Areeq Hasan ’20… The Information Revolution: A Marxist Analysis

Makers of the Modern Mind The Information Revolution:

A Marxist Analysis

Areeq Hasan ’20

The restriction of information to the scope of the individual has as long been integral to the successful survivalistic tendencies of the human species as has been the breaching of data secured by competing individuals. Indeed, it is out of the struggle to dominate this very information gradient that the power structures intrinsic to human society have emerged, manifested as the Marxist notion of class struggle between the bourgeoisie and the proletariat. For millennia, the statistical range of this information gradient has remained similar given the statically classical nature of the collection and storage of data. Amid the current technological climate of rapidly increasing global interconnectedness and the real-time flow of information recursively supplying and demanding big-data storage solutions and data analysis mechanisms, however, human society appears to be approaching a revolution in information that is fundamentally altering social mechanics by means similar to the dialectic transformation of the global superstructure as propelled by elementary alterations in the societal base during the First Industrial Revolution. As a direct repercussion of this novel, nonlinear growth in the collection and storage of data, the bourgeoisie, as regulators of information flow, have become exponentially strengthened in their instrumentalization of information as a means of manipulating the proletariat who are constant generators of data, creating a divergence in the information gradient and, thus, socio-economic divide between the bourgeoisie and proletariat that ultimately provides a means to establish the conditions for a global revolution in hierarchical dynamics.

In order to apply Marxism to interpolate the social sub-mechanisms constituting the revolution in information, the relevant postulates of Marxist social theory must first be established. The exploitative characterization of the bourgeoisie as a collective entity interested solely in material gain at the cost of the proletariat is directly stated in Marx’s Communist Manifesto, wherein he claims that the bourgeoisie “has left remaining no other nexus between man and man than naked self-interest” via “shameless, direct, brutal exploitation” of the proletariat (Marx 15-16). Despite the fact that, in a modern context, the bourgeoisie consists, in part, of the large private enterprises of the tech industry from Alphabet Inc. to Apple Inc. and Facebook Inc., hegemonic forces only showcase the direct benefits these companies 33

provide us, specifically in the form of physical product. The bourgeoisie masks their exploitative tendencies, as shown by their mass data theft and intentionally implementing algorithmic biases to maximize profit despite negative repercussions on the client-end. Furthermore, Marx claims that the “bourgeoisie cannot exist without constantly revolutionizing the instruments of production, and thereby the relations of production, and with them the whole relations of society” (16). One instrument of production is the data collection and analysis techniques built into proprietary technological systems, altering the bourgeoisie-proletariat social dynamic by allowing the bourgeoisie to more effectively manipulate the proletariat. Marx even claims that this phenomenon creates a universal social dynamic through the penetration of the world market by bourgeois entities claiming that the “bourgeoisie… through its exploitation of the world market,” “[give] a cosmopolitan character to production and consumption in every country” (16). With rapidly globalizing companies such as Huawei Technologies Co., Ltd. and Samsung Group, this notion is more applicable than ever before in the tech industry. In addition, Marx states that an “immensely facilitated means of communication” and the “extensive use of machinery” characterize the movement of the bourgeoisie in its ‘constantly revolutionizing’ of ‘the instruments of production’ and directly highlights the optimization of information transfer, communication, as manifested today in 5G technology, low-latency streaming services, and the real-time flow of information recursively supplying and demanding big-data storage solutions (18). Furthermore, Marx emphasizes the means by which the bourgeoisie functions as a collective, stating that no “sooner is the exploitation of the labourer by the manufacturer, so far, at an end, that he receives his wages in cash, than he is set upon by the other portions of the bourgeoisie…” (18). This notion is clearly manifested in the collusive efforts of mass data theft. Finally, Marx claims that as the proletariat “direct their attacks not against the bourgeois conditions of production, but against the instruments of production themselves,” destroying products “that compete with their labour” and smashing “machinery” to pieces (18). This characterizes modern-day ethical or “white-hat” hacking as performed by organizations such as the decentralized international hacktivist group Anonymous and the international media organization and associated library WikiLeaks as dedicated to liberating information from the manipulative control of the bourgeoisie and eradicating the information gradient to re-engineer the bourgeoisie-proletariat social dynamic. As such, it is clear that Marxist social theory effectively establishes a framework by which to analyze the information revolution, and we can use it to interpolate social dynamics in 34

Makers of the Modern Mind recent milestones in the revolution.

Rapid globalization and the real-time flow of information dialectically supplying and demanding Big Data storage solutions and data analysis mechanisms has allowed for the bureaucratic collection of private information. The Facebook-Cambridge Analytica Data Scandal, for example, demonstrates the intention of the bourgeoisie to psychoanalytically manipulate the proletariat. In 2015, Ted Cruz embedded Cambridge Analytica, a small data analysis firm, into his presidential campaign to “gather detailed psychological profiles about the US electorate using a massive pool of mainly unwitting US Facebook users” matching individuals’ traits with existing voter datasets and “build[ing] sophisticated models of users’ personalities without their knowledge” amid “longstanding ethical and privacy issues” (Davies 1). In line with Marxist social theory, Cruz’s campaign, a constituent of the bourgeoisie, colluded with Cambridge Analytica and Facebook using behavioral microtargeting based on the vast amounts of profile information stored in Facebook’s databases to optimize their advertisement efforts without the consent of targets in order to politically influence the proletariat in favor of their campaign, as well as creating economic profits for Cambridge Analytica and Facebook. If not for Facebook’s vast data repositories storing an immense quantity of interaction microfeatures regarding Facebook users as made possible by the real-time collection of information, Big Data storage solutions, and data analysis mechanisms such as Deep Learning networks and Artificial Intelligence systems, Cambridge Analytica would not have had sufficient feature information for successful behavioral microtargeting. The information revolution is allowing for the bourgeoisie to more easily exploit the consent and privacy of the proletariat for their own gain by making information more accessible to the collusive bourgeoisie.

Furthermore, companies are beginning to ignore developing algorithmic biases on the server-end to maximize profit despite potential negative repercussions on the client-end, as demonstrated in a plethora of social media platforms, namely YouTube. YouTube uses deep learning neural networks to recommend content and maximize a viewer’s session time, recording many engagement and interaction micro features from liked videos and watch history to view duration and saved playlists. The recommendation algorithm appears innocent, collecting information regarding users only in order to determine what content to advertise. However, significant repercussions arise out of this system. Deep learning neural networks develop correlations betweens their training data and their performance, and biases present in the training data are reinforced and amplified in an attempt to 35

maximize performance. As such, YouTube’s algorithm, in the words of sociologist Zeynep Tufeksi, is “one of the most powerful radicalizing instruments of the 21st century,” promoting, recommending, and disseminating content “in a manner that appears to constantly up the stakes” (Friedsdorf 1). As such, a consequence of the algorithm is recursively increasing one’s intellectual depth, locking the individual into a mindset while decreasing intellectual breadth. Nonetheless, the deep learning algorithm proves extraordinarily effective at maximizing session time, and, as such, this repercussion is disregarded as trivial, rendering it yet another means by which the bourgeoisie exploit the proletariat for their own economic gain.

The struggle to dominate this very information gradient, from which the power structures intrinsic to human societal mechanics have emerged, manifests in the Marxist notion of class struggle between the bourgeoisie and the proletariat. Although the statistical range of this information gradient has remained similar for millenia, the revolution in information collection and analysis has fundamentally altered social mechanics. As a direct repercussion of this novel growth in the collection and storage of data, the bourgeoisie have become strengthened in their instrumentalization of information as a means to manipulate the proletariat, creating a diverging widening in the information gradient and therefore the socio-economic divide between the bourgeoisie and proletariat.

Works Cited

Davies, Harry Fox. “Ted Cruz using firm that harvested data on millions of unwitting Facebook users.” The Guardian, 11 Dec. 2015. The Guardian, www.theguardian.com/us-news/2015/dec/11/senator-ted-cruzpresident-campaign-facebook-user-data. Accessed 8 Feb. 2020. Friedersdorf, Conor. “YouTube Extremism and the Long Tail.” The Atlantic. The Atlantic, www.theatlantic.com/politics/archive/2018/03/ youtube-extremism-and-the-long-tail/555350/. Accessed 7 Feb. 2020. Madrigal, Alexis C. “How YouTube’s Algorithm Really Works.” The Atlantic. The Atlantic, www.theatlantic.com/technology/archive/2018/11/ how-youtubes-algorithm-really-works/575212/. Accessed 7 Feb. 2020. Marx, Karl. The Communist Manifesto. Marxists Internet Archive, www. marxists.org/archive/marx/works/download/pdf/Manifesto.pdf. Accessed 8 Feb. 2020. 36