The return of time

It is by now a cliché to say that technological development and its digital culture are endlessly accelerating. Superficial as this may seem, there is much at stake, both philosophically and materially, in the rise of what Ernst and Parikka (2013) call ‘time- criticality.’ Time is critical, for instance, for a worker in an Amazon distribution centre, as a recent plethora of stories documenting working conditions inside such centres teach us. These conditions stretch the principles of Taylor and Gilbreth’s

Time-Motion studies almost to (human) breaking point. One of the more memorable stories to document the working conditions inside a distribution centre is by

journalist Mac McClelland (2012), and is worth quoting at length.

The place is immense. Cold, cavernous. Silent, despite thousands of people quietly doing their picking, or standing along the conveyors quietly packing or box-taping, nothing noisy but the occasional whir of a passing forklift. My scanner tells me in what exact section—there are nine merchandise sections, so sprawling that there's a map attached to my ID badge—of vast shelving systems the item I'm supposed to find resides. It also tells me how many seconds it thinks I should take to get there. Dallas sector, section yellow, row H34, bin 22, level D: wearable blanket. Battery-operated flour sifter. Twenty seconds. I count how many steps it takes me to speed-walk to my destination: 20. At 5-foot-9, I've got a decently long stride, and I only cover the 20 steps and locate the exact shelving unit in the allotted time if I don't hesitate for one second or get lost or take a drink of water before heading in the right direction as fast as I can walk or even occasionally jog … Often as not, I miss my time target … Plenty of things can hurt my goals. The programs for our scanners are designed with the

assumption that we disposable employees don't know what we're doing. Find a Rob Zombie Voodoo Doll in the blue section of the Rockies sector in the third bin of the A-level in row Z42, my scanner tells me. But if I punch into my scanner that it's not there, I have to prove it by scanning every single other item in the bin, though I swear on my life there's no Rob Zombie Voodoo Doll in this pile of 30

individually wrapped and bar-coded batteries that take me quite a while to beep one by one. It could be five minutes before I can move on to, and make it to, and find, my next item. That lapse is supposed to be mere seconds.

Her story is littered with references to time beyond the algorithmically generated time targets coded into her scanner. McClelland’s experience supports Rossiter’s claim that “[l]ogistics robs living labour of time” (2014, p. 67) and in so doing subjects life to new forms of self-regulation, what Foucault (1990; 2007) defined as biopower. Amazon-like distribution centres are petri dishes of time-criticality, a product of the logistical worldview’s dream of pure rationality and efficiency: Bestand in motion, 24/7. Jonathan Crary takes ‘24/7’ seriously, moving the term beyond cliché by elaborating it as a critical concept that can describe the contours of a society that has become recalibrated around nonhuman, machinic time.

“24/7 is a static redundancy that disavows its relation to the rhythmic and periodic textures of human life … It is only recently that the

elaboration, the modeling of one’s personal and social identity, has been reorganized to conform to the uninterrupted operation of markets, information networks, and other systems” (2013, p. 9).

Lists abound in the logistical world of 24/7, giving form to everything from instructions, schedules, and standard operating procedures to warehouse pickers’ daily lists of targets and the algorithms that produce them. Such computational protocols, processes, and mechanisms enframe contemporary logistical operations everywhere, not just in Amazon-like distribution centres. Rossiter shows how the movement of workers in warehouse and transport industries is “increasingly regulated by global positioning system (GPS) vehicle tracking, radio-frequency identification tags that profile workers within database time and voice-directed order picking technologies ‘that manage the passage and pace of workers through the workplace with the aim of maximising efficiencies’” (Rossiter 2014, p. 68). And, as should be evident, the effects of these changes are not exclusive to production or labour. “The rhythms of technological consumption are inseparable from the requirement of continual self-administration” (Crary 2013, p. 46).

For Rossiter, “code is King” (2014, p. 68) in logistical modernity, and “whoever sets the standard rules the world” (p. 65). These claims do not delve deeply enough; code and standards are only effective tools of logistical

governmentality because they have the capacity to capture, manipulate, and

program time. For instance, database ‘contents’ (for lack of a better term) materialize on our screens dozens of times each day, re-presenting digital data sets and code in a format recognizable to human senses, such as a Google search results list. What is on the screen is a product of data that has been run through an algorithm and

rendered for display on an interface. In such a format, the data appear as spatial ‘things.’ Data are organized on a screen as we might spatially organize written material on a page. Historically such formats have structured experiential and conceptual space, as we saw in chapter three. However, when we focus solely on screens—a tendency Kirschenbaum (2008) describes as ‘screen essentialism’—we mistake as spatial abstractions the operations of computational databases that are actually about time. The popular press has often cast Google or Wikipedia as

actualizations of Borges’ library of Babel, emergent archives of ‘all the world’s

knowledge.’ Such comparisons conjure images of vast archives wherein contents are stored as extant individual items (or coherent sets of 1s and 0s) at the ready to be summoned, as a book on a shelf in a library. Such understandings, which cast databases as a digital equivalent of a physical archive, miss the fact that any data ‘contained’ by database are summoned, called forth, materialized, and made to function in an essentially temporal operation (Ernst 2013; Parikka 2011;

Kirschenbaum 2008). Data points in a database are ontologically distinct from physical objects such as files in an archive or a name written on paper. They do not sit on shelves waiting to be pulled out and opened. Their physical reality is

detectable only at the micro-level of inscriptions made on silicon chips

(Kirschenbaum 2008). Our language to describe computational databases is infused with metaphors that reference the world of analog technology, but these metaphors paper over the fact that the ‘data’ of databases are sequences of code that

materialize and de-materialize in real time as required by a programmer or, increasingly an algorithm.

The mining, measure, and analysis of Big Data is different from earlier, analog administrative contexts in that Big Data is essentially about real time, the creation of databases—archives—that do not simply exist in space (on server racks), but are constantly made and remade according to the ever-accelerating feedback loop of input/output. The form that structures this feedback loop is very often the list—not only as input/output format, but also as code. The difference from earlier

administrative and logistical milieux is that control of the archive is no longer about physical space but rather operational time. Put rather crudely, the database that programs time has replaced the register that inventories space as the paradigmatic form of logistical modernity. With such new problematics and objects of analysis— algorithms, databases, digital footprints, informational persons, and so on—there is need for new tools that can parse the time-critical dimensions of digital culture.