Considering datafied colonialism

# Considering datafied colonialism In this fourth and final assignment I approach the perception of datafication through a lens of colonialism and exemplify this tendency and its effects through the three individual assignments prior to this. ## Datafication and Data Colonialism Datafication, as articulated by among others Mayer-Schönberger & Cukier (2013), van Dijck (2014) and Mejias & Couldry (2019) can in itself be understood as a colonial process. Not just metaphorically speaking, when reading that “data is the new oil” (The Economist, 2017), but literally as a new mechanism of data colonialism (Couldry & Mejias, 2019a), which is appropriating human life in order for data to be repeatedly withdrawn from it in order to reach benefits for capitalist interests (Mejias & Couldry, 2019). As Mejias & Couldry and Lauren Scholz have noted, this metaphor can be said to actually “side-step evaluation of any misappropriation or exploitation that might arise from data use” (Mejias & Couldry, 2019, p. 4; Scholz, 2018, p. 2). When situated within the framework of Data Colonialism, as presented by Couldry and Mejias (2019a, 2019b, 2019c), datafication can be investigated as an extension of the coloniality of power, defined as the power which lies in its control over “social structures in the four dimensions of authority, economy, gender and sexuality, and knowledge and subjectivity“ (Mohamed et al., 2020, p. 5; Quijano, 2000). Information and communication technologies have, historically, enabled the surveillance and administration of colonies in conjunction with propagation of legitimizing narratives in regards to dispossession and extraction, and datafication can be said to continue and extend those functions (Mejias & Couldry, 2019, pp. 6–7); the concept of datafication can in this colonialized lens be said to surpass the scope of ‘just’ a capitalist mechanism - it’s a land grab (Couldry & Mejias, 2019a). ## Partaking in datafication In the first assignment I argued that I’d “digitized my physical presence on my bike in regard to spatiotemporal dimensions”. The data, referring to the CSV-file (See Appendix "[20200924080218-22138-data.csv](https://curatingdata.broholttrans.dk/resources/20200924080218-22138-data.csv)”), is pointing at exactly where I’ve been at what exact times represented through GPS-coordinates and timestamps. If I, instead of approaching this as efforts of digitization as I’ve done in the assignment itself, am to address this phenomenon as acts of exactly datafication as described above, I’d argue that I am willfully positioning myself as both subject and object. By supplying ‘raw’ (Gitelman, 2013) nonsensical data, and in turn receiving meaningful meta-data which has been extracted from it, I’ve deliberately entered into what Couldry & Mejias describes as “data relations”, being “ways of interacting with each other and with the world facilitated by digital tools” (Couldry & Mejias, 2019a, p. xiii). I can be said to voluntarily enact, as Karen Barad would phrase it, agency (Dolphijn & Tuin, 2012) towards shaping my life in a such fashion, so that I am better able to get hold of improved data. This, in an effort to supply Strava with it, in order to myself be able to better understand and communicate my workout sessions. Through this lens, Strava has effectively morphed into a medium of communicating and interacting with others, in a social fashion, and the world around me in my quotidian life as an amateur cyclist – of which I can only be assumed to have partial, or at least limited control over. But more importantly they now hold the power of knowledge, as they are the ones appropriating the data, in the meaning-making from coordinates and timestamps. If I were to not adhere to Strava’s predefined models of workouts, the workout I’d just performed might as well not exist, and I would be hard pressed to communicate my efforts, as Strava is doing this ”codifying of life into datafied realities” (Mejias & Couldry, 2019, p. 4). In this case, I am now working hard, quite physically and literally, in order to supply Strava with sufficient datapoints of my whereabouts at certain times; one could say that I’ve become subject to continued surveillance and monitoring, as my physical efforts are fueling Strava’s capitalistic machine from which they extract profit – if one were to stay within the eluding metaphor of data being modern oil. ## The value of the datafied self As for assignment two, I consider it natural to continue off of the conclusive research question posed; can these datafied selves be said to hold value? The datafied self, as a digital object, holds value as a currency of information, extracted and traded by corporations - parts of what Couldry & Mejias defines as the social quantification sector; “the industry sector devoted to the development of the infrastructure required for the extraction of profit from human life through data” (Couldry & Mejias, 2019a, p. xiii). I have here approached the value of datafied selves in the consideration of economic value, as the information which the data constitutes is considered as they, for example, form the basis for ad hoc advertisement on multi-sided market platforms, as noted by Tarleton Gillespie (2010, 2018). As economic value can be said to be extracted from these datafied selves, being the reason they are systematically and routinely produced and maintained in the first place, it seems natural to assume some degree of ontological value imbued in those. Although Cheney-Lippold says they’re ultimately meaningless for us, they are still, at the moment of advertisement, “good enough for Google” (2017, p. 148), which I interpret as a way of stating, that even though our datafied selves are gibberish and meaningless for us directly, they’re indirectly responsible for how were treated by algorithm-driven platforms as Google, Facebook and Twitter. As long as their perceptions of us work, they don’t need to necessarily be correct – they are still very capable of exercising, what Couldry & Mejias take on as, modern colonialism; we need not look further than the Facebook and Cambridge Analytica scandal (Couldry & Mejias, 2019a, p. 3). The datafied self which I had explored in assignment two was the product of a limited third-party algorithm, the Apply Magic Sauce project, on behalf of a limited set of data. In the real tangible world towards a future, which Couldry & Mejias defines as the Cloud Empire, “a totalizing vision and organization of business in which the dispossession of data colonialism has been naturalized and extended across all social domains” (Couldry & Mejias, 2019a, p. xiii), we experience an amassing information as the transformation of social relations emerges. It can be considered as “the larger outcome of this combined growth of the social quantification sector and data practices right across business and social life” (Couldry & Mejias, 2019a, p. xv), which I will definitely describe as holding value; operating within the system of data colonialism, the datafied self produced through acts of datafication can thus be said to hold value. ## Disembodied selves As for my third assignment I will be pointing at my own partaking of the subjective role of a curatorial process, as opposed to being an object of curation myself which has been the focus up until this point. I originally worked with a group towards creating what in this frame of reference can be approached as a folksonomy, which we termed zoteronomics, as a way of dealing with taxonomies in a social setting, where we were forced to col-laborate in order to reach a meaningful categorization in a Zotero library consisting of what we termed disembodied metadata. We’d mainly been judging and categorizing, regarding the texts which we hadn’t read, judging from their covers, abstracts, table of contents, perhaps skimming the contents. But nonetheless we’d been categorizing them alongside known texts. As Zotero operates mainly on meta-data, we haven’t been working with ‘data’ per se, but rather operating from and upon metadata comprising the objects of categorization. This experience of working with what we’ve termed disembodied data has mediated my personal stance and view towards the workings and intentions of algorithms and their connections towards decision-making upon my actual lived social life. As these texts has had nothing to say for themselves in regard to our collective evaluation of its constituents, so do I not have much to say in how my online reality is tailored as to how I’m constantly under evaluation – at the end of the day, we’re all just being judged by our covers, being juxtaposed. In this way, we surely are not considered greater than the sum of our parts – we are nothing but the parts. Parts which are designed to fit the information models subjectable to enumeration. I here want to continue this notion of disembodiment, as I argue the same phenomenon is taking place with our datafied selves. Having taken part of this process, I here attempt to draw comparisons with the colonialism-part of Couldry & Mejias’ notion of data colonialism, as by disembodying historical slaves’ potential to generate value, be it extracting coal from the ground or by producing high quality data for Strava, the object is separated from the subject; the same, I argue, applies when our datafied selves becomes disembodied from our social selves, as we are reduced to labor power in a modern Marxist understanding (Couldry & Mejias, 2019a, p. 30), as we enter data relations which are “normalizing the exploitation of human beings through data, just as historic colonialism appropriated territory and resources and ruled subjects for profit” (Couldry & Mejias, 2019b, p. 336). ## Final comments Having approached the prior assignments with this framework of data colonialism, I’m left wondering how these data relations can be said to affect me. I’ve got no real grasp of the actual inner workings on some of these relations I take active part of; data for services. I quote Couldry & Mejias as a provocation directed at myself: “The final turn of the data relations spiral comes when categorizations derived from the processing of your data are applied back onto you, the human subject, from whom the data was derived, whether or not you are identified by name” (Couldry & Mejias, 2019a, pp. 29–30). I do not see myself as the modern equivalent of a Marxist slave (2019a, p. 30), but I now more than ever realize my partaking in the datafication as a whole, and as “[d]ata subjects often attempt to modulate their behavior in order to influence the algorithm that they believe is categorizing them” (2019a, p. 30), I also now recognize my enactment of myself online as exactly that; a data subject believing that algorithms is categorizing it. Am I then a realist or pessimist? I suppose I will find out eventually – in the meantime I will continue opting out of social media, embracing my current situatedness whilst remaining open towards new ones. ## Bibliography * Cheney-Lippold, J. (2017). We are data: Algorithms and the making of our digital selves. New York University Press. * Couldry, N., & Mejias, U. A. (2019a). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford University Press. * Couldry, N., & Mejias, U. A. (2019b). Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject. Television & New Media, 20(4), 336–349. https://doi.org/10.1177/1527476418796632 * Couldry, N., & Mejias, U. A. (2019c). Making data colonialism liveable: How might data’s social order be regulated? Internet Policy Review, 8(2). https://doi.org/10.14763/2019.2.1411 * Dolphijn, R., & Tuin, I. van der. (2012). New Materialism: Interviews & Cartographies. New Metaphysics. https://doi.org/10.3998/ohp.11515701.0001.001 * Gillespie, T. (2010). The politics of ‘platforms.’ New Media & Society, 12(3), 347–364. https://doi.org/10.1177/1461444809342738 * Gillespie, T. (2018). Regulation of and by Platforms. In J. Burgess, A. Marwick, & T. Poell, The SAGE Handbook of Social Media (pp. 254–278). SAGE Publications Ltd. https://doi.org/10.4135/9781473984066.n15 * Gitelman, L. (2013). “Raw data” is an oxymoron. The MIT Press. * Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work and think. Murray. * Mejias, U. A., & Couldry, N. (2019). Datafication. Internet Policy Review, 8(4). https://doi.org/10.14763/2019.4.1428 * Mohamed, S., Png, M.-T., & Isaac, W. (2020). Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology. https://doi.org/10.1007/s13347-020-00405-8 * Quijano, A. (2000). Coloniality of Power and Eurocentrism in Latin America. International Sociology, 15(2), 215–232. https://doi.org/10.1177/0268580900015002005 * Scholz, L. (2018). Big Data is Not Big Oil: The Role of Analogy in the Law of New Technologies. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3252543 * The Economist. (2017, May 6). The world’s most valuable resource is no longer oil, but data. The Economist. https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data * van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208. https://doi.org/10.24908/ss.v12i2.4776 ## Appendix * Appendix "[20200924080218-22138-data.csv](https://hackmd.io/@martinbtrans/assignment-1-dataset)"