MA Thesis New Media and Digital Cultures University of Amsterdam Student: Jan Zuilhof Student nr: 6152139 Date of completion: 14-11-2014 Supervisor: Michael Dieter Second Marker: Marc Tuters

The Soundtracked Self: Algorithmic Individuation on Spotify

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I would like to thank Michael Dieter for supervising this thesis. The conversions that we have had about the topic and relevant literature were truly insightful and have helped me a lot. His patience is also very much appreciated. Although he left the University of Amsterdam before I did, he continued the supervision process, for which I am very grateful.

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INTRODUCTION 4

1. CAPTURING ATTENTION: LEISURE OR LABOUR? 6 1.1 INTRODUCTION 6 1.2 DEMOCRACY ON THE WEB 6 1.3 EXPLOITED PROSUMERS 8 1.4 ALIENATION: THE DOUBLE LOGIC OF PROSUMPTION 10 1.5 CONCLUSION 13

2. INDIVIDUATION IN THE COMPUTATIONAL INDUSTRIES 15 2.1 INTRODUCTION 15 2.2 PSEUDO-INDIVIDUATION IN THE CULTURE INDUSTRY 15 2.3 RECORDING OF TRACES: ASSOCIATION 20 2.4 CONCLUSION 24

3. ALGORITHMIC RECOMMENDATION: INDIVIDUATION THROUGH SPOTIFY 25 3.1 INTRODUCTION 25 3.2 BEATS IN BITS 27 3.3 SOUNDTRACKING YOUR LIFE 31 3.4 DOWN TO BUSINESS 40

CONCLUSION 46

LITERATURE 49

3 INTRODUCTION

"Maybe with motion sensors in phones, we can start guessing things like 'are you running, biking or driving?' Maybe it has a temperature sensor, or a heart rate sensor so we can get a sense of whether you're tense.

Maybe it connects to some other services, for example if we know more about your sleeping habits we know what time you're likely to go to sleep or what time you wake up it can be personalised."

-Donovan Sung- Product manager at Spotify (Smith)

When my girlfriend and I wake up in the morning, we will sometimes listen to the radio. Whether it plays mostly depends on how we communicate: “shall I turn it on?... shall I turn it off?... should it be louder? The decisions that we make are based on the opinions of two humans that either have to debate, or agreed upon it in the first place. Whichever one of those it is, we have explicitly expressed how we feel about it, and by this have made it into a collaborative practice. During the day, many more of these types of situations happen. When friends come over for diner, should there be music playing in the background? And if yes, which music will every one like at least to some extent? What radio station do the most people like to listen to at work? All of these things can be discussed, and people can communicate their preferences in a way that everybody understands. In the past years, however, another approach for selecting music has also gained popularity. Whereas humans have been curators during the first century of recorded music, this can now also be delegated to algorithms. Although both human-to- human and algorithmic recommendations rely on the preferences of people, they also differ from each other; algorithms can process information in ways that go beyond human comprehension. This thesis is about how such ways influence individuation. To look for those implications, Spotify is used a case study because the service has caught much attention in the past years and is explicit about its motivation, which is revitalizing the music industry. Why Spotify is also important is its data driven approach. In the quote on the top of this page, Spotify’s Donovan Sung speaks about possible future directions that Spotify might go in. Although this is still speculation, it does signify that the extraction of data might get even more abstract than it sometimes already is now. This abstraction is an important thread for my project here. In a sense, my approach is quite the opposite of

4 Spotify’s, which means that I will look for answers that cannot be found in data alone but should be searched in theorizations. The research question that will guide me through this thesis is: how do the discursive and technological dimensions of Spotify influence individuation? To find an answer to this question, I will treat how relations between humans and web platforms can be theorized terms of labour in the first chapter. Concluding this chapter, I will offer a definition of the widely used concept of prosumption. In the second chapter, I will focus on theories about how the distribution of media influences individuation. This chapter also functions to introduce the vocabulary of associated and dissociated milieus, which will be used later. The case study of Spotify will be treated in the third and final chapter. For this analysis, the theories about prosumption, association and dissociation will be used as a framework.

5 1. CAPTURING ATTENTION: LEISURE OR LABOUR?

1.1 Introduction In this chapter, I will discuss the first part of the theoretical background for this thesis. Understanding relevant debates about the economy on the web and its influence on subjectivity is crucial for the analysis of Spotify that will follow in the third chapter. I will begin by briefly sketching out why the democratic and emancipatory character that the web sometimes seems to have should not be taken for granted, but instead examined critically. Next, I will move into a more specific direction, which is a Marxist description of the economy on the web. Doing so, I will show that the traditional Marxist concepts of exploitation and alienation have undergone a transformation, yet are still present in today’s digital structures. This chapter also functions as an introduction to the second chapter, where I will go further into the influence of corporate orchestrated media on subjectivity.

1.2 Democracy on the Web The web offers many opportunities for people to communicate and express themselves. However, these opportunities are restricted by technological rule sets. User generated content is not only information produced by an individual, but also a composition of the rule set of a specific platform and an act or acts performed by people. There are numerous examples of websites and –applications that allow users to perform an act that influences what happens in that particular space. Social media like Facebook enable people to interact with each other, and potentially anything that can be expressed in written language can be discussed there. Instagram lets its users take any picture of the real world and upload it to their database. The rhetoric of these types of platforms often suggests that anything can be done. Facebook states that its mission is to “give the people power and make the world more open and connected” (“About Facebook”). Instagram lets people share their lives in an easy way for free (“Instagram”). But the way in which these platforms are set up contributes to what can and cannot be done. While a person can decide what status update he or she will like or comment on, it is Facebook that has decided that you can like- or comment on a status update. On Instagram you can share every moment of your life, but Instagram also arranges the set of filters you can choose from so your friends will see your life in a very ‘Instagram way’.

6 So although people obviously contribute to web platforms in their own way, the spaces and conditions through which they move partly shape their roles. Furthermore, this is complicated by the way various platforms are interconnected. Music platforms such as Spotify and Soundcloud, or video platforms such as YouTube and Vimeo all encourage their users to ‘share’ content on social media like Facebook and Twitter. Facebook and Twitter even encourage their users to link content between the two platforms, so that a message posted on one will also appear on the other. All of these platforms work according to their own logic and follow their own business model, and both them and their users have their own agendas. The result of this is a complicated system of spaces, structures, and acts, in which various actors with different needs move. What this system – the web - is has been theorized in various ways in the past decades. One term that has resonated for years was ‘web 2.0’ (O’Reilly 2007). It was used to describe a new structure of the web in which companies “leverage customer-self service and algorithmic data management to reach out to the entire web” (ibid: 21), and “network effects from user contributions are the key to market dominance” (ibid: 24). While O’Reilly mainly writes about business models, the same shift has also been noticed in cultural studies. In Convergence Culture (2006), Henry Jenkins argues that new media reshape old media. He acknowledges that these changes are corporate driven, but he also writes that it is up to the people whether they are ready for greater participation (ibid: 243). Many more have argued that this phenomenon – often described as ‘prosumption’ – on web 2.0 platforms has changed the role of consumers in the sense that they are more empowered and conscious now, and the web is a largely democratic medium (Andriole 2010: 78, Bruns 2008: np, Deuze 2007: 244, Leadbeater 2008: 6, Lin 2007: 102, Tapscott & Williams 2010: np). There are others, however, that claim that these accounts tend to focus on the aspect of participation without critically examining its implications. Authors should take into account that the web is still ruled by big corporations that turn user generated content into large profits. Van Dijck & Nieborg (2009: 869) argue that Jenkins recognizes the difference between producers and consumers, but his rhetoric is the same as that of business manifestos that do not make this distinction. Elsewhere, Van Dijck (Van Dijck 2009: 42) has argued that user agency should be understood in its complexity, since “the boundaries between commerce, content and information are currently redrawn”. According to Christian Fuchs, moreover, positive claims about the revolutionary characteristics of web 2.0 platforms should be more modest. The web has always been communicative, but recent developments such as greater bandwidth and

7 cheaper technologies such as digital cameras make it possible for people to create more content (Fuchs 2011: 289). So although the web might now be a space in which people can actively engage in content creation, it is important to critically theorize the social and economic implications of these new platforms.

1.3 Exploited Prosumers One very specific direction that the previously mentioned discussion gone into is whether what happens on the web can be described in Marxist terms. Marx wrote the trilogy of Capital in the same period that the telephone was invented, and the web would not be there for another century. The object of his analysis was capitalism with factory owners and their employees, which seems to differ quite a lot from people engaging in online activities in their leisure time. However, since value is created by activities of people on the web, a Marxist framework can still be relevant to gain insight in the relations that exist between platforms and their users. Many web platforms are corporate driven, and since users generate content that is turned into profit, the question arises if they are being exploited. In this section, I will juxtapose different perspectives regarding this question. This is often strongly related to the concept of alienation. I will turn to this in the next section, and how this can be related to the web and prosumption. To find an answer to these questions, I will begin with a brief explanation of what exploitation in the Marxist tradition is. According to Marx, value can be measured in units of time. The wage that the worker gets paid to produce goods is reflected in the value of the product. This is accompanied by the value of the goods that have been used, which is also based on the labour time spent to produce them (Marx 1972: 116). However, there is a difference between value and price, since there does not have to be a correlation between the labour hours used to produce a good and the price that the seller sets. So value can be expressed in units of time, while the price can be expressed in money (Fuchs 2012: 634). Marx called the part of the price that “the capitalist gets from the worker without the return of an equivalent” (Wendling 2009: 81) surplus value. Surplus value solely benefits the bourgeois employer, since the employed working class only earn their wage. The difference between the bourgeoisie and the working class is that the former owns the means of production, while the latter can only sell their labour time for a set amount of money. The surplus value generated in this process can be reinvested in more means of production, solidifying the position of the bourgeoisie, and making him or her

8 richer. In this scenario, the bourgeoisie earns money passively while the working class is exploited since people are not fully compensated for what their labour is worth.

There are significant differences between the web and the factories that Marx wrote about. Users of web platforms often engage in their activities without the expectation of economic revenue, while factory workers go to their jobs to make a living. However, web platforms are often corporate driven, and their users can generate surplus value just like factory workers. While users of platforms are not fully compensated financially for their work, Tiziana Terranova argues that it is too easy to simply dismiss labour in the digital economy as an “innovative development of the familiar logic of capitalist exploitation” (2000: 33). Rather, it reflects a complex relation between labour and people that is widespread in late capitalist societies. However, she also writes that the internet is one specific instance where this can be made apparent. For her, the digital economy is connected to the social factory that Italian Autonomous Marxists describe as a situation where work has shifted from the factory to society. This allows for labour to be seen as something that happens in society as a whole instead of in the factory alone. From this perspective, who is exploited where becomes much more complicated then when a clear separation between labour and leisure time is drawn. Whereas the factory worker was exploited during his labour, which had the sole purpose of earning wages, a member of the social factory contributes to the complete apparatus of society, while not necessarily getting paid. Like society at large, the web is a space where people contribute “free labour” (ibid) because they like it, even though they generate money that they will never see. This leads to some people stressing that the labour theory of value is not applicable to social media, because value is expressed differently. To “create and reaffirm affective bonds” (Arvidsson & Colleoni 2012: 136) constitutes value, and this is not only to boost the sale of commodities but acts as a complicated network of exchange between firms and actors. The work that users of web platforms do is often beneficial for both those firms and actors, which would make exploitation an irrelevant concept. Furthermore, if the surplus value generated on those platforms would be divided among all of its users, this would hardly produce any noticeable income (ibid: 138). Moreover, the value of web platforms is often dependent on affective investments, which

…can be interpreted as a symptom of a transition away from a Fordist, industrial model of accumulation where the value of a company is mainly related to its ability to extract surplus value from its workers (to use Marxian terminology), to an informational finance-centred model of accumulation where the value of a

9 company is increasingly related to its ability to maintain a convention or brand that justifies a share, in terms of financial rent, of the global surplus that circulates on financial markets. (ibid: 145-146)

But even if this might be true, the creation and reaffirmation of those affective bonds is time consuming. The more time people spend on web platforms, the more data they generate by refining their profiles. This allows for better personal targeting (Fuchs 2012: 639), but also contributes to the financial bubble around a commercial platform. This means that, even if not in the traditional sense, people tweeting, liking and sharing more create more value by making a platform attractive for investors. It takes a lot of time and effort to establish and maintain the brand name that Ardvisson & Colleoni write about. However, individuals who do these hours of work do not see any money as compensation. Fuchs (2011: 298) argues that workers on the web can be divided into two categories, which are paid employees and unpaid prosumers. Ritzer & Jurgenson state something similar; for capitalists, unpaid employees are even better then low paid ones. For them, working consumers create “nothing but surplus value” (2010: 26). Although all these people do not get paid, they are constantly (and successfully) being persuaded to spend more time on web platforms. Using platforms is made comfortable through the use of browser cookies that remember people’s preferences such as login details. But many websites also offer a personalized environment in which previously gathered data is used to select content that might be interesting to the user, avoiding the risk that her or she will get bored and disengage. Google Search takes location, but also search history into account when presenting its results for a query (“About Google”). Facebook and its algorithm make sure that users get to see stories of others they have recently interacted with, or content that concerns topics that they seemed interested in before (Owens and Vickrey). Websites where goods are explicitly sold like Amazon suggest more and more products to buy till infinity, but sites like YouTube and IMDB that are ‘free’ to use too constantly show their users what they also might be interested in. This capturing of attention makes sure that efforts of free labourers are indeed mutually “enjoyed and exploited” (Terranova 2000: 33).

1.4 Alienation: The Double Logic of Prosumption Exploitation and alienation are concepts that are often related to each other. In Marxist theory, exploited labour alienates the factory worker, because he or she has no direct affiliation with or power over the product that he or she produces. To understand this

10 dialectic, it is important to grasp the distinction between objectification and alienation. According to Marx, objectification exists in the relation between human work and passive material. People can shape nature, and by this create a world in which they can live. In a capitalist society, however, this objectification becomes alienated. This is a mode of production where the “fruits and tools” (Wendling 2009: 15) of production are unjustly distributed. Employers own the means of production, and the workers do not appropriate the produced goods but instead get money in exchange. The worker becomes alienated from the product he or she produces as well as from his or her life activity, since the labour is “barbarous and detested” (ibid: 49). For his theory, Marx falls back on Aristotle’s concept of use-value and exchange- value. Whereas use value actually relates to what can be done with a product, exchange value signifies what one can expect in return if it is traded. For Marx, this also brings about a double character of labour. The first is qualitative, and the ones who did the work directly enjoy the result. The second is abstract labour that is quantitatively measurable. In the process of qualitative labour, which can be expressed in use-value, objectification takes place. Abstract labour, however, can be expressed in exchange value, and this is here where the worker becomes alienated (ibid: 52). For Marx, this does not only mean that the worker is estranged from the actual product he or she produces, but also lacks self-realisation in the process. That the bourgeoisie owns the means of material production empowers them to also regulate mental production. Since the working class has no power over the material means, it is also subjected to the intellectual production that is scripted by the ruling class. Although alienation finds its roots in the economic and the technical, this psychological dimension in widespread in society. In this way, the concept of alienation transcends being a feature of specific economic relations to a mode that characterizes social life as a whole, which influences the becoming of subjectivity. This leads to a false consciousness in which the subject holds the “illusion of an individual producer whose subjectivity and sociality are founded in the acts of labour and exchange” (Ibid: 49).

Like exploitation, alienation on the web has been theorized and compared to alienation in industrial society. From one perspective, alienation has been reduced because motivations for online prosumption differ greatly from factory work. In many instances, people engage in activities that they choose, not because the feel like they need to but simply because they like it. On platforms like Facebook, YouTube and Instagram, prosumption is enjoyed for both its productive and its consumptive qualities. They could not exist if their users would not feel any affiliation with them, because they

11 facilitate “consumption that is possible because it is simultaneously productive” (Rey 2012: 408). They simply need their users to like what happens there. In this sense, late capitalism actually benefits from minimalizing alienation, since reduction of experienced alienation means more capturing of attention. This attention, however, is not all that is captured. Whereas the factory worker saw and touched what he produced, the productive dimension of prosumption has a double character. On the one hand, people communicate intentionally. On the other, large portions of data are collected and saved into databases during the process of prosumption. The exact details of what is being captured remain hidden, so the prosumer never really knows what information he or she gives, and to whom. This metadata “or information about information” (Pasquinelli 2014: 14) is also a product of prosumption, but one that the worker has not direct affiliation with, and is thus alienated from. Part of this is often used to enhance the use-value of the platform for the specific user. The user that becomes an “ambient producer” (Rey 2012: 410) can only guess which part that is. This can be related back to the Fordist mode of production, in which the factory worker is alienated from his product also because he or she only contributes to the end product by executing a task that is only a small part of the entire production process, while for the capitalist, it is the end product that counts. In prosumption, two degrees of alienation take place. The first being that metadata is extracted; the second being that this is not even a complete product. So prosumption can be experienced as “socially constructed relations…” that are “…‘voluntary’ and ‘empowering’ (which at a lived, concrete level, they are) yet, in some fundamental respects, they are not” (Comor 2010: 319). This is apparent, for example, where data is being gathered of which the prosumer never knows exactly when, where, and what is done with it. Furthermore, this metadata has exchange-value because it can be sold or directly used for better personally targeted advertisement. Moreover, improving the user experience using this metadata means that capturing attention becomes easier, resulting in even more data. An example of what can happen to the exchange value of a platform when all this data accumulates is the market value of Facebook, which is now over 200 billion dollars (“Facebook Inc. Stock Quote”). The alienation of metadata from prosumption is then directly related to the exploitation of prosumers. The algorithms that aggregate and process this gathered metadata are the centre of growing interest (Pasquinelli 2014: 14). For Pasquinelli, algorithms should be divided in two categories; the first kind translates information into other types of information, the second one extracts metadata. This second category includes Google’s Pagerank and

12 Facebook’s algorithm, but also Spotify’s recommender algorithm that I will later discuss. These algorithms are continuously redesigned to meet the specific needs of the people that use them to generate profit, so that they facilitate “control, accumulation and ‘augmentation of surplus value’“ (ibid:15). Pasquinelli suggests that,

If Simondon recognized already the industrial machine as an info-mechanical relay between flows of energy and information, a further bifurcation of the machinic phylum should be proposed to recognize the information machine as a meta-informational relay whose algorithms handle both flows of information and metadata. Metadata can be logically conceived as the ‘measure’ of information, the computation of its social dimension and its transformation into value.

Metadata is thus the crucial link here between prosumption, exploitation and alienation. It is extracted, abstracted, and processed into new information, generating surplus value.

1.5 Conclusion In this chapter, I have treated various perspectives on activities on the web and what these imply. I have mainly focused on Marxist frameworks, and how these can be related to the web as it is today. Although the project of this thesis is not to engage with this specific vocabulary, these theories are very helpful in understanding the digital economy. People on the web are exploited, but the account of exploitation needs to be updated since exploited activity is also enjoyed. Like exploitation, alienation on the web takes place in different dimensions than in the traditional Marxist sense. A double logic takes place, in which traditional alienation is diminished only to make place for a newer, less conscious type that is, however, inherent to communication on many web platforms. This unconscious alienation will be the starting point for the next chapter, where I will treat some theorizations about the relation between corporate owned media and human subjects.

At this point, I do wish to briefly reflect on some terms for the sake of my argument. Although a lot of literature in new media is concerned with web 2.0, I will avoid using this term in the rest of this thesis. The term inconsistently refers to many different platforms that work in many different ways and have different business models, if these are even present. Some are based on premium models for revenues, while others gather their income from advertising. Some combine these systems and work with a ‘freemium’ model, in which the paying user will get more options, customization and less

13 advertising. There are definitely patterns that can be recognized, but there are just too many different types of websites that overlap and a lot has happened since the term was first coined. The term ‘prosumption’, however, I will use in my argument for pragmatic reasons, although I agree with Van Dijck (2009: 42) this simple term might distract from the complexity of the concept. It is important not to forget that many acts performed on platforms also shape that same platform in unique ways. The feedback loop between the platform and the actor constitute what both the platform and the actor can be. However, there often is a difference between what the prosumer produces and what he or she consumes, and wherever this distinction is relevant I will point this out (for example, Facebook users directly produce and consume the same type of content as well as produce metadata that they do not directly consume). So although I do acknowledge that there is difference between traditional consumption and prosumption, I want to make clear that the paradigm of production, distribution and consumption has by no means been transcended. Rather, I argue that prosumption exists as a connection between production and consumption as well as between different actors and their specific products. In this sense, prosumption should not be seen as an individual act but as an aggregate of collective activities inside a system. This aggregate of activities, however, has different consequences for different parties. Although I do realize that this is not a radical view, it should be pointed out because it is exactly the complexity of the concept that is relevant for my later analysis of Spotify.

14 2. INDIVIDUATION IN THE COMPUTATIONAL INDUSTRIES

2.1 Introduction In this chapter, I will move to a discussion of theories that concern the production, consumption and distribution of cultural products. Besides introducing a different approach to algorithms that can complement what I have written about in the previous chapter, this also allows me to get closer to Spotify as the main object of this thesis. I will begin this chapter by elaborating on Max Horkheimer and Theodor Adorno’s account of the “culture industry” (2002: 94), and where the links and discontinuities are with what David Berry has described as ‘computational industries’ (2014: 25). Next, I will move to Bernard Stiegler’s theory of the “programming industry” (2011: np), which both criticizes and complements Horkheimer and Adorno’s analysis. I will, moreover, discuss Stiegler’s concept of ‘associated- and dissociated milieus’ (2010: 82), and look at how this will prove to be useful for theorizing subjectivity in the digital economy. This account will then serve as the main theoretical framework through which I will analyse Spotify’s material dimensions in chapter 3.

2.2 Pseudo-Individuation in the Culture Industry In the chapter ‘The Culture Industry: Enlightenment as Mass Deception” of their book Dialectics of Enlightenment, which first appeared in 1944, Horkheimer and Adorno (2002) introduce the notion of the culture industry to describe that cultural production and distribution have come to be industrial processes. For them, the culture industry impresses “the same stamp on everything” (ibid: 94). They argue that monopolies rule mainstream culture, because large corporations carefully plan the construction of cultural artefacts, which include architecture, but also movies and television. They write that all mass culture is the same in this situation, and its creators do not even pretend that it is art anymore. As the creative industries today do, people identified their fields of work as industrial already then. Like Marx, they notice that this organizational structure has large implications for the subject, because those who have the economic means acquire power over society with technology. This is apparent, for example, in radio. Whereas communication over the telephone enables two parties to equally participate in a conversation, radio “democratically makes everyone equally into listeners, in order to expose them in

15 authoritarian fashion to the same programs put out by different stations” (ibid: 95-96). In this system, Horkheimer and Adorno argue, private broadcasters are denied freedom and have to work by the rules that have been imposed on them from above. Talent gets scouted by professionals and absorbed by the industry, with which all spontaneity is removed. So Horkheimer and Adorno’s analysis of the culture industry leads them to conclude that it is organized in a top-down structure in which people are subjected to ruling monopolies. In various respects, this differs greatly from the way in which the creative industries on the web are organized. Algorithmic recommendation devices have replaced much of the careful planning of artefacts that is done by humans. Besides, the web is a space where communication heads in multiple directions instead of only top down. Recommender algorithms are set up to be a feedback loop between people and technology, distributing content by a logic that does not categorize groups of people, but targets individual users. Furthermore, actual content production and distribution are now for everybody; the technological means to make artefacts such as music, videos and blogs are affordable to most people, and everyone that is connected to the web has various options to choose from regarding the distribution of their duplicable creations. However, there is more to Horkheimer and Adorno’s analysis. According to them, the top down structure that they write about leads to a society in which people are ‘pseudo-individuated’ (ibid: 125). In industrial production, both procedures and goods are often standardized to maximize efficiency. The interchangeability of parts lowers production costs, since it is cheaper to produce one kind of tire that fits three cars, than design and produce three separate types of tire. However, Horkheimer and Adorno argue, this greater efficiency also lead to homogeneity in the end products that are sold. Many goods are largely identical, but carry different price tags. This is illustrated, for example, by the Chrysler range and General Motors products being basically the same (ibid: 97). The products that are produced by the industry are categorized into different classes. The distinctions between goods are made very clear, so every consumer can choose which type of product he or she wishes to engage with. The part-interchangeability is hidden here, and individuality made clear. However, Horkheimer and Adorno argue, this individuality is not real because everyone gets the same product in a different package anyway. Adorno argues elsewhere that this also happens in popular music, where the structure of every pop song is the same, so that the trained listener will know when the chorus begins in advance, and the beginning and end follow simple harmonic schemes. Songs must become pre-digested to ensure that consumers do not have to struggle with them. But novelty is suggested with every new

16 hit song by introducing new hooks that are carefully worked out by professionals. The part interchangeability that facilitates this, however, has to remain hidden for this illusion of novelty to be sustained (Adorno 1941: np, Gendron 1986: 23). However, while the production of music could be seen as an analogy to the production of cars, there are certain differences in their production processes that are worth mentioning. Bernard Gendron (1986: 28) argues that typical industrial production involves a Fordist assembly line in the process, while for music, this assembly line is only present in the production of carriers on which music is distributed, such as a vinyl discs or CDs. He writes that an original text, whether spoken or written, is not something that lends itself to be mass-produced. Recordings of songs are written texts in this context, and the assembly line metaphor can only be used for the duplication of material carriers of these songs. In industrial production, part- interchangeability is used because standardization makes production efficient. In music, however, this efficiency is reached only in the stage of distribution of copies of a song, a time at which the song has already been made. The production of this song itself does not involve an assembly line, so for Gendron, the concept of standardization for greater efficiency makes no sense here.

Figure 1. Loopmasters website with options for sounds in different genres. Loopmasters. Web. 9 Nov. 2014

What Gendron did not foresee was that some decades later, interchangeable parts of music are actually being sold in the form of sample banks and software presets, often pre-formatted to different genres to prevent producers from spending too much time looking for the exact right part that will fit their needs (see figure 1). It is no surprise that large corporations such as Loopmasters and Native Instruments orchestrate this

17 efficiency in music production. The parts are exchangeable to such an extent that it has been made explicit. While it could be argued that the ability to make music outside of expensive professional studios is empowering, selling sounds as parts also allows such corporations to explicitly push and re-articulate categorizations in a top down structure. This calls to mind Horkheimer and Adorno’s pseudo-individuation, but in this context choices about consumption are also about production. Computer musicians can buy pre- recorded sounds such as drum hits, piano chords and vocals. These parts are professionally made by recording and mixing engineers to potentially be used in many different songs. They can be browsed in music software, and the musician can make his own composition of fabricated, mass-distributed interchangeable parts. Traditional studio music production would have also involved musicians and engineers, but these would work towards an end product instead of an interchangeable part. In this sense, music software becomes a digital assembly line that uses duplicates of original recordings to save time and money. However, the mode of production is unlike the Fordist since the assembler does not repeat the same task over and over again. He or she makes choices about which interchangeable parts fit best. So whereas Gendron rightly notices that traditional studio music production does not follow an assembly line logic, these techniques are now indeed sometimes used to make music production efficient, but in radically different ways because individuals take care of the composition. The material dimensions of digital music also imply different possibilities for distribution. In a digital domain such as the web, original texts can be reproduced till infinity at only the cost of disc space and the network that people are already connected to. So one relevant question that comes to mind is how distribution through streaming media is related to the assembly line metaphore. Streaming media serve end products; recorded, processed and compressed in music software, written on the server of platforms like YouTube, Soundcloud and Spotify, and ready for people to consume. However, the material dimension of distribution here lies in the connection between the server and the machines that request the information that will be played back as music. Files are only distributed when an actual request is made, and the only carrier that serves the sole purpose of transporting this specific package of information is written in code. While the assembly line in the production of music is to a certain extent more present then ever, it has started to fade away in distribution. This assembly line then makes place for a new artefact: metadata that is used for profiling users as consumers for third parties as well as capturing attention on the platform. For Horkheimer and Adorno, monitoring of popularity also happens in the

18 culture industry. Both part-interchangeability and market research signify that cultural products can be seen as quantified goods. While the former lowers production costs, the latter makes it easier to categorize products and target consumers. Artworks are succumbed to the instance of their economic value, which turns them into fetishized commodities of which the production has to be efficient, and how they are perceived becomes a quantified statistic. Horkheimer and Adorno write that the industry designates this system as necessary because identical goods need to be distributed to an unlimited amount of consumption points. According to producers, the consumers would happily embrace this without struggle, since it already was their own wish anyway. Adorno and Horkheimer disagree, stating that the attitude of the public is part of the system rather than an excuse for it (Horkheimer & Adorno 2002: 96). Like alienation for Marx, this pseudo-individuation can be seen as state of the people under capitalism, although the former directly addresses factory workers while the subjects of the latter are consumers. Control is key here, and the few set out the rules for the many. On the web, this control exists in protocols, or “conventional rules that govern the set of possible behaviour patterns within a heterogeneous network” (Galloway 2004: 83). This standardization of formats allows different types of software and languages to communicate with one another by encoding and decoding packets of information so that they can be properly transported. On the one hand, protocols are necessary for the network to function properly, but on the other hand this implies certain power relations that are backgrounded so that the rhetoric of web platforms can remain empowering and democratic. Whereas the culture industry’s control over distribution was largely centralized, Galloway argues that “protocol is how technological control exists under decentralization” (ibid). However, recent accounts of large web platforms show that power is often also centrally organized again. As these “walled gardens” (Berners-Lee 2010: 82) grow large enough it gets harder for others to compete, and since their walls are also written in protocol, it could now be argued that this is where control still exists after re-centralization.

So although the relation between media and people has changed a lot, the abstraction of the production process shows similarities with the way flows of information are abstracted in software in general, and web platforms in particular. In both the culture industry and the computational industry, the end product that the customer gets served is the result of a machine of which the workings are intentionally made cloudy. Where standardization - of material parts and production processes - and market research

19 accounted for this in the culture industry, abstracted protocols and metadata characterize the computational industry. Because Horkheimer and Adorno extracted their theory of pseudo-individuation from their analysis of the culture industry, and the computational industry has a different economy, I will move beyond this concept. However, although the process of individuation through the consumption of cultural products has changed, it remains relevant for the analysis that follows. In the next section, I will turn to a more detailed account of individuation by introducing Bernard Stiegler’s work and the accompanying vocabulary.

2.3 Recording of Traces: Association Whereas Horkheimer and Adorno were mainly concerned with how the culture industry imposes products from above, a framework in which the relation between the human subject and technology is emphasized more offers a different perspective. One of such theories can be found in Stiegler’s work, who criticizes the analysis of Horkheimer and Adorno because for him, the culture industry requires a critique of Kantianism, so using Kantian schematism to analyse it is not apt (2011: np). For Kant, the schema is a category of the mind that comes prior to external images. Stiegler, however, argues that if it is necessary to make a distinction between schema and images, it should also be noted that these two concepts could only exist in relation to one another. The mind is always penetrated by external images. This originary technicity means that humans are the product of technology as well as the other way around, so for Stiegler there has always been a relation between humans and technology and what constitutes us a human beings is our relation to that technology (Lechte 2012: 80, Stiegler 2011: 42, Verbeek 2008: 388). This also helps to address the condition of subjectivity in a different way than I have done before. The Marxist framework allows for a theory in which technology facilitates the alienation of humans from their labour. But like the Kantian schema, the theory of alienation arguably assumes the existence of an authentic subject prior to relations with technology. By reframing both alienation and pseudo- individuation as dissociation using Stiegler’s work allows me to focus more on the composition of human and non-human elements that interact with each other.

Although their method was invalid to Stiegler, in his 2004 essay ‘Suffocated Desire, or How the Cultural Industry Destroys the Individual’, he also writes that Horkheimer and Adorno were right about that culture industry’s “aim is to ensure the flow of new

20 products ceaselessly generated by economic activity, for which consumers don’t feel a spontaneous need” (2011: np). For Stiegler, it is apparent that the promise of a post- industrial society was false, and a hyper-industrial society has formed. This society is characterized not by great individuality, but on the contrary, by mass behaviour, the loss of individuation and the industrialization of memory. Cultural industries, and in particular radio and television since these are programmed, introduced “industrial temporal objects” (Stiegler 2011: np), which means that they are constituted by the time of their passing. These cultural objects, based on the programming of time, allow for the transformation of individual behaviour into mass behaviour, while it can still be experienced as individual. Television, for example, allows for viewers to watch in a private situation in which they can choose what channel to watch. However, these programmes are still made for mass distribution, and are broadcast at given times, or as Stiegler (ibid) has put it: “alone in front of my television I can always say to myself that I behave individually, but the reality is that I do exactly as the hundreds of thousands of television viewers watching the same program.” In this way, current forms of leisure time should not at all be seen as ‘free time’, since they are designed to hypermassify and control behaviour. Programming industries produce and show objects that appear and disappear at given times, and this time flow is controlled by the industries in such a way that they “coincide in the time of their passing with the time flow of the consciousnesses of which they are the objects” (ibid). According to Stiegler, this means that the consciousness of people starts to adopt the time of the temporal objects it sees. However, for Stiegler, what makes one able to speak of an ‘I’, is that an ‘I’ can give the self its own time and is self conscious. So the programming industries eliminate this self by synchronizing consciousnesses through the presentation of temporal objects. This synchronizing has great implications for how people appropriate pre- individual funds. Stiegler, whose idea about this was influenced by Gilbert Simondon, writes that pre-individual funds can be seen as “heritage of the accumulated experience of previous generations” (ibid). The individual never stops becoming what he or she is, and singular participation in appropriating heritage that is commonly available to a group is what makes him or her an individual within it. So, the appropriation of heritage by each singular member of a group is what makes individuation possible. Individuation, in this way, is only possible collectively, a conception that stands against the post-industrial idea that the individual and the group are binary opposed. Programmed television and radio, however, invert this process by synchronizing the

21 time at which pre-individual funds are appropriated, making sure that people’s pasts become the same. On the web, temporal objects are organized in radically different ways. Stiegler’s programmed industries synchronize people’s schemes, but it is exactly the desynchronizing of temporality through an individual-based approach that characterizes recommender algorithms. Synchronizing, however, remains present in terms of content selection on the web. Whereas the time of consumption becomes less relevant, the actual messages remain important. Social network sites like Facebook ensure that stories that prove to be popular appear in more content streams, which means that a personalized environment can still contain synchronization. Besides, Facebook allows fan page owners to promote their posts, and select how many people their message should reach. The more money one is willing to spend on this, the wider the reach, and the greater the synchronization. Spotify will recommend new songs based on metadata, and the more data Spotify has gathered about a song, the more refined the recommendation will be. Here, synchronization takes place at the level of an algorithm that decides what content to suggest because others have also listened to it. The synchronized appropriation of pre-individual funds on these platforms is not planned and orchestrated in a top down structure, yet it is controlled through the technological infrastructure that interacts with its users immanently. On the web, the time flow of regulated television consumption patterns is arranged so that virtually every moment has the potential of capturing people’s attention.

One good framework to make sense of the interaction between human and non-human elements is Stiegler’s theory about experience and memory that can be divided into different degrees of retention. Primary retentions exist in the conscious experience, or the selection that the consciousness makes and experiences. Secondary retentions exist in the selection that the consciousness actually memorizes, so these filter the primary retentions. Tertiary retentions exist when memory leaves the brain and is stored with the help of tools, which can be seen as the “recording of traces” (ibid). Tools such as the alphabet are found in every civilization, and when individual experiences become recorded traces they enable others to individuate through them. Growing up in an environment with ever evolving technology enables people to extend their memory further and further. When memory extension becomes industrial, however, these tools such as audio-visual media are the technological infrastructure on which the hyper-industrial model of control relies. Elsewhere, Stiegler has argued that whether a receiver can also

22 take the place of the sender determines if there is a dissociated relation between production and consumption or associated interlocution (2010: 82). He writes that mankind has always used tools to help memory, and in fact to make knowledge available for future generations. In this sense, the externalization of memory (or tertiary retentions) helps individuals gain knowledge, and could as such be seen as empowering. The shift from individual ways of externalizing memory to industrially organized and networked forms of external memory, however, implies control over this information. At some point, the external organization of memory will reach beyond what is comprehendible for an individual (ibid: 67). The more complicated this becomes, the less able the individual becomes to control his own externalized memory. This is highly apparent in prosumption and the metadata it produces. Prosumers cannot know what exactly is hidden behind the interface of the web platform that has become a “dissociated milieu” (ibid: 82). Because this information can be used for various purposes such as targeted advertising, this is where dissociation becomes profitable for others. It is striking for Stiegler that the loss of knowledge, which can be experienced as a feeling of powerlessness, takes place at the same time that our external memory is organized in such a way that it seems to be infinite and accessible at all times (ibid: 69). However, he is quite optimistic about the potential of the web, writing that “audiovisual memory can be produced through participative technologies that no longer impose the producer/consumer opposition” (ibid: 83). As such, he sees the age of the internet as “the end of the era of dissociated milieus” (ibid). However, although these new technologies can place receivers in the place of senders, Stiegler does not notice that much of the communication on the web introduces a much more complicated model. The fact that people can communicate through these technologies does not mean that they can communicate with them, let alone fully understand them. For Stiegler, industrialization can be defined as the separation between producers and consumers. Technically mediated messages such as film and television are also received by those who cannot produce them (ibid: 77). However, this also happens on the web: whereas the temporal organisation that once belonged to broadcast media might be contested (or reinvented), many messages are still designed to be consumed by a large public, and are still transmitted through media with which most users do not share a language. Designating the internet as a signifier for the end of dissociated milieus is quite optimistic, since power relations now appear in the form of code, protocols and metadata. Although direct communication between people is possible, the ways in which web platforms work are often much more complicated. As I have argued

23 throughout this thesis, the industrial model has not been replaced by prosumption, but rather has been complemented by it.

2.4 Conclusion In this chapter, I have moved the discussion from labour to consumption. It is clear that media are now organized in different ways than they were in the 20th century, which was largely dominated by top down mass media. Horkheimer and Adorno’s concept of the culture industry, however, remains a relevant concept because there are noticeable similarities in the way old and new media giants deliberately hide the exact functioning of their mechanisms, suggesting individuation through their platforms. Stiegler acknowledges this, but does not agree with their method because their analysis implies an authentic subject that exists outside of technology. For Stiegler, humans and technology constitute each other rather that the latter being a product of the former. Stiegler’s theory of associated and dissociated milieus offers a framework that allows for a close examination of the relation between humans and technology. Although he fails to acknowledge the industrial relations that are highly present on the web, and many platforms should in this respect be seen as dissociated- rather than associated milieus, this framework will prove apt to analyse Spotify. It is this that I will turn to in the next and final chapter: an analysis of the impact of the discursive and material dimensions of Spotify in terms of individuation and dissociation.

24 3. ALGORITHMIC RECOMMENDATION: INDIVIDUATION THROUGH SPOTIFY

3.1 Introduction In this chapter, I will introduce and analyse the case of Spotify, which will help put the previously treated theory in perspective. I will do this in a way that has not yet appeared in other literature; its recommender system and the claims that Spotify makes about it are related to individuation. Although much literature is concerned with online recommender systems, most of this tends to focus solely or primarily on aspects of their technological affordances. Some authors either explain or compare different kinds of recommendation techniques and technologies (Adomavicius & Tuzhilin 2005, Pazzini & Billsus 2007, Lops et. al 2011, Ricci et. al 2011). Others have written about how to improve the algorithms of specific kinds of recommender systems such as content based filtering (Mooney 2000, Tkalcic et. al 2010), collaborative filtering (Herlocker et. al 2000, Linden et. al 2003), or hybrid forms (Salter & Antonopoulos 2006, Burke 2007). Still others have also taken social implications of recommender systems into account, such as privacy concerns (Perik et. al 2004, Resnick & Varian 1997). However, in all of these writings the socio-political context is either absent or backgrounded. One way to address this problem is to analyse recommender systems and how they relate to the process of individuation. As I have shown in the previous chapters, activity on the web can be theorized in terms of labour, production, distribution and consumption. Marxists have written mainly about exploited labour and the alienation of people from their metadata. Although people often engage with web platforms because they like it, they are exploited because they generate surplus value and alienated from their work because part of what they produce is abstracted from them. Horkheimer and Adorno’s culture industry targeted consumers by constantly reinventing products so these could maintain an increasing flow of profit. However, according to them, these products are the same over and over again. These products are made to sell, instead of serving meaningful purposes, and undermine the formation of the subject because they are pre-digested and categorized. That people fail to see this and individuate through the consumption of these products creates pseudo-individuals over which the culture industry has a lot of control. The logic on the web is different in its organizational structure, but represents some of the same essentials; corporations set up controlled networks that target consumers. Stiegler (2011: np) has taken Horkheimer and Adorno’s idea further, mainly focussing on programming industries that create and plan

25 temporal objects, organizing mass-synchronization of behaviour and consumption. For Stiegler, what makes this possible is the way that people externalize their memories and dissociate from them. Stiegler argues that this situation can be overcome in the age of the internet because people have regained the ability to communicate with each other instead of only being able to receive messages. But in the past fifteen years, many scholars have written about the present situation, describing it as a new mode of capitalism. The internet and its communicative characteristics is largely being used to gather and monetize data from users, which would mean that Deleuze’s “society of control” (1992: 4) is now more present than ever. However, although Stiegler’s analysis should have been more critical, his model for individuation and dissociation still remains relevant. Many of the critical works about the web I have mentioned describe how its infrastructure in general works, but none of these have been specifically about recommender systems. In the various theorizations of the culture- and programmed industry, exploitation and alienation seem to remain largely about the similarities between various media platforms, their connections, and the political economy this creates. I acknowledge the importance of these abstractions, but focussing on one specific property and its relation to the whole allows for a more detailed account of individuation in a specific instance. As personalized targeting of both content and commercials lies at the core of the web’s contemporary logic, researching how people individuate through these mechanisms is now more relevant then ever. In addition, music consumption as an engagement with cultural material and collective memory plays a central role in the formation of the subject. It is for these two reasons that I will turn to an analysis of a music platform on which a recommender system plays a central role: Spotify. Of the many online music platforms that have been launched in the past decade, Spotify has arguably caught the most media attention. This should be no surprise; the music streaming service now has a user base of 40 million, of which 10 million are paying subscribers. Globally, over 20 million songs have been licenced. Which songs exactly can be accessed depends on which of the 56 operational countries the user is in. Apart from its popularity, Spotify is an interesting object because it has several different mechanisms that have unique implications for how music reaches people. Algorithmic recommendation plays an important part, so relating Spotify to the theoretical framework on originary technicity and individuation discussed in earlier chapters is highly relevant. This chapter proceeds through an analysis of the discursive dimensions of Spotify – what the company claims to be – and a medium-specific account of the

26 platform, or how it technically operates. The discussion will then turn to some influential critiques of Spotify in order to theorize the capture of user activity and the political economy of royalty fees.

3.2 Beats in Bits Before analysing Spotify, I will briefly introduce the topic of online music distribution. As Spotify is a catalogue of music as well as a radio service, the recent histories of both digital music catalogues and online radio stations deserve attention here. These histories are not meant to be a complete overview; rather, they are an introduction to digital music and the milieus that surround it. Since the beginning of recording music, technologies for both capturing sounds and producing new ones have undergone many changes. An example of the former can be seen in microphones, amplifiers and recording units that have become sophisticated to the extent that recorded sound can quite accurately reflect the original sound source. Examples of the latter can be found in the introduction and development of electroacoustic instruments such as electric guitars and –pianos, synthesizers and drum computers, as opposed to traditional acoustic instruments. More recently, the possibility for creating music with software – often referred to as ‘in the box’ music production – has made the distinction between sound source and recording device less relevant. Especially this software has paved the way for hobbyists that are now able to produce complete works of music, functioning both as one-man band and audio engineer. Although this does not mean that trained professionals have become redundant, it is possible to record and finish songs without the use of a studio. But even music that is produced in professional studios is often directly recorded to– or stored in digital format. The recording of sound, however, is not only about faithful reproduction of original sound source, but also largely about portability and thus the possibility “to move the recording across space” (Sterne 2006: 837). For digital formats, this movement – or distribution – differs greatly from the way analogue media are multiplied and relocated. Whereas vinyl and tape require more material for each copy, digital files can be copied more precisely and infinitely, but also transferred without extra costs apart from the disk space it takes and the necessary networks. This cost- efficient distribution system has the potential to benefit music retailers, but the rise of the digital file format has also increased concerns about piracy in the past decades. While Napster now offers a legal form of online music consumption, it was once a

27 peer2peer file sharing system through which many copyrighted works were shared for free. Even when buying music online was not yet common, software to ‘rip’ CDs enabled people to transfer their music collections from physical forms to files on hard drives, which also allowed for duplication without the use of extra material. Originating in 1999, Napster’s software allowed users to download music from other users’ hard disks, and by this made it possible to own large portions of digital audio files without paying for it. After several lawsuits, the service eventually shut down in 2002. This would by no means be the end of peer2peer piracy, since similar services such as Gnutella and KaZaa were initiated in the same period (Fagin et. al 2002: 459). Over the past decade, on the other hand, various online stores have enabled customers to legally buy digital files that can be downloaded. While iTunes is arguably the most well-known platform to facilitate this, digital music files can also be bought in stores that do not only exclusively sell music such as Amazon, or stores that specialize in specific kinds of music such as the dance-oriented Beatport. Whether bought or illegally downloaded, the transportation of these digital files still has to deal with physical constrains. As I have mentioned before, numbers of copies of digital files can be infinite. Disk space, however, is finite, and so is bandwidth. Large files will take more time to transfer then small ones. Increasing the bandwidth of a network is one solution to that problem, but decreasing the size of files is another. The application of the latter on digital files can be traced back to before file sharing networks and online music stores existed. In 1988, the Motion Picture Experts Group was formed in order to standardize compression so that media could be freely transferred across different digital technologies (Sterne 2006: 828). In 1997, Microsoft’s Windows Media Player started supporting their format for sound, the MP3 (Ewing). Although other compression formats exist, the MP3 is a format that is still widely used today. Various services such as iTunes have made efforts to prevent their files from being pirated by coding files so that they cannot be used across different platforms. However, illegally downloading files that can all be played the same software is much less inconvenient than having to move between different programmes to play music that you have paid for (Sterne 2006: 829-830). Besides, the compatibility among different platforms is one of the central characteristics that made the MP3 appealing in the first place. In essence, the coding of MP3s works by algorithmically filtering out parts of uncompressed audio files that will be less clear to human hearing anyway, which leads Jonathan Sterne to see MP3s as “a celebration of the limits of auditory perception” (ibid). High rates of compression can decrease the size of files drastically, but inevitably also remove more sound. The extent to which an MP3 is compressed is expressed in

28 kbps, which stands for kilobit per second of sound. On the one hand, that MP3s do no sound like their uncompressed predecessor is a great deal of compromise. On the other, however, Sterne argues that MP3s are designed to listen to in places where sound quality is less relevant. In offices with computer fans, noisy streets or through cheap playback systems, people can hardly tell the difference (ibid: 835). Sterne further states that this algorithmic decision making of what information is relevant and what is not puts people in a sonic austerity program; the codec decides what people need to hear (ibid: 838). Because the rates of compression are adjustable, however, the extent to which MP3s are sparing with information is flexible, and humans remain part of the decision making process. The result of the combination of decisions of both the human and the codec – the MP3 file that contains musical information - should then be seen as a balanced consideration between audio quality and quantifiable portability. What is also interesting about the MP3 as an entity that can be owned is that it creates different milieus that can be related to different stages of their distribution process. Although there are many different scenarios in which MP3s can originate and travel in various ways and combinations, one typical situation is where MP3s shift from dissociated to associated milieus. Professionally produced music is converted to a standardized digital format and sold by large corporations. Whether the sale is made on CDs or in MP3 stores, it often happens in dissociated milieus. In this system, communication in the form of music flows in one direction from one point to many; the only thing that flows back is money and information about the purchase from many points to one. However, because these digital files lend themselves to be transferred so well, they enter associated milieus at large scale. Peer2peer software directly connects people in such a way that what they give and take is the same type of information, and in this way, associated milieus arise around the MP3. An industrially distributed pool of pre-individual funds transforms into a social system in which people can individuate through a network of file-sharers. Digital music that can be owned can also be controlled in terms of arrangement through playback software such as Winamp and iTunes, which makes curating much easier that it was when people had to record mix tapes or burn CDs. Furthermore, because there is no promotion in these systems, it leaves room for desire to come from within, instead of being imposed from outside trough advertisement. Whereas this is liberatory to a certain extent, however, it is also problematic in that the actual content that is freely distributed finds its origins outside of that system. Although music can be made in an attic or basement, it will often require much time, and indeed, money. Before something can be shared, it must be created first, and music is

29 often not created in file-sharing networks. A system that is purely based on circulation is thus not sustainable; the music has to originate somewhere. In the case of peer2peer file-sharing networks, the associated and dissociated milieus are related to each other, with the former being dependant on the latter. While systems that exist because of digitization and compression can create situations in which the appropriation of cultural heritage happens unsynchronized, these systems rely on building blocks from external milieus. The question also arises how the reduction of audio quality can be related to association, since the creation of an associated milieu in this instance is largely dependent on a file format that influences how much information can be embodied. More bandwidth is one obvious answer to that problem, but that also means that people with more expensive connections – more heavily invested individuals – do better in that milieu. So the system of legal purchases combined with the free distribution of both copyrighted and non-licenced works creates a milieu that can neither be fully called associated nor dissociated, since there are properties of both.

One other account in which people can engage with music differently can be found in online radio stations. While analogue methods for streaming music dominated the twentieth century, relatively small files and large bandwidth now also allow music to be played directly from internet servers at a large scale. Whereas the technology for playback has evolved from analogue to digital, the method for music selection has in some instances shifted from a ‘professional curator’ approach to a ‘human and algorithm’ approach. In the former, music is selected and arranged by DJs. Other then choosing between different radio stations, curating is left to others, whether it be for their expertise or just for convenience. In this system, pre-individual funds are appropriated in a mass-synchronized way that is often industrially programmed. However, although traditional radio stations still exist, recent developments have given rise to a new kind of radio in which recommendation is done algorithmically rather than by humans. This allows for radio streams that are personalized, which changes the mode in which funds are appropriated. Pandora is an example of a service in which people can create radio stations that are based on the preferences of the listener (“Pandora”). After the listener enters an artist name as a starting point, Pandora’s algorithm creates a stream of music that is related to that artist. After that, the listener can improve the station by giving the algorithm feedback about the music that it suggests (Stockment 2009: 2133). These suggestions, however, are based on classifications that Pandora employees have attached to songs, which makes the database of music a taxonomy (Haupt 2009: 23). The synchronization of the

30 consumption of temporal objects that is typical for the loss of individuation in the programmed industries model remains largely absent here. However, the milieu in which music is listened to is only associated to the extent that the algorithm responds to explicit feedback. The selection of music is delegated to a machine that works according to classification resources to which the Pandora user has no access. Another online radio station, Last.fm, has taken a different approach to classifying musical content (“Last.fm”). In its folksonomy, songs are categorized according to the tags that users have given them. These tags then function to group music; radio stations can be created to play everything with the tag ‘rock’, but since the classification has few restrictions, a station based on ‘baguette’ could also very well exist. Furthermore, it responds to “implicit feedback” (Oard and Kim 1998: 81) through its ‘Scrobbler’ software that registers what music is played on a computer and how often, even when not using Last.fm. It then compares this listening behaviour to that of other Last.fm users, and makes recommendations that are not based on the actual music, but on what others also liked (Haupt 2009: 24). Individuation is done here in a milieu that has a relatively large associated dimension. Recommendations are done by an algorithm, but are based on tags and listening behaviour of people that all hold the same type of position in the network. Much more could be discussed about any of the platforms mentioned in this section, but that would go beyond my scope. What is important for the argument of this thesis is that they have all contributed to the discourse of online music consumption in different ways. On the one hand, digital audio files can be seen as loose entities that can be sold, transferred and owned, which makes them singular objects that are accessible at all times. On the other hand, online radio gave rise to different methods for recommending and distributing music that cannot be selected from a catalogue but rather depends on selection algorithms. Both of these forms remain largely present today. However, the distinction between the catalogue and the radio stream is one that Spotify aims to overcome, which makes it particularly interesting to analyse this specific platform more extensively.

3.3 Soundtracking Your Life

In the next two sections, I will analyse Spotify by treating it as an “assemblage” (Wise 2011: 81), because this enables me to address the “complexity of human-technology relationships” (ibid) for this specific instance. Since assemblages are “not just things,

31 Figure 2. Spotify's homepage Spotify. Web. 8 Nov. 2014 practices and signs articulated into a formation, but also qualities, affects, speeds and densities…” and “…work through flows of agency rather than specific practices of power” (ibid), this way of addressing Spotify allows me to connect the discursive and technological dimensions to the theorization of individuation. In doing so, I will first take into account the claims that Spotify makes about itself by looking at the website’s contents, which reveal how Spotify ‘sells’ itself prior to its use. These claims will then be connected to how Spotify’s application is set up, what flows of information and feedback are created by the machine and its users, and how this self proclaimed soundtracking of your life (“About Us”) relates to modes of individuation.

Spotify is a platform of which both the home computer and mobile device versions operate through a web player or an application that must be downloaded. For the home computer version, the story of Spotify begins on its website, www.spotify.com. The mobile application can be downloaded from Google’s Play store for Android or Apple’s App store for iPhone. What follows below is directly derived from the website, but the same claims can be found in the information sections of the mobile apps. As can be seen in figure 2, the first grand claims that the platform makes on the website are clear: Spotify is for everyone, and it has the right music everywhere. That Spotify is for everyone is a claim in which certain tensions arise; obviously, Spotify is not used by every artist or label. Still on the homepage of the website, the next notable claim is that “all your music is here. Spotify gives you millions of songs at your fingertips. The artists you love, the latest hits, and new discoveries just for you. Hit play to stream anything you like”. Here, they emphasize that what you already like will be there in addition to many things you will like and do not know yet. However, although their database is large, Spotify knows that it does not nearly contain all the music in the

32 world. Whether it is music that small independent labels decide only to release on vinyl, or others that publicly take a stand against Spotify and reject it as a medium for the distribution of his music, there is simply a lot happening outside the domain of Spotify. From a media specific perspective, moreover, certain complications arise in the universal appeal to which Spotify aspires. Even when its interface and database are not taken into consideration, Spotify can be seen as a specific kind of transmitter of music since it works with compressed digital audio files. The format that is used is Ogg Vorbis (“What Bitrate”), which uses a variable bitrate so that files can keep more of their sonic quality than MP3s that are compressed to the same file size (“What is Ogg Vorbis?”). As opposed to lossless compression formats such as FLAC, Ogg Vorbis is a ‘lossy’ one, which means that it discards information that cannot be regained. Ogg Vorbis files that are streamed through web applications can be a medium of preference, or some people might say that they do not care about the medium and audio quality too much. But there are also people that would rather listen to other carriers such as vinyl, CDs, cassettes, uncompressed digital audio files and so on. So listening to music on Spotify also means accepting the audio aesthetics that it offers. Some people refuse this, with the debate varying from vinyl purists (Aguilar) to CD fanatics (Stead). The point being here is that how people like to consume their music is medium-specific. Many people do not accept the aesthetics of streamed compressed files, so in this materially mediated sense, Spotify is not for everyone at all. Nevertheless, these slogans and statements from Spotify also suggest important characteristics of the platform as a streaming-service. As discussed in the previous section, compressed audio formats mainly serve the purpose of distribution, and like MP3s, Ogg Vorbis files have flexible compression rates. Spotify uses this flexibility to stream music in different qualities for different situations and types of subscription. The desktop and web-player versions standardly stream at 160kbps, while the desktop version allows premium subscribed users to stream audio at 320kbps. The mobile version’s default mode is 96kbps, and can be upgraded to 160- or 320kbps. Although mobile data traffic develops quickly (Mahanti & Sen 2014: 8), today it still makes sense to stream audio at lower bitrates for mobile internet connections. By making the distinction between devices, Spotify aims to distribute music to as many places as possible, and fulfil the promise of it being everywhere. Furthermore, although Spotify does not contain all the music in the world, the 20 million songs that it contains are much more than anyone could ever listen to, and odds are that there will be something for most people’s liking. Besides, the twenty thousand songs that are added every day (“Information”) are an indicator for Spotify’s aim to

33 handle rapid expansion. As such, by being flexible enough to increase in size and accessibility, their aim for being for everyone can also be seen in terms of network effects. As Spotify grows as a network, it also becomes more valuable to its users because there is more music to be found and there are more people contributing information. This growth solidifies Spotify’s position in relation to other platforms. In this sense, being for everyone also signifies a movement towards monopolizing streamed music. However, although the application and database function as both a catalogue and personalized radio stream, using only Spotify for music consumption offers a fixed playground for individuation. Spotify is everywhere and for everybody because of the distribution of music that is possible thanks to compression, which calls to mind what also happens in peer2peer networks. Sterne has argued that for reasons of portability and storability, the best attitude towards compressed audio might be an ambivalent one, and that “given the infrequency with which people are in a position to have the ‘full’ sonic experience of recorded music, perhaps the trade-off is worth it in some cases” (2006: 838). However, this trade-off is made for every case in Spotify. This is not to say that the overall quality of Spotify is not sufficient; that is a matter of aesthetic judgement that is none of my concern here. However, the audio quality in Spotify does have its limits. Given that it aims to be everywhere, it actively promotes distribution of only compressed files, but from a centralized, expansive and, therefore, profitable perspective. While the trade-off in peer2peer technologies can be seen as one in which the loss of aesthetic quality benefits associated individuation, Spotify compensates the compression of information with the ability to stay connected to an industrially managed pool of pre-individual funds, wherever you are. Moreover, although a premium account allows people to make songs temporarily available offline (“Listen Offline”), the music cannot be owned. Streaming services with corporate gatekeepers offer people different relations to music than systems in which individuals can own songs. The streamed audio file in Spotify becomes a temporal object of which the temporal programming is not regulated, but can only be accessed through the platform so long as it has not been removed. So by claiming that it is for everybody, Spotify offers a singular vision on how people can individuate through their music consumption, in which the problem of reduced connectivity is solved by compressed information. However, deciding not to use Spotify as a medium for music is also an act through which subjects can individuate. Spotify’s claim means that it aims for being the standard platform in the music industry. What is presented here is a large music database of free music for everybody, but what is actually offered is a

34 synchronized method for the appropriation of pre-individual funds in which tertiary retentions are corporate controlled. Controlling these extensions of human memory is essential for automated search mechanisms like Spotify because their aim is not only to represent information, but also to deal with the problem of how to allocate this (Rieder 2013: 67). For Spotify, this evaluation that is related to aggregated information from users is crucial to present music in a way that makes sense out of its millions of songs. Because there is much more music then can ever be heard by an individual, attention is more scarce then the music itself. Bernard Rieder argues that where algorithmic search mechanisms have replaced traditional institutions such as families, schools and libraries, the logic according to which this happens resembles that of an economy of supply and demand. In this system, the price is set according to the relation between the product and how it is valued through different variables such as ratings and how many times people link to it. The mechanisms used for making popular products visible are similar to pricing signals that are found in traditional market systems (ibid). Whereas a market in which more readily available goods cost less money, the least scarce songs require less attention and knowledge to find on Spotify. As a result, music that has gotten less attention before will be less likely to appear in search results, so costs more investment to find. Like in a supermarket, there will be something for everybody in terms of what they can afford, but the visibility of products is far from equally distributed. By offering a “value choice that implies winners and losers” (ibid: 68), Spotify can be for everyone but does not necessarily provide the best system to all.

As for the actual music that is heard, different uses of Spotify lead to different modes of synchronization. Although there is a ‘search’ function, the front page of the application (figure 3) shows that there is a strong focus on exploration methods that work through suggestion, such as ‘Top Lists’, ‘Genres & Moods’, ‘New Releases’ and ‘Discover’. ‘Top Lists’ presents lists that are similar to traditional hit parades. They are categorized according to genres such as ‘pop’ and ‘country’, but also according to spatial and temporal categories such as ‘top tracks in the Netherlands’ and ‘today’s top hits’. ‘Genres & Moods’ also categorizes tracks, but does so in terms of the atmosphere that the music sets, such as ‘party’ or ‘romance’ or ‘workout’. Clicking on one of the genres leads to the next menu in which various popular playlists are presented, some of which are created by Spotify, others by brands such as Nike, and still others by individual users. ‘New Releases’ is a section in which new albums and singles can be listened to. This section clearly takes geographical location into account, since there were various Dutch releases

35 Figure 3. Spotify's Desktop App Front Page presented to me. While these methods for exploration of music vary in their organisation, they have in common that are not personalized. While users have the ability to create their own playlists, synchronized selections of songs in terms of categorizing and arrangement are foregrounded. Furthermore, by focussing on exploration through charts, a lot of emphasis is put on what is already popular. A different method for exploration can be found in the ‘Discover’ section. In this function in the application, part of the content is suggested as ‘give it a try’, while the rest is selected by algorithmic recommendation. Spotify’s algorithm for content selection is based on a collaborative filtering approach that uses a combination of editorial tagging and audio analysis for the classification of songs, and metadata for recommendation. This metadata is entered into a matrix with 40 different variables, which then looks for patterns so that users can be compared to each other (Bern). The results of this are statistics such as can be seen in figure 4.

Whereas the previously mentioned uses of Spotify function mostly as a catalogue with navigation tools, another part of the service where algorithmic recommendation plays an important role is Spotify Radio (see figure 5). Spotify Radio uses an artist name that is entered by the listener as a starting point, and continuously plays new songs that are selected by the recommendation algorithm. The radio station learns during this process; when the user gives explicit feedback in the form of a ‘thumbs up or down’, the algorithm learns about the musical taste of the listener to improve its output. However, the privacy policy of Spotify states that information about every use of the service can be

36 Figure 4. Example of the outcome of algorithmic comparison on Spotify. Erik Bern. “Music Discovery at Spotify.” LinkedIn Slideshare. 11 Apr. 2014. Web. 13 Nov. 2014.

captured in order to improve user experience (“Spotify Privacy Policy”), so implicit feedback such as how often tracks are skipped can also be used to ‘get to know’ the user. Where this system of recommendations differs from traditional models of programming industries is the lack of concrete temporal organization. Whereas media like television and radio synchronize in terms of what specific time programmes are watched and listened to, Spotify has its content available every hour of the day. This provides increased autonomy in a sense; people can make their own selection and do not have to play by the programming rules of media channels. However, people do engage with Spotify especially at times when they are not likely to be occupied by work. When music and technology blogger Paul Lamere analysed a large dataset of skipping behaviour on Spotify (Lamere), one of his main conclusions was that most of the skipping happens during mornings, evenings and weekends. So although no particular temporal planning is done by Spotify, it does succeed in capturing attention especially at times that people are ‘free’. Another finding was that people tend to skip more on mobile phones. Only the paid version of Spotify offers unlimited skips, so reducing the skipping option to six times per hour is used to get people to register for a premium account. His analysis further showed that total songs played on Spotify reveals a different curve; during the day, Spotify is used a lot but captures less attention in terms of skipping. While skipping is a form of measurable attention, it is also an account of changing flows of agency between human and technology. In the future, these flows may

37 Figure 5. Radio station in the app based on Herbie Hancock work quite differently. Whereas Spotify now still needs human input in which the computer or mobile device must be actively controlled, it has already started thinking about other mechanisms that can register different kinds of information. Mobile phones could contain sensors for both speed and temperature to estimate if people are jogging or driving, but also heart rate sensors to check if they are tense (Smith). However, while skipping requires conscious attention, the sensors that Spotify’s staff speculates about are designed to keep people attended with soundtracks of their lives, while the interface becomes less visible. This also raises questions about what to do when multiple people are in a room together, all of which have their own heart rate and temperature. The answer to this question could be that Spotify is mainly for individual use. On the other hand, Spotify presents itself as a social platform. In this economy of attention scarcity (Goldhaber 1997: np, Dimaggio et. al 2001: 313), it is important for platforms that attention is spent on their platform instead of others. Spotify’s claim that it is social because people can share content on other social media like Facebook and Twitter can be seen in this respect. While sharing content does widen the social sphere in which it circulates, and this opens up the possibility to enjoy music together and discuss this, it also draws attention by rearticulating the platform. To enhance this, Spotify has a web API so that a player can be integrated into other websites (“Web API”). Furthermore, the deep integration Spotify has with Facebook (“6 Ways”) also has a

38 “desocialized” (Stiegler 2010: 82) dimension because associated communication between people is accompanied by dissociated externalization of information. This desocialized socialization also happens within the prosumptive sphere of the platform. The use of Spotify fluctuates in various qualities between actively engaging with and just staying connected to the platform. Spending more time doing the former benefits the latter, which again increases the odds that the user remains with the service. In this sense, while people consume music on their personalized radio stations, they also co-produce the output for themselves, but also others. Consumption is done individually here, since the stream is personalized. Prosumption, however, is done collectively since the algorithm needs data from other users as well to function. Although this is a clear instance in which individuals and collectives complement each other, a transmitter – the algorithm – functions as a mechanism that constitutes an associated milieu for individuals, but also information about them from which they are dissociated. In this account of prosumption on Spotify, association and dissociation are related to one another in feedback loops like the platform and the user constitute each other. On the one hand, the setup offers an associated way of engaging with music in which people can search for every artist they like, and find many. The algorithm that then takes over is impassive; if it is corrected for outputting the wrong music, it ‘learns’ and iterates. Besides, it depends on information from peers with the same type of position in the network, which can be seen as a social characteristic with a horizontal organization. On the other hand, the same mechanism produces Spotify as a dissociated milieu in two ways. The first of these is that even when information is used to improve a musical exploration journey, Spotify users have no access to it. The process of selection is delegated to the machine to the extent that tertiary retentions such as ratings are stored in places that cannot be reached by the individual. These retentions, however, are what make the existence of the system possible in the first place. They help Spotify by suggesting ‘the right music’ with as little input as possible, but like the supermarket with its pricing signals, the basis for Spotify’s “normative thrust” (Rieder 2013: 67) is not visible to the public. Even when the third parties that are interested in metadata for profiling are not even considered yet, the associative and dissociative dimensions of Spotify’s recommender system feed off each other. The second mechanism that renders Spotify’s milieu dissociated can be found in how the platform and its users constitute each other. Prosumption moves Spotify beyond a platform for distribution to a platform for recirculation in which the platform and its users co-evolve. Musical content, which is what attracts people to Spotify in the

39 first place, is produced outside of the milieu. It then enters Spotify, which has various mechanisms for distribution. However, as soon as music is consumed, the metadata that this produces re-enters the system of distribution. The user here evolves in terms discovering music through recommendations that should get better with every click he or she makes, while the platform evolves as an ever-expanding database. This creates a multi-dimensional feedback loop in which all relevant data is accumulated to improve the recommender algorithm, but this also goes into other directions such as advertisers. As such, Spotify’s accumulation mechanism also accounts for the second dissociative property; that of metadata as an economic commodity.

3.4 Down to Business

The previous section was about how Spotify’s technological setup can be related to the claims that is has everything for everybody. One other term that resonates on its website is that Spotify is free. On the front page, it is stated that the shuffle mode and ready-made playlists on mobile devices are free, and the desktop version allows you to play any song any time. Clicking on this section of the website directs the visitor to a ‘learn more’ page, where these functions are briefly explained, accompanied by a big banner that again states “Music for everyone, Now free everywhere”. Spotify here attracts potential users by emphasizing that Spotify is free over and over again. This section is concerned with how that freeness of Spotify can be theorized. Like many other platforms, Spotify has a business model, which instantly makes the question relevant how free it really is. Although this does not directly show on the homepage, Spotify is relatively transparent about it; it has a specific webpage where this is explained (“Spotify Artists”). This webpage aims for artists rather than regular users, although it is accessible for everyone. On this page, the workings of Spotify’s business model are explained with highlights on the relevant parts for artists, and what should make the platform attractive for them. So what exactly can we know about this business model? The artist page introduces Spotify’s relevance for artists by stating that they are working hard to fix the condition that the music business has been in for the past few decades. According to this site, music consumption was once simple; someone would listen to the radio, and if he or she liked what he or she heard it would be easy to go out to a store and buy it. Recent developments such as online piracy, YouTube and iTunes would have replaced the old model with a fragmented market that generates little to no

40 revenues for artists. Spotify is proud to offer an alternative that is both legal and monetizable for artists. However, this promotional talk does not make any distinction between the platforms it mentions. Although piracy does not directly get artists money, it has been argued that sampling music by illegal downloads helps consumers make more educated decisions, which does not necessarily mean that they will spend less in total (Peitz & Waelbroeck 2006: 908). YouTube is not transparent about royalty fees it pays (“Generate Income”), but does leave room for artists and labels to add text such as purchase links to a video. iTunes purchases are done once instead of the potential of numerous plays of one song by one user on Spotify, but the royalty rate of an iTunes download exceeds that of a Spotify play by large numbers (“iTunes Artist-Producer”). Other platforms are not even taken into account here, while platforms such as Bandcamp offer their users the ability decide the price of their music themselves (“Bandcamp Artists”). Besides, many have criticized Spotify’s business model for artists as well, to which I will return in a later section. As a solution for the economic problems of the music industry, Spotify aims at taking over the distribution part. How a platform that is free can still benefit artists is explained shortly after. As it appears, Spotify “migrates” people from piracy and less monetizable platforms. Once those people start using the free version, Spotify will “drive” them to a paid subscription so they will pay $9,99 every month. The accumulation of subscription fees and advertising money constitutes Spotify’s income, of which 70% is then distributed among the rights holders of music according to a specific model (see figure 6).

Figure 6. Spotify's model for artist revenues. “Spotify Artists.” Spotify. Web. 13 Nov. 2014.

On this same page, the vocabulary that Spotify uses to describe people hardly matches the rhetoric of freeness it presents on the homepage. Next to herding a user population by migrating and driving them, Spotify speaks about “value per listener” and “the amount of money each of our users is worth”. Additionally, although it is possible to use the service without losing money, even Spotify admits that free users “pay for their

41 consumption by viewing and listening to advertising”. Spotify here explicitly quantifies its users according to their economic value and claims to steer their individuation processes by driving them into the mode of consumption that is the most monetizable. Furthermore, Spotify offers artists insight in analytics. It has teamed up with premier music analytics company Next Big Sound to help artists boost their careers. Although this is not available yet, artists will soon be able to see demographics of their audience and what songs are the most popular on their albums so they can choose what singles to put out next. Moreover, Next Big Sound offers a dashboard that shows statistics such as Spotify plays, but also Facebook likes and Wikipedia views. In this instance too, both the music and Spotify’s users are turned into commodities of which the value in the end can be expressed in profit.

As I have mentioned above, part of Spotify’s earnings comes from advertisement. Like for artists, there is a special section on the website that was formerly named Advertisers, and now called Brands (“Spotify for Brands”). This section is focussed on the prospects of advertising a brand on Spotify, and does so by showing some statistics. Apparently, 146 minutes is “how long the average cross-platform user spends listening, dancing or singing along to Spotify every day”, and they do this from morning until night. The relevance for advertisers is that the more time users spend on the platform, the more time they are exposed to advertisements. This part of the site also shows the number of people that use the mobile application has increased, which also means they can be targeted for advertisement in more places. Furthermore, users share their experiences and musical behaviour, and two thirds of this happens on other social platforms such as Facebook and Twitter. In another section on this part of the website, a selection of a market research results are presented, concluding that Spotify listeners are exceptionally receptive for brands (“Music Streamers”). It is clear that Spotify aims to be attractive for advertisers, and has the statistics to back this up. Once a brand has been attracted to Spotify, it can advertise in various ways. Some advertisement formats include: Video Takeover – a video pops up between songs; Audio – a sound commercial that is accompanied by a clickable link; Display, Billboard and Homepage Takeover – all of which are visual advertisements that vary in the place and time of appearance; Branded Playlist – personal playlist are accompanied by images and texts from brands; Advertiser Page – turns the Spotify application into a microsite that can contain various kinds of content. What is the most notable is that Spotify for some of these explicitly states that they are unavoidable for users. However, they do experiment with this system. In the near future, Spotify will introduce Sponsored

42 Session (“Sponsored Session”). This means that advertisers are able to reward free subscription listeners with 30 minutes of uninterrupted listening after watching a video commercial. So whereas Spotify users love to engage with brands, they still have to be rewarded for watching a complete commercial. This is not necessarily contradictory, but does point out that there is some friction in this field. Spotify, however, must convince listeners, artists and advertisers that it is the right platform for them. According to Tarleton Gillespie, this is inherent to what he calls “the politics of platforms” (2010); they need to be appealing to different parties, but must carefully make sure that “whatever possible tension there is between being a ‘platform’ for empowering individual users and being a robust marketing ‘platform’ and being a ‘plat- form’ for major studio content is elided in the versatility of the term and the powerful appeal of the idea behind it” (ibid: 358). Spotify is relatively transparent about its intentions, but also makes sure that you will not find them if you do not look for them. So the aim of Spotify’s business model is revitalizing the music industry. They are not critical about the economic system that dominated before online piracy existed, but try to invent a way in which music is monetizable in new ways. As such, there are also no accounts in which Spotify is critical of the culture industry and its top down distribution when it comes to finances. For Spotify, the point of departure is not dissatisfaction with the former capitalist mode of industrial music distribution, but how this model of distribution was undermined through new circuits of cultural circulation. At the core of their philosophy, Spotify does not aim to replace the industrial model, which is not only visible in their numerous mentions of the ‘music industry’, but also in the different explanations they offer parties about how value is created. Rather, they neatly adjust to the latest mechanisms of network capitalism while attracting users with the promise of a free platform. Although it is true that one does not necessarily spend money while using Spotify, the account of a free platform should at least be tempered. However, the tension between association and dissociation also arises in Spotify’s business model. While it may not be free in the sense that no money is involved, the service does function as an area in which users can to a certain extent move freely between different modes of discovering and listening to music. But to monetize this, Spotify does register all of these free movements. The associated milieu of freedom of choice and its business model of monetizing this freedom by dissociating information from people are two things that can only co-exist in the current configuration. Furthermore, while other buzzwords are used to attract brands, a lot of freeness is offered to them in terms of flexible options for advertising.

43

That freedom in terms of accessibility in Spotify also has its limits appears in a recent critique from singer-song writer Taylor Swift. She decided to remove all her albums from the service after a Spotify spokesman publicly said that 2 million active followers regretted that she had not yet given permission for het latest album to be streamed (Hernandez). Her album, however, is available on rival service Beats Music that is owned by Apple, which also introduces another problem. The incompatibility between different streaming platforms signifies how economic decisions of exclusivity affect how people can individuate. They can engage in a relation to the music that they like, but in some cases have to learn the hard way that they cannot control habits and investments in cultural material. Another question that remains relevant is how empowering all this actually is for artists. Although Spotify proudly speaks about how it has paid out more than one billion in royalty fees on the artist’s page, there are also musicians that publicly take a stand against how the platform operates. One of the most noticeable is Radiohead singer Thom Yorke, calling Spotify “the last desperate fart of a dying corpse” (Dredge), with which he meant the music industry. For him, Spotify is mostly about major labels that hold shares (“Record Labels”) selling their old catalogues again. Furthermore, the service would not benefit emerging artists that gain virtually no revenues and do not need corporations to be gatekeepers in an age where technology has made these redundant. On the other hand, U2 lead singer Bono defends the platform, arguing that it helps battle the music industry’s opacity that has often not been beneficial to artists. While Spotify’s artist page argues against negative statements about its royalty fee system by stating that a niche indie album generates $3300,- per month, the 392857 streams that it takes to generate that number1 raise the question how niche that album really is. However, the business model is built so that when the number of paid subscriptions increases, there are also more royalty fees to pay. This obviously benefits small artists, but also has implications for other retailers. If Spotify succeeds in taking a larger piece of the pie to make its model beneficial for small artists, its growing market share leaves less room for others retailers, an by this less milieus in which people can experiment and engage with new networked music systems. However, there are also accounts in which people actively use the flaws that they see in the system. One critique with a very positive but also constructive approach comes form Forgotify (“Forgotify”). This application works by only playing songs that have never been played on Spotify before, which was a total of 4 million at the time

1 Based on the per stream rate of $0.0084, which is an estimate of Spotify

44 Forgotify was started. It generates data for Spotify because it works through an embedded player, but it obviously also benefits artist that have not or unsuccessfully promoted their music. While this application can be used for fun just to see what music comes out, it also provides people with an opportunity for reaching music in a very open minded sense with an ‘off the grid’ approach. There is also an example of one a niche indie bands that has turned Spotify’s business model into an advantage. American band Vulfpack uploaded an album to the service called Sleepify (see figure 7). It contained ten tracks of lengths varying between 31 and 32 seconds, which is the minimum length needed to count as a play for royalties (Jonze). Next, they asked their fans to stream the album on repeat while they were sleeping, since there was no sound anyway. Spotify removed the album in April, but in the mean time, the band had received $19655,56 in royalties. Although it could be asked whether it is ethical to set up such a scheme and by this earn royalties that otherwise would have gone to artists that have actually put music on the service, it also shows that it is possible to game the system, which also implies tactical possibilities for critique and change. What it also shows, however, is that it is quite easy for Spotify to act as a sovereign gatekeeper and oppress these little riots.

Figure 7. Sleepify album playlist. “Vulfpack … the Band Who Made $20,000 from Their ‘Silent’ Spotify Album.” The Guardian. 25 July 2014. Web. 13 Nov. 2014.

45 CONCLUSION

Throughout history, much has been written about how the relation between humans and technology often also influences the way humans relate to each other. In recent years, some debates about this relation have been concerned with whether the Marxist concepts of the exploitation and alienation of labour are still relevant for the web. While some argue that prosumption can be seen as a new mode that has replaced the traditional division between production and consumption, my position is that these categories still exist, but are complemented by prosumption. Although the concept of prosumption is strongly related to labour, this thesis has mainly related prosumption practices between humans and specific technologies to how they can be theorized in terms of individuation. To get to a theory of individuation, the thesis has moved from Horkheimer and Adorno’s concept of the culture industry to Stiegler’s programming industries. However, the concepts that surround Stiegler’s theory for individuation – the appropriation of pre-individual funds and the externalization of tertiary retentions – have been used as a framework to analyse a more contemporary phenomenon; online music streaming. Adorno and Horkheimer’s pseudo-individuation as well as Marxist exploitation and alienation have been also been reframed into Stiegler’s vocabulary, which allows territories, movements and configurations to be seen as milieus that can be associated or dissociated. The project of this thesis has been to find an answer to the question: how do the discursive and technological dimensions of Spotify influence individuation? In the final chapter, music streaming service Spotify has been analysed using the theoretical framework that has been discussed in the first two chapters. The platform has appeared to be many different things that are accompanied by various modes of individuation. One important aspect of the service is its catalogue function. This catalogue can be searched with queries, but Spotify also has different tools to navigate through the large database of music. While these navigation tools such as playlists and charts do not require the user to engage with the platform at a specific time together with others, it does synchronize what is presented in terms of categorization and arrangement. However, another important aspect desynchronizes which music is heard. Spotify’s recommender algorithm personalizes music streams through both discovery functions and its online radio station. Because this personalization requires human input that also co-constitutes the output of the service, this is where prosumption on the platform appears as a dimension that complements distribution and consumption.

46 Because Spotify is a commercial platform, tensions arise between the associative and dissociative dimensions of the platform. On the one hand, people use Spotify to externalize their memory by searching for music, creating playlists and giving the platform feedback. This information is then processed by an algorithm that compares this information with peers in the network, and feeds it back into the distribution mechanism for recommendation of more music. While this can be seen as a largely associated practice, it also dissociates because people externalize their retentions in ways that they neither fully understand nor have access to. Furthermore, Spotify and the ways in which it is embedded all over the web are carefully set up in such a way that they maximize attention. This also increases the network effect that increases the value of the platform as more people engage with it, driving it towards monopolizing streamed music services. Moreover, users are dissociated from metadata because it is used for commercial purposes outside of the milieu. However, because Spotify is a platform that has to remain attractive for artists, fans and third parties, they are all approached differently. It is problematic that the associative and dissociative properties have to feed off each other for the platform to exist in the current configuration. The freedom that access to millions of songs at any time of the day brings can only be guaranteed by a platform that constantly tracks every single move and makes a lot of effort to capture attention and soundtrack its users lives. So does this mean that sustainable online music distribution can only be set up as a milieu in which dissociation plays an important part? Not necessarily, is the answer. Whereas recommender algorithms do need to register data, this does not have to be locked up. A system in which data is used for the sole purpose of providing users with recommendations based on the preferences of a collective can indeed be an associated milieu, as long as people have the right to own their data. The same might go for musical content. There could be options for streaming music in various qualities as well as downloading music. In that way, users can decide for themselves not only what pre- individual funds they wish to appropriate, but also how they would like to do this. As for the economic health of the system, it could be set up so that the platform itself is non- profit. Financing the platform based on a subscription fee and financing the artists based on voluntary donations both perfectly fit in an associated form of communication. These donations do not have to remain exclusive for downloads, but could also be integrated in the interface for streaming music. This also leaves room for people to decide how much money they grant artists, which could result in a system that functions like an inversion of a progressive tax; if they like, people can pay artists that are less likely to do well financially more than those that already drive Ferraris.

47 How this could be made operational is something that should be looked into further, but it does offer and idea for how online music distribution could be free, social and for everybody. Stiegler suggested to “conceive this age as an ecology of associated hypomnesic milieus” (2010: 84). My suggestion is that conceiving is not the right verb here: let us transform the music industry into an associated music milieu.

48 LITERATURE

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