Patrice Riemens on Sun, 25 May 2014 00:40:17 +0200 (CEST) |
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<nettime> Ippolita Collective, In the Facebook Aquarium Part Two, |
Ippolita Collective, In the Facebook Aquarium, Part Two The Libertarian World Domination Project: Hacking, Social Network(s), Activism and Institutional Politics Social networks as seen through the anarcho-capitalist lens - or the management of sociality through Big Data. (section 4, continued) (The story and the stratification of this web of relationships that we call society forms a kind of consensual imagination which we can access thanks to the symbolic and linguistic functions of the neocortex and the peridium (?)....) [rerun from previous installment] .... Societies of animals with only a small frontal cortex are less complex than human societies and produce practically no artefacts. Neuro-scientific research also shows that when the functionalities of a person's frontal cortex are compromised, sHe loses the specifically human characteristic of empathy. Such a person will no longer be able to conceive what someone else experiences while they share the same space. Having seen their reflexive capacity either damaged or even, destroyed, they are no longer able to conceive themselves as individuals belonging at the same time to various social groupings (like family, sporting club, network of friends, social class, workplace or project team, local community, nation, etc. etc.), neither are they longer able to interact purposefully with all of them. The meaning usually assigned to things and to the world becomes undefined, everything is muddled, fluid, interchangeable and equally valid. Nothing makes sense any longer, in a distinct, articulated and communicable way. To understand the world of which we are part means to position ourselves, in space and time, in an environment which transcends our finiteness as individuals, while still re-placing this environment through an imaginary creation endowed with signification. The very prospect of imagining and planning a future with the help of previous experience, and hence to understand what is around us, becomes moot at the moment that we are no longer able to go through and modify in a significant way (that is with an idea that has stricken us, or a shared emotion that moves us), the networks of which we are part. Then, even by way of imagination, this has become impossible. And paradoxically, when we are confronted with too many data, we become unable to make sense of them. The sheer mass of data and the speed at which information hits us makes analysis either garbled, or potentially extends the time necessary towards infinity. Such an analysis hence becomes pointless, and impossible on the long term - yet two concepts may render a further exploration feasible: Big Data and profiling. Both are thoroughly interlinked. At the beginning of the 21st century, one gigabit (GB, one billion bits, i.e. one billion typographic signs) was considered to represent quite an amount of data. Ten years later and the Internet contains a hardly imaginable amount of data, something like five trillion - and counting: the numbers are bound to double every year [29]. Two examples so as to grasp this order of magnitude: a high-definition feature film needs a number of GBs; a personal computer contains more data than an entire family would have been able to produce over several generations. There are billions of site-pages on the Internet, but there exists also a number of non-Internet-linked networks on top of that, and they are probably larger than anything one can imagine, or even what a human brain can fathom [30]. We have entered the era of Big Data, and we are seeing only the beginning. In everyday life also, even when one is not directly involved in the use of all kinds of devices generating data, there are countless occasions to notice that the gathering, stocking and analyzing human activities-related data have multiplied manifold over time. Details are ever more numerous, the resolution is ever more fine-grained. Every single day, an extraordinary amount of SMSs, mails, calls, posts, pics, videos and chats, together with an innumerable amount of various documents are produced. There is no way we could memorize even a fraction of all data being send and exchanged, including those travelling over WiFi and other mobile tools that register our every single move in space. Search engines register meanwhile all our web-requests (bwo. /logs/, cookies, LSO - local shared objects). Automatic payment systems in toll booths, supermarkets, ATMs etc, keep track of all our purchases. /Social networking/ platforms memorize all our connections with friends, colleagues, co-workers, loved ones, etc. Register, stock, archive,and analyze all and everything, and ever more of it, and faster and faster: mass and speed are still being viewed as something positive. However, it is not so much the size of all these data that counts - inordinate as it may be - but their inter-relationship, and the ever greater opportunity to access and make use of them from out a smartphone, a tablet or a PC. We are linked to all these data, they can not be dissociated from us, and they constitute our digital footprint, our identity permanently under construction, which in turn can be traced back through retrieval and analysis of our data. But this has nothing to do with knowledge: all Big Data can do is to provide ever more opportunities to make profits through profiling. We have already broached on this method in the first part of this book. Profiling consists in the creation of a template, basically a digital finger-print that is unique and identifies an individual in an unequivocal fashion. No wonder then if the vocabulary used, 'fingerprint', 'traces', all reeks of a crime scene: the whole line of research actually originates in forensic science. Indifferent which digital tool a user makes use of, sHe will leave a trace that might be an occasion for profiling through control and archiving operations. The metadata take care of profit-harvesting, which in turn makes the 'Web 2.0.' what it is - and its use, 'for free'. Human beings, unlike machines, are not able to manage Big Data. Machines, moreover, analyze them and formulate also real-time forecasts about individual's most likely behaviour (/narrow-casting/). Please then, remember that for anarcho-capitalism, the individual realizes her/himself in action, in its two specular manifestation as production and consumption. But since people are no longer able to orient themselves amidst the noise (of data) that surrounds them, it becomes necessary, in order to accelerate the process, to delegate this tasks to machines. In order to bring the ideal society nearer, individuals need to become machine-readable. They must also continuously feed the data-leviathan within ever faster retroactive loops. Their explicit and implicit preferences are then stocked, dis-aggregated, and then re-aggregated, and all this in real time. (to be continued) next time: more on profiling and Big Data ----------------- [29] the information comes from a report by the marketing consultancy IDC, and should be treated with the usual caution: their, like /all/ data should be evaluated and contextualised: IDC is a large multinational enterprise with its own interests in the matter. But since we only wanted to show our reasoning the exact numbers do not really matter, even at a higher or lower scale, the argument would have remained the same. For more see: http://australia.emc.com/collateral/demos/microsites/emc-digital-universe-2011/index.htm also a report under David Boulier's direction, /The Promise and Peril of Big Data/, Washington, The Aspen Institute, 2010. http://www.aspeninstitute.org/publications/promise-peril-big-data [30] Unlike what is generally believed, public information constitutes only a tiny fraction of all information stockpiled in networks. A large part of all information extant remains hidden: state or industry secrets, removed from the public eye, and largely meant to subjugate, alienate and manipulate us. See the important research undertaken on 'secret materials' by Peter Galison, a physics professor at Harvard, especially 'Removing Knowledge', /Critical Enquirer/ 31, 2004 (University of Chicago Press) http://www.fas.harvard.edu/~hsdept/bios/docs/Removing%20Knowledge.pdf and his mind-blowing documentary film, together with Robb Moss: http://www.secrecyfilm.com/about.html ----------------------------- Translated by Patrice Riemens This translation project is supported and facilitated by: The Institute of Network Cultures, Amsterdam University of Applied Sciences (http://networkcultures.org/wpmu/portal/) The Antenna Foundation, Nijmegen (http://www.antenna.nl - Dutch site) (http://www.antenna.nl/indexeng.html - english site under construction) Casa Nostra, Vogogna-Ossola, Italy # distributed via <nettime>: no commercial use without permission # <nettime> is a moderated mailing list for net criticism, # collaborative text filtering and cultural politics of the nets # more info: http://mx.kein.org/mailman/listinfo/nettime-l # archive: http://www.nettime.org contact: nettime@kein.org