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How algorithms increase consumerism

Algorithms are structured decision-making processes that employ a set of rules or procedures, to automatically “supply outcomes based on data inputs and decisional parameters” (Airoldi,2019:p2). Thus, from this perspective, algorithm are used in our everyday lives. However, with the rise of new technology and new media algorithms have also become highly advanced, with many social media platform and tech giants, such as Facebook, Twitter, Google, YouTube and Amazon, employing algorithm to output certain recommendation based on a consumer’s past actions and behaviours. Thus, in this essay algorithms are analysed in term of how they increase consumerism.    

An algorithm is a system used to transform input data into a desired output, thus can be used to help consumers make “decisions in market transactions” (Gal,2017,p314). This is achieved through algorithmic systems incorporated in digital platforms and services such as Facebook, Amazon, Tinder, Netflix and YouTube. Which analyse input data in real-time and provide an output tailored to consumers “predicted needs and desires” (Massimo,2019:p2). With Amazon, this is attained through an A9 algorithm system, which considers keyword and picks up sale conversation, in order to decide how products are ranked in search results. Thus, as amazon provide consumers with relevant products recommendations, gaining higher sales is more likely to be achieved. However, using algorithms in order to increase consumerism, although highly beneficial for the company, for society this has had many negative effects. Including generating a society heavily obsessed with “consumerism” and “materialism” (Hatherley,2013:Guardian). This according to researchers at the University of California Los Angeles, is demonstrated by the English language, which has become increasingly consumeristic. With words such as “get”, “unique”, “individual”, and “self” becoming more apparent in the English language (Hatherley,2013:Guardian). 

Thus, here evidence reinforces the powerful impact which consumer algorithms can have on society.

Nonetheless, as platforms such as Netflix also employ algorithms, known as “pragmatic chaos” (Cohn,2019:p56), in order to provide audiences with related videos. Consumerism, in this case, is also gained, as audiences rely on Netflix for deciding what to watch next. This, according to theorists Hallinan (2016), generates a recursive relationship – a “closed commercial loop”-, which ultimately produces an “algorithmic consumer culture” (Airoldi,2019:p3). Whereby, computers running on complex “mathematical formulae classify and hierarchize people, places, objects, and ideas” (Granieri,2014:online). Thus, as algorithmic systems now output more personalised recommendations, in order to introduce individuals to new cultural goods. Audiences from this perspective, become wrapped in the toils of consumerism. However, this recursive process is also evidently seen through Facebook. Which use algorithms, known as EdgeRank, to invisibly ranks and filters content presented to the user. Through this Facebook maintain audiences on the site, as algorithms used, prioritise certain messages and posts. However, as Facebook’s algorithmic systems also focus on users “likes, comments and impression” (Bucher,2019:p89), in order to output relevant social media posts and messages. Algorithmic systems, from this perspective, also output information in a “recursive and path-dependent way” (Airoldi,2019:p3). Thus, again reinforcing this rise towards an algorithmic consumer culture.

Additionally, on many social media websites, such as Facebook and Instagram, algorithms have also been used to provide specifically tailored advertisements for the user. This is achieved as social media network “use cookies” (McAllister,2013:p184), to track individuals downloads, shares, reposts and likes. In effect enabling tech giants to gain enough information on users personality and consumption habits. Through this tech giants increase consumerism, as tracking technologies enable social media platforms to provide personalized online advertisements. This process, according to theorists Raley (2013) however, is coined as “dataveillance”, given the shifts in modes of surveillance that increasingly monitor users through social media and online communication technologies, by means “of advanced tracking technologies” (Granroth,2019:p2). Thus, on Facebook, dataveillance is achieved, as Facebook uses cookies, web tracking, location tracking and continually gain email from other websites, in order to provide users with personalised advertisements. However, as companies continue to fill the internet with personalised advertisements, for Chomsky, this has in some respect “slowed the internet down” (Fuchs,2018:p72). As advertisement not only slow down computer systems, however also contribute to the narrowness of coverage. Though this, as the internet continually provide users with a vast array of online advertisements, according to theorists Chomsky, this in effect provides a distorted view of the world. Such views are supported by Baudrillard, who believes consumers are trapped in invisible “filter bubbles”. As algorithmic systems encode desires which reflect only “micro-targeted predictions” (Belk,2013:p330). Thus, from this perspective, evidence reinforces the negative impact which advert algorithms can have on society.   

Additionally, on Instagram, gaining user information is also attained, as Instagram’s algorithmic systems can use image recognition as well as extract buzz words from the site. Through this, Instagram also increases consumerism as algorithmic system enable the platform to provide users with personalised advertisements. However, in terms of extracting buzz words, a technique used by many social media platforms, such methods also aim to keep users on the app. As automatic keyword extraction, “based on statistics, linguistics, and machine learning” (Vincenzo,2018:online) enables platforms like Instagram to recommend key posts and messages. Thus, again here consumerism is achieved as algorithms use keywords extractions, in order to ensure user, become heavily reliant on the app. Additionally, other forms of algorithms on Instagram also include bots, which is an AI software used to “perform an automated task” (Soto,2018:p40). On Instagram algorithms allow bots to recognize text patterns, like captions, direct messages, comment appropriately on photos as well as direct users towards sponsored advertisements. Thus, Instagram bots, in this case, can also be used in order to increase consumerism.  

Overall, this essay reinforces the way in which algorithms are used in order to increase consumerism. For many social media platforms such as Facebook and Instagram algorithms are utilised to keep audiences on the site by providing users with personalised posts and recommendations. Additionally, as platforms such as Facebook and Instagram also provide users with personalised advertisements consumerism is also increased. On Amazon however, algorithm system, which pick up key words and sale conversations, also increase consumers as Amazon, similar to Netflix, provide users with related recommendation. Thus, here evidence shows the different ways tech giants use algorithms, in order to increase consumerism.


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