, which is not restricted within a range from beginning to end of the current pandemic, but rather is viral because of its lack of single-species (re)productive mechanism. In the case of 1B, state operation has become fundamentally interfacial as in 1A, but it locates its control mechanism inside the user-app interface (rather than the state-app interface), as described by Gilles Deleuze in his “Postscript on the Societies of Control.” This can, to utilize Peter Sloterdijk’s terms from the Spheres trilogy, be described as a foamification of hybrid governance. By extension, in case 2A, the mechanism of the state—or, more usefully now, the territorial authority—becomes subject to a twofold interfaciality: That between the territorial authority and the app, and that between the various territorial authorities, or between the various territorial authorities and a global operator like the WHO. This implies a third, secondary intersection between different territories’ viral time, dependent upon the time it takes for different medical systems to produce test results and introduce them into the app’s dataset. (This third intersection is operant, of course, in cases 1A and 1B, but it produces a more significant effect when different territories’ medical systems must interact.) The mechanisms of control are also located, in 2A, in this system of 2 (secondarily 3) interfaces. Finally, in 2B, this combination of interfacialities applies at the level of territorial authority (whose boundaries are blurred by that combination), but mechanisms of control are located within the user-app interface, which is now expanded beyond territorial/political borders. And so, once more to utilize Sloterdijk’s terminology, the foamification of hybrid governance reaches toward or, in the case of global data aggregation, achieves planetary diameter.

a.     In all cases, governance (not to be synonymized with government) becomes hybridized as it begins to run on viral time. This means that it is no longer meaningful to speak of human governance but of interfacial governance. After all, the production and distribution of tracking apps is not a simply governmental function: In some cases, territorial authorities (e.g. the UK) have provided funds toward production of such apps or have mandated their use (e.g. China), but private undertakings have determined their availability: Apple, for instance, has mandated that only professional medical organizations may place their coronavirus-related apps in its app store. And so, in this case (and, crucially, in future analogous cases) it makes no sense to speak of governance as state power or as a purely human endeavor, nor to refer to the action of governance as primarily an exercise of humanity. Governance is doubly hybridized as public/private and human/app, and its primary operative temporality is not human but viral.

VII.       The introduction of viral time is accompanied by the introduction of viral space, which emerges from the user-app interface in a process analogous to that which produces viral time. For instance, one app may cross the first threshold in its fuzzy logic (from green to yellow) when a user has passed within 100 meters of someone who later tests positive. As viral time interfacializes the experience of causality, viral space interfacializes the experience of bodily boundaries, moving the user-world border from the skin to a spherical radius of 100 meters. In a viral space so constructed, we may specify the radius of Sloterdijk’s foamy units as 100 meters. Like viral time, this space is not reducible either to human proprioception or the functions of any given app, but emerges from the interface between the two. The interaction between viral time and viral space produces an interfacial viral space-time which forms the four observable dimensions for the app-user hybrid.

VIII.     In the most expanded instance, we therefore have an image of a planetary, spherical foam whose fixed-diameter hybrid bubbles writhe, pass each other, and collide, popping on impact. Each bubble leaves a 14-day trail in its wake which is no less material than the bubble as conceived in the present reference frame of human chronology, producing a non-metaphorical and non-representational hauntology in which the viral past, present, and future may affect each other at precisely the speed of data transmission, without exclusive dependence upon linear time; and in which the barrier of the skin is no longer the primary or operant dividing line between a being and its world.