Spotify Playlists, Algorithms and Power

Seeking to understand why my Spotify use has changed and is now increasingly skewed toward algorithmic lists I researched a “Digital Cultures” paper for university – this is an edited version.

Canadian cultural critic, Marshall McLuhan would define Spotify as a medium, and therefore differentiated from the music (content) that is played on the platform. He would argue it is not the music that matters so much but what we do, as humans, with it is that has an impact on culture.

As a digital media platform Spotify functions within what new media scholar Jose van Dijck calls a ‘techno-cultural construct’ meaning Spotify can shape users’ activities instead of merely facilitating them. The technological engineering of Spotify was socially shaped by the desire of users to curate personal playlists — now the foundation for the consumption of music.

I am a beta-launch premium subscriber to Spotify, a heavy ‘end user’ of music. My use of Spotify is public, personal, professional and collective. Even when I listen to music in ‘private’ on headphones, at home or in the car I am still participating in a networked collective of humans and algorithms. I have ‘user-agency’ at the intersection of ‘conscious human activity’ and the ‘technological unconscious’ (Dijck 32). Additionally, as a Spotify user I am a consumer, content producer and participant of culture. I am a ‘doing’ the labour of cultural production.

I curate and follow a range of content playlists with four distinct attributes:

1. My own curated lists eg. Spring 2020, Albums of 2020, Guitar Love, Self-Care. I am active in the creation of culture.

2. Other human curated user-lists that I share a common interest in new Australian music with eg Sound Doctrine, Sounds Australia, Double J and the Nightlife Music Team. These ‘humans’ share my interest in ‘new Australian music’ and provide reputational credibility to their playlist curation.

3. Human curated Spotify lists to discover music created by women and First Nations peoples including Original Storytellers, Deadly Beats, Women of AU and NZ.

4. Algorithmically curated Spotify lists that automatically personalise content from my listening habits including Discover Weekly, Release Radar. In 2020 I include two new lists that collate my music taste with news and lifestyle podcasts Your Daily Drive and Your Daily Wellness.

Spotify usage today has expanded the algorithmically curated consumption of songs and sound recordings, transforming humans’ relationships with music.

Music is now inseparable from technology

Walter Benjamin theorised art is an extension of technologies. Music has, what Benjamin called an ‘aura’ — a value and expressive purpose. A playlist removes songs from their original context, intended as a radio single or album track, to create modular lists of human or algorithmically curated inter-connected tracks. Benjamin would argue that when tracks lose their ‘aura’ — their value and expressive purpose are now at the mercy of Spotify engineers, curators and algorithms.

Spotify users are a force in the production of culture

Henry Jenkins contends that media convergence fosters participatory culture by empowering everyday users with the tools to “archive, annotate, appropriate and recirculate” content. These ‘tools’ provide for labour in the cultural production of playlists. As consumers we have become cultural producers. I am now a ‘prosumer’ — a digital culture ‘professional’ where my taste and opinions, playlists and blogs have an audience and influence others’ opinions and consumption.

Algorithmic Culture and Power

“An algorithm is a finite list of well-defined instructions for calculating a function, a step-by-step directive for processing or automatic reasoning that orders the machine to produce a certain output from given input.” Jose Van Dijck (30)

Spotify’s engineered design is intended to influence music listeners behaviour. The manifestation of this is Spotify’s playlist strategy combining both ‘aggressive’ human-curated play lists and ‘passive’ algorithmically individualised playlists — together creating an ecosystem for algorithmic culture to thrive.

Algorithmic culture is the use of computational processes to sort, classify and hierarchies people, places, objects and ideas and also the habits of thought, conduct and expression that arise in relationship to those processes” Hallinan and Striphas (3).

Interpreting Foucault for the digital age Harcourt suggests algorithms are a new form of power. Power that is actively shaping human subjectivity and with more and more digital exposure we are effectively restructuring ourselves and our identities.

Spotify’s algorithmic culture is gathering momentum with the convergence of different forms of audio content — music, news and podcasts into algorithmically curated personalised content and the continuing proliferation of algorithmic lists curated by genre and mood.

It is clear in Werner’s 2019 research how Spotify’s algorithmic culture is problematic —she proves that the recommendation algorithms create “closer circles for music consumption, organising music by similarities in genre and gender.” Cultural forms, of which the algorithmic playlist is one, will reflect dominant values and hegemonic cultures. The play data from algorithmic playlists used to for royalty distribution will enforce inequities.

Broader cultural implications are evolving as Spotify’s increases pervasive practices of feeding users’ algorithmic playlists . Their business model preserves existing power structures and the status quo.

Like film did for text, it is now evident that music streaming platforms build the capacity of algorithms to curate music. Spotify, as the dominant consumer music streaming platform, will aim to ‘lock in’ users to their features to maintain control of the status quo. Robert Prey in his paper “Locating Power in Platformization : Music Streaming Playlists and Curatorial Power” demonstrates how Spotify actively uses curatorial power to “mediate markets in the attempt to advance their own interests.”

Spotify are growing the trifecta of Big Data, revenue and subscribers.

Digital music is a data source. Any future analysis of the impact of digital media will be based on ‘media analytics’ and the ‘billion data rows per second’ being created.

In her chapter ‘The Ecosystem of Connective Media: Lock In, Fence Off, Opt Out?” Jose Van Dijck explains how the major players in the platform culture ecosystem are primarily conduits for data traffic and the subsequent Big Data “flowing through their arteries are the ecosystem’s life blood, determining it’s vitality” (161).

“Spotify’s flywheel is accelerating faster with every new user and creator that comes on our platform. We’re building the world’s largest audio network and it’s clear that our strategy is working” Spotify CEO Daniel Ek, November 2020 in The Music Network

There is little doubt that strategy includes the expansion of algorithmic content that will influence platform engineering design and monetisation of user data.

Business practices such as the recent controversial ‘pay for influence’ tool reported in Music Business Worldwide, where record labels can pay Spotify to influence personalised playlist recommendations– is an example of platforms obtaining user (play) data and selling it to third parties in more ‘discernible’ ways to monetise their services as core to their business model.

Yet, on a personal level I remain troubled.

What would it mean to ‘resist’ the power of the algorithm and its influence on my personal and participatory engagement with music?

Philosopher Colin Koopman believes the idea of data resistance ‘impossible’. He considers the future is living “within a data episteme and under the power of information. We are informational persons.”

What will be the future consequences for us humans as ‘informational persons’ and our music use, artists, royalties, equity, diversity and music taste be?

I doubt the algorithms can think that far ahead.

***

WORKS CITED / RECCOMENDED READING LIST

Benjamin, Walter and Michael W. Jennings “The Work of Art in the Age of Its Technological Reproducibility [First Version].” Grey room, vol. 39, no. 39, 2010, pp. 11–38, doi:10.1162/grey.2010.1.39.11.

Bonini, Tiziano and Alessandro Gandini. ““First Week Is Editorial, Second Week Is Algorithmic”: Platform Gatekeepers and the Platformization of Music Curation.” Social media + society, vol. 5, no. 4, 2019, p. 205630511988000, doi:10.1177/2056305119880006.

Dijck, José van. The Culture of Connectivity a Critical History of Social Media. New York : Oxford University Press, 2013.

— -”Users Like You? Theorizing Agency in User-Generated Content.” Media, Culture & Society, vol. 31, no. 1, 2009, pp. 41–58, doi:10.1177/0163443708098245.

Hagen, Anja Nylund. “The Playlist Experience: Personal Playlists in Music Streaming Services.” Popular Music and Society, vol. 38, no. 5, 2015, pp. 625–645, doi:10.1080/03007766.2015.1021174.

Hallinan, Blake and Ted Striphas. “Recommended for You: The Netflix Prize and the Production of Algorithmic Culture.” New Media & Society, vol. 18, no. 1, 2016, pp. 117–137, doi:10.1177/1461444814538646.

Harcourt, Bernard E. . “Rethinking Power with and Beyond Foucault.” Carceral Notebooks, vol. 9, 2013, pp. 79–87.

Jenkins, Henry. “Convergence? I Diverge.” Technology Review, vol. 104, no. 5, 2001, p. 93, ABI/INFORM Collection; Research Library.

Keltie, Emma. “The Culture Industry and Participatory Audiences.” Springer International Publishing, 2016, pp. 35–58. doi:10.1007/978–3–319–49028–1_3.

Koopman, Colin. “How We Became Our Data: A Genealogy of the Informational Person.” University of Chicago Press, 2019.

Manovich, Lev. “100 Billion Data Rows Per Second: Media Analytics in the Early 21st Century.” International journal of communication (Online), 2018, p. 473.

McLuhan, Marshall. Understanding Media the Extensions of Man. Gingko Press, 2013.

Prey, Robert. “Locating Power in Platformization: Music Streaming Playlists and Curatorial Power.” Social media + society, vol. 6, no. 2, 2020, p. 205630512093329, doi:10.1177/2056305120933291.

— — “Musica Analytica: The Datafication of Listening.” Networked Music Cultures, edited by Nowak, R. and Whelan, A. Palgrave Macmillan UK, 2016, pp. 31–48. doi:10.1057/978–1–137–58290–4_3.

Siles, Ignacio et al. “Genres as Social Affect: Cultivating Moods and Emotions through Playlists on Spotify.” Social media + society, vol. 5, no. 2, 2019, p. 205630511984751, doi:10.1177/2056305119847514.

Werner, Ann. “Organizing Music, Organizing Gender: Algorithmic Culture and Spotify Recommendations.” vol. 18, 2020, p. 78.

Leanne de Souza is an owner and Non-Executive Director of Nightlife Music — a B2B music-tech platform, with the crowdDJ interface, are the market leaders in licenced background music for public performance in Australia and New Zealand.

In 2020 Leanne is also engaged as: :

An active Guardian of Purpose for BIGSOUND50 artist Lydia Fairhall — collectively exploring artist empowered next-economy models for contemporary music.

Chair for the Advisory Board of the Electronic Music Conference (EMC)

A Trustee of the Qld Performing Arts Centre (QPAC)

Completing a Bachelor of Arts at University of Qld majoring in Media and Digital Cultures.

Twitter: @rebelbuzz

Governance | Leadership | Advocacy | Strategy | Research | Undergraduate at UQ | music, books, conversation, alchemy, justice and champagne