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Jing Yi Teo
Armen Nalbandian
Johan Michalove
MacEagon Voyce
Armen Nalbandian
Johan Michalove
MacEagon Voyce
The Music Industry as a Field of Cultural Production | #1: Discovery
Radio was the tiny stream it all began with. Then came other technical means for reproducing, proliferating, amplifying sound, and the stream became an enormous river.
– MILAN KUNDERA, IGNORANCE (2000)
0. PREFACE, OR, A PROMISE TO NOT BEAT THE SAME DRUM
The drum that rolls like this: Spotify sucks, streaming’s model is broken, fraud is rampant, all that is bleak turns into gold but only for the major labels and streaming platforms, alliances that have revealed themselves to be a deepening cartelization, leaving indie artists to get increasingly and disproportionately lost in the gaps, gaps that would deepen and widen with generative artificial intelligence, which would serve technology’s final, fatal blow to music as an art form. But what if we began there, with the assumptions and logic so convenient in wringing the music industry’s discourse into an incorrigible, hopeless result ensnared in platform capitalism’s all-consuming path?
This is a self-directed body of research, one that was undertaken independently after a proposal we generated for a music and events company fizzled out. As an experimentally-configured strategy practice, this is normal. Also normal is asking ourselves where the missing links lie – why go-to-market strategies for ideas benefitting the music ecosystem holistically go ultimately unpursued, and why founders and investors quickly relinquish to status quo paradigms in designing new products in a sector that is valued for its creativity and artistic innovation. New apps, products and features mushroom up across the globe, but they are homogenous in how they look and feel, finding new intersections to wedge into only to find the same pain points. It’s hard to gain new users and retain existing ones when people default to where they can find more music, more event listings, more of a social network.
Given the luxury of researching completely independent of stakeholder bias, this is a proposition that seeks to encourage thinking about the music industry as a model for cultural production – a context-aware, broadened approach that owes its dues to Pierre Bordieu’s theoretical formulation of art not only as work to be taken for its internal characteristics (medium, content, form), nor simply as an economic product of an arrangement between its producers and its consumers (where each transaction is discrete), but as the result of a correspondence between the space of the producers and the space of the consumers; these spaces being the material and socio-economic positions taken by each stakeholder, and the relationships that embed these transactions through which the art is produced, circulated, and consumed.[1]
To highlight the aspect of discovery within the music industry is to confront the technological context within which music now exists. When Spotify was founded in 2006, media was not experienced in a streaming culture premised on constant connectivity but rather a storage culture dependent on ever-larger, ever-cheaper hard drives.[2] Come 2014, as advancements in cloud technology drove the company to reconstitute its data and computing stack on cloud service providers and thereby relinquishing its dependence on P2P infrastructure, the company’s founding roots in file-sharing and music piracy had long receded into the background. The ability to stream virtually any music instantly on a mobile device was not only indicative of the infinite access that came with the internet, it was also Spotify’s brand long in the making: the future of media – whatever you wanted, anytime, anywhere, for as long as you like. That image of infinite access was by that time synonymous with the public’s perception of the internet, where the need to own an artifact was replaced by the ability to stream it. The chain of events that had to happen in order for a person to hear and take to a piece of music for the first time – hearing a sample on iTunes and then buying the digital album, overhearing a song in a public space, visiting the store to buy a record, burning one borrowed from a friend, downloading illegally, and so on – had been evaporated and distilled into the lacuna of the search bar. Beyond which all the music in the world lay, abstracted from context. How music reached the ears of listeners became a sub-section of the industry wherein new mechanisms could be formulated. It was the unploughed land to be dominated. In 2024, Spotify R&D’s Research arm is nearly entirely dedicated to discovery, with its areas of research covering ‘search & recommendations,’ ‘language technologies,’ ‘user modeling,’ ‘machine learning,’ and ‘human-computer interaction,’ amongst a few others.[3]
1. NETWORKS OF DIVERGENCE: RECLAIMING VIBE
“How can cultural producers leverage network effects to their ends?” asks cyberneticist Johan Michalove, in an essay proposing “the network is the territory,” an approach that carries the idea of the network as “a map of meaning itself, shaping the cultural landscape (the territory) rather than merely reflecting it.”[4] The role of the cultural producer thus shifts from being creators of standalone works to “navigators of an ongoing process of meaning-making, situated within a web of associations and relations.” In the music industry, this is apparent at every step of the process. Among the upload material in submitting music for distribution are forms that artists and their managers are asked to fill out specifying associations to the work: artists “you sound like” as well as identifying genres and vibes. Contrary to the common nostalgia-rooted dismissal of music industry’s digitization, the public still listens to music in search of meaning, even though that search occurs increasingly further away from the nucleic center of the work. According to Michalove, “cultural artifacts obtain their meaning not by what symbols and aesthetics they employ, but rather how their connotations are metabolized by the wider associative network they’re situated within.” For music, these associative networks are shaped by factors such as social identification, trend lifecycles, and lifestyle routines. As streaming platforms, through increasingly “seamless” and “intuitive” interface design, encourage their users’ proclivities towards constituting their cultural consumption based on vibe and ongoing activity, naming a specific album or song title becomes a task increasingly out of reach, an awkward moment of incongruence against interfaces that at once exude and entice immediacy.
Upstream, musicians are also encouraged to produce music that compete within these associative networks formed on the basis of similarity. Trapped in the tension between the availability of infinite music and the scarcity of means to explore it, the curious listener, like the vagabond trickster, hops to new networks in order to tap into novel ways of forming associations. On Reddit, users express boredom with not only Spotify but music in general, seeking advice and playlist recommendations from anonymous strangers who possess not data or algorithms but personal experience.[5] Where variation, such as in the way For You playlists reshuffle in their weekly update, fails to suffice, discovery requires divergence.
Why do networks tend towards similarity rather than divergence? Do vibes, or what Michalove refers to as “ambient meaning,” only lead to closed circles of cultural discovery?
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Let’s say you have been listening quite a bit to Norah Jones. As is, on streaming platforms you will be recommended other singers of the jazz-pop genre, such as Diana Krall, Alicia Keys, Michael Bublé, etc. Maybe genre isn’t at the top of your mind as you listen, but the buttery, innocuous voices singing to simple piano melodies recorded at the same time period will fit just right into what has already charmed your ears. Scroll further or refresh the playlist often enough and you will likely get to the next layer of recommended artists: Billie Holiday, Aretha Franklin and Bobbie Nelson – universally beloved artists who have influenced Jones. If your listening history includes names skewed towards either more jazz or blues, you may see Ray Charles, Bill Evans or Tom Waits in the playlists, who do not technically share obvious similarity to Jones but who she has stated as influences. It might take some active searching or a much more expanded listening history in order to get to Jones’ father and the world’s most acclaimed sitar player Ravi Shankar, or her half-sister Anoushka Shankar, a prolific Indian classical musician whose kaleidoscopic tapestries of polyrhythms and microtonal inflections sound words away from Jones’ own repertoire of simple chord progressions.
Let’s say, however, that in a suspended reality you have decided to walk into a record store in your city, and as you browse its collections the shopkeeper comes up to you, asking if you would like recommendations. You tell them that you like feel-good, easy listening, that you put on music at home to unwind from a day’s work while you cook and try to find a warm, cozy, relaxed vibe at home, and Norah Jones, for example, does that for you. The shopkeeper would parse through associations that spring up in their own mind informed by their own listening exposure and their own interpretation of vibes, and perhaps point you to Red Garland’s shimmering block chords, or bossa nova pioneer João Gilberto. Feeling courageous, they might point you to somewhere further back and towards the margin of jazz history in suggesting jazz harpist Dorothy Ashby. Or they might decide, in a genre-agnostic whim of courage, that the lush, smoky atmosphere of Fennesz’ collaboration with King Midas Sound is the perfect music to sink into after a long day.
Wherever you decide to land in the infinite ocean of sounds, this quick hypothetical scenario brings us to two key aspects of cultural discovery: interpretation and risk.
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How divergent a music discovery journey can be hinges on the openness of interpretation and the propensity to risk; divergence becomes restricted in a network of associations structured on the continuation and prolongation of a meaning already accepted. Considering our hypothetical scenario, the record store shopkeeper’s one-time interaction with the listener is drastically more limited than Spotify’s data capture of their listening track record. Even without additional degrees of courage the risk of recommending an album the listener would indeed enjoy is quite high, without time-tested substantiation to the feel-good vibe prompt. In a network model, incorporating such propensity to risk means greater allowance to reconfigure which associations are given more weight and others less or none; it also means giving interlocutors more agency in forming associations anew.
Take for example the preservation and distribution company Dust-to-Digital, whose Instagram presence is a stunning artifact of a divergent associative network. Over years of posting clips of musical performances, their profile @dusttodigital takes the form of a contemporary archive of sonic culture, curated from its followers’ submissions and featuring music through a prismatic range of geographies, contexts and professionality. At the time of writing, its latest post encounters the social media scroller with British musician Shabaka Hutchings playing a wooden flute while riding a bicycle-powered surrealist instrument next to Altai harpists singing in Mongolia next to Italian guitarist Andrea Chiarini playing the guitar with a fishing reel attachment. Its comments section is spirited with people thanking Dust-to-Digital for the joy of being introduced to sounds they have never heard before; the wondrous experience of being exposed to music from disparate worlds at the slide of a finger. Curating each post from a tremendous amount of video clip submissions, Dust-to-Digital’s platform can be considered to be both highly gatekept and extremely random. Yet, it is this active curation – the intervening eye over which cultural artifacts, in the sea of infinite others, belong together in a group – that results in the expansion of possibilities in determining how one artifact connects to another.
There is no doubt Dust-to-Digital is a vibe: one of awe and communality, or in the words of one commenter, one that “reminds me how beautiful and creative humanity can sometimes be.” Similarities exist among the thousands of videos that the account has posted – sublime melodies, DIY or found instruments, polyrhythmic group percussion, indigenous music, etc. – yet the associative network on which it curates is distinctively divergent. With its follower count of 1.1 million and counting, the platform is a living, breathing example of how vibe-based associations can lead to divergent discovery.
2. WAYS OF LISTENING
Are functional, scalable networks simply uninhabitable for divergent associations?
We look into the work of Grey Matter, a platform-agnostic community layer built atop existing music streaming services. Its co-founder MacEagon Voyce describes its goal product as a decentralized Instagram that can play music from any streaming platform, where moments of human-based discovery form the building blocks for community and meaningful artist support. After building the app in open beta where thousands of songs were shared amongst 1500+ users, the team, running on zero external funding, decided to unpublish the app, and are currently reimagining the project as a broader, more decentralized interface. The various aspects of Grey Matter are now being coalesced into a constellation of connective tools: organized through Discord is Crate Coalition, a community forum of “music heads who believe in a more interdependent music ecosystem,” while For the Record is an experiment in generating connective listening graphs through conversations with members and guests of the Crate Coalition community. With music journalists, record store owners, DJs, musicians, festival owners, A&R folk, label heads and more in the web of these conversations, For the Record looks to uncover the listening history of their interviewees, their relationship with music, their discovery pathways and methods. In each conversation, every music mention (a song, album, performance or artist, as well as labels, venues, radio stations) is stamped, and in the background, mapped to form those yet unseen connective threads between the artist, the listeners, and everyone in between.
By nurturing space for its community to tell their stories of how they discovered a certain piece of music or artist, and then visually representing the nodes and associations that form different pathways of discovery, the Grey Matter project presents a model that traces the human stories and connections behind music discoveries, potentially uncovering unexpected pathways to new artists and genres. On its path towards a public, human-centric tool for music discovery, the Grey Matter project has highlighted the staggered, inconsistent and unpredictable potentialities in discovery pathways; how someone who loves Jimi Hendrix as a teenager, finds their way to Captain Beefheart and then to Japanese psychedelic rock band Minami Deutsch. What we can glean from these storied maps is that wherever one’s music taste arrives at is a product of time and a consequence of having listened to music they have enjoyed as well as music they disliked or may have found challenging. Here we return to the risk factor upon which the scope of associative divergence is contingent on: in reinforcement learning, which is a technique within machine learning, a framework often discussed is the trade-off of the algorithm between exploration (trying something new and different, that might help the system gain information) and exploitation (using the information already gained to extract value). Between exploration and exploitation, algorithmic formulas that are built for the purposes of gaining market share inevitably abide by low-risk principles to achieve accuracy in their results, dialing closer to the exploitation end – operating as prediction networks rather than exploratory ones. In fact, these recommendation formulas go a step further and make the listener more predictable by feeding them music that has greater predictive capacity over what they’ll listen to next.
Between Dust to Digital and Grey Matter, curious listening occurs across satellite webs of discovery: smaller, limited-scalability networks that resist free market patterns of domination. Music streaming apps may function increasingly as discovery platforms, although as networked products built with the primordial goal of gaining market share, they operate by generalizing people of all backgrounds, habits, tastes and desires as a populus of the same “listener” even while feeding back your listening profile as unique, and therefore, their service as personalized. But with recommendation algorithms designed to cater to the broadest user base possible by generating varying recommendations based on the music one has listened to, the pluralities of music listening approaches are deprioritised, distilled to aggregates and at best patterns of one’s listening history. Ultimately, ways of listening comprise more than what a person listens to. Multitudes exist in terms of listening habits that extend beyond the markings of vibe, genre and sonic structures: different levels of intentionality, communality and emotionality factor into a person’s approach to music, as with dependencies on everyday lifestyle like routine and environment. Even within an individual, approaches may vary over time, or according to the situation. In effect, the same algorithm applied to different sets of input data yields not personalized pathways to the discovery of new music but variations of playlists past, anchored by similarity and continuation.
3. CO-OPERATIZING DISCOVERY
At the time of writing, there are numerous independent networks that, like Grey Matter, are reclaiming the music space to redistribute value to the cultural producers that create it. For instance, the freshly launched co-operative platform Subvert is intent on building a successor to Bandcamp “that is owned and controlled by its community of artists, labels, supporters, and workers” since the legacy “indie” marketplace once again succumbed to acquisitions that led it to abandon significant aspects of its platform like the editorial team and “Bandcamp Fridays,” which were the very features that defined its core values and community. In Subvert’s precedence is Catalytic Sound, a music distribution co-operative whose work even includes running its own streaming platform, the Catalytic Soundstream. Operating under the goal of creating economic sustainability for musicians in the experimental-avant-garde music scene, Catalytic Sound pledges 50% of the net income directly to the 30-odd musicians in its collective, defining itself as “a co-operative between artists and patrons”[6] – absorbing the listener-subscriber-fan group into its realm of cultural producers as well.
As these innovations play out in establishing alternative financial models of collective and equitable value flows amongst cultural producers, could there be a co-operative model applied to the discovery layer of the music sector? What are possible modes of platforming those aforementioned smaller, limited-scalability networks where truly divergent, explorative discovery transpires, while initiatives like Catalytic Sound and Subvert work to generate possibilities on the distribution end? Returning to the framework of associative networks, how could satellite discovery networks maintain in orbit around each other, each with their own discernible breadth of music?
We could look to wherein lies rich potential in conceptualizing discovery through distributed, locally-attuned constellations of curatorial nodes: performance venues, which are satellite networks that are already enmeshed within a city’s infrastructure, but which thrive on their own autonomy in programming events and artists. In Los Angeles, 2220 Arts + Archives is a brilliant example of a venue co-operative where the programming is collectively curated by resident and guest programmers alongside “roughly a dozen complementary arts nonprofits, independent artists and curators” who host one to two events a month at the venue.
We want our operating revenue to flow as much into programming as possible, and avoid growing a large ‘creative workplace’ and bureaucracy. Our space directors are calendar-focused and avoid top-down planning and art direction, in favor of listening and coordinating among our different programming entities, and otherwise just balancing and EQ’ing the mix.
We’re a collaborative multiplicity, and we watch and learn from other models around our city and elsewhere.
– 2220 Arts + Archive’s Mission Statement[7]
Also of note is that as an artist-driven and artist-organized space, 2220 Arts + Archives is somewhat of a meta-satellite network, a venue embedded amongst Los Angeles’ umbrella of at least a dozen other performance art venues, itself host to a multitude of niches and thereby transcending their siloes, “blend[ing] audiences and communities across styles and artforms in the process.” A jazzhead who attends the 60th’s anniversary of the “October Revolution in Jazz” presented by Black Editions and Zero Productions is thus in the orbit of discovering the experimental composer Eiko Ishibashi under Acropolis Cinema’s showcase of her live score to GIFT, a silent film by Ryûsuke Hamaguchi.
Within already-divergent networks such as 2220 Arts + Archive, the curious listener is able to traverse from one node to another on associations that are not only novel but also open to interpretation. If venues were to be perceived and given agency as divergent networks, we could imagine a plethora of ways that these venues, institutions and hosts embrace this agency in facilitating the multitudes of true discovery that can be potentialized on their networks. For instance, we could envision a shift in power from the event ticketing platform monopoly towards a more distributed and direct discovery-to-ticketing infrastructure where a venue’s event calendar serves as a site of discovery – with audio-visual content in place of boilerplate artist bios and profile photos. Returning to Michalove’s definition of the role of cultural producers as “navigators of an ongoing process of meaning-making,” the associative network model could serve as a valuable model for intervening in the music industry to better serve its artists, listeners and all the other cultural producers in between. Under this framework, wouldn’t the layer most ripe for reconfiguration be discovery – where one node connects to another in associations formed anew?
Notes
- Pierre Bordieu, “The field of cultural production: essays on art and literature,” ed. Randal Johnson (Columbia University Press, 1994).
- Patrick Vonderau, “Spotify Teardown: Inside the Black Box of Streaming Music” (MIT Press, 2019).
- See ‘Research Areas’ documented by Spotify R&D: https://research.atspotify.com/research-areas/.
- Johan Michalove, “The Network is the Territory,” (The Last Wave, 2024).
- Threads abound on subreddits like r/Spotify and r/Music. Here is one example: https://www.reddit.com/r/spotify/comments/s3hlxk/need_new_playlist_recs_im_bored_of_my_music/
- https://www.catalyticsound.com/about/
- https://www.2220arts.org/about