London; oligoptic and panspectric

Posted on May 12, 2008 by Karl Palmås

The oligopticon vs. the panspectron: Notes from two London sites, featuring two different modes of organisation and surveillance.

Victoria Embankment Gardens, 2008:05:09@16:09:03GMT: The oligopticon

If you ever pass by Embankment tube station and have a moment to spare – have a seat on either of these benches, look beyond the trees and general greenery, and you’ll see The Shell Centre.

Situated on the South Bank, the building (according to the plaque in the lobby) was built to host “the central offices in London of the Royal Dutch/Shell group of companies”. The building is thus a veritable command central for the monitoring and control of a vast enterprise, whose operations are dispersed across a wide geographical area.

Bruno Latour has called such command centres oligoptica: The Shell Building is not a panopticon, it does not see “everything” in all the Shell subsidiaries, scattred across the world. The command centre only sees selected elements of the world, monitoring operations along the lines of certain metrics, using certain technologies. Thus, the oligopticon “sees little, but what it does see, it sees well” (Latour and Hermant, Paris ville invisible, 1998, p. 48)

Through mediation of technology (contraptions for measurements, as well as communication technologies), oligoptica are tools for the enacting of action-at-a-distance. Large corporations are thus dependent on oligoptic contraptions - indeed, the rise of the multi-divisional, modern corporation (as charted by Chandler) presupposed oligoptic monitoring. The “vertical integration” of business enterprises, the integration of ever larger chunks of the production process in one single hierarchy could only take place once more effective oligoptic techniques had been introduced in the nascent large-scale corporations. Hence the propensity for corporations to build “war rooms”, as well as all kinds of computerised systems to monitor international sales, offshored manufacturing operations, etc.

In order to compare the logic of the oligopticon with that of the panspectron, we’ll have to experience another London site - the airport.

Heathrow T5, 2008:05:10@13:09:14GMT: The panspectron

If you pass the security controls at the new terminal, take a right and walk along for 20 metres or so, you’ll pass the customs office. Here, you can enrol in the IRIS scheme.

IRIS (a recursive acronym - Iris Recognition Immigration System) lets you scan your irises, in exchange for a quick passage through immigration. The biometric data (your unique iris image) will be stored by Home Office Border & Immigration Agency (in encrypted format), making it easier and quicker for the agency to determine your identity next time you enter the country.

The storing of biometric data is a touchy issue, and obviously the Home Office is treading lightly. In the “Information for Passengers” leaflet, they state that the agency “will only use this information to operate the scheme, for management, statistical and other immigration purposes”. Moreover, the agency will “NOT disclose iris image and iris codes” to external bodies. The agency may, however, disclose other information “to other governmental departments and agencies for official reasons”.

Given that none of the biometric information will be shared - and that the database is not lost by civil servants - this seemingly nasty piece of technology is merely a means to striate space a tad more efficiently. (The passport system is a bit more leaky.) Thus, the IRIS scheme does not represent a qualitative change in abstract machine of ordering, as compared to the use of passports. (Nevertheless, as this technology does spread into more civil use, it will yield new forms of modulated data.)

However, the fancy biometric technology often causes us to neglect other surveillance techniques currently being introduced - techniques that break with earlier approaches of generating order. Even prior to the security check, you may have become subject to panspectic means of organisation. Nevermind Big Brother - panspectrocism works in more subtle ways.

Ever been upgraded to business class? Did you enjoy the free lunch? Chances are that the lunch is not free. Literally. The statistics are against you, because you don’t have the data.

In Super Crunchers: How everything can be predicted, Ian Ayres writes:

The advent of tera mining means that the era of the free lunch is over. [...] In this brave new world, you should be scared when a firm like Harrah’s [a casino chain] or Continental [Airlines] becomes particularly solicitous of your business. It probably means that you have been paying too much. Airlines are learning to give updates and other favourable treatment to the customers that make them the most money, not just the ones that fly the most. Airlines can then “encourage people to become more profitable” (31-32)

How does this work? Well, the twin processes of intensified universal modulation and ever-more effective data mining are allowing companies to control markets in new ways: Instead of being generous to loyal customers, they can shift their attention to the potentially illoyal customers. Data mining not only enables them to single out customers who are statistically profitable; it helps them calculate the exact minimum level of getting consumers to stay loyal. Panspectrocist business practices thus involves

a new science of extraction. Data mining increases firms’ ability to charge individualised prices that predict our individualised pain points. If your walk-away price is higher than mine, tera mining will lead firms to take a bigger chunk out of you one way or another. In a Super Crunching world, consumers can’t afford to be asleep at the wheel. (32)

Indeed – new power imbalances between consumers and producers are emerging. Consumers only see their own molecular actions, producers have access to the aggregate flows of consumer desires. The business in question knows the customers better than the customers know themselves. As in the case of Harrah’s – the casino knows (through a predictive algorithm fed by a database of personal data and gambling patterns) when an individual customer having a rough day at the slot machines is close to leaving the casino – and potentially never return. At that point, a casino clerk comes up to that individual, and goes

“I see you are having a rough day. I know you like our steakhouse. Here, I’d like you to take your wife to dinner on us right now.” (31)

Thus, this is a sophisticated kind of anti-market activity. Not only can the biggest players (like Wal-Mart) use huge databases to predict future demand of a certain product - companies can fine tune their relation to consumers, reeling them in, keeping them away from the competition, while extracting the maximum profit from them.

And that is only half the story. The examples above are based on regression analysis (and neural network analysis), mining historical data for “on aggregate” patterns. Companies are also using “randomised trials” to conduct experiments with the mass of consumers. One example - an online bookseller can make random changes in the price of a certain book, so as to ascertain the optimum price. Thus, corporate operations are effectively turned into laboratories, allowing corporations to continually monitor the quantum flows of customer desire.*

The oligoptic vs. the panspectric

So, to recap - the oliopticon and the panspectron are both

- means of rendering certain elements of reality visible.
- Both models feature a move away from human vision surveilling subjects or objects, and
- both models feature a “distributed” collating of data not usually associated with Foucault’s panopticon.

However, there are differences:

- The former allows managers in command centrals to see certain performance metrics of the operation; the latter allows the analyst to detect previously unseen patterns in aggregate data. The latter is thus more focused on prediction.
- The former is based upon a pre-formed knowledge of what to measure, which is hard-coded into the apparatus. The latter is increasingly based on heterogeneous digitalised data, “scraped” from (m)any source(s), with the intent to explore patterns. This goes especially for neural network analysis, in which the technique itself explores what factors that are to be featured into the predictive algorithm.

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* Footnote: On the use of Tardian expressions such as “quanta” – as Andrew Barry and Nigel Thrift write

The ‘economy’ described by Tarde is perhaps closest in form and spirit to modern consumer ‘flock and flow’ economies which are based on tracking and periodically initiating consumer enthusiasms. [...] It is an economy which depends on tracking as well as generating the propagation of desires. (”Gabriel Tarde: imitation, invention and economy”, Economy & Society, Vol. 36, No. 4, pp. 518-519)

Thus, ironically,

a certain form of Tardean programme for social research is only beginning to be realized, although it is likely to be carried out not primarily by academic researchers but by corporations, market research agencies, governments, and regulators (521)

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