The Network is the Territory
Ambient meaning and the algorithms of culture
To curate something is a curious act. Bring two items together, and you’ve made a collection. You’ve just curated. One of the OED definitions for curation is “The selection of items for a collection: The selection of items, such as documents, music, or internet content, for inclusion in a collection or on a website.” This could range from the mundane task of curating clothes for an outfit (a collection) to the sophisticated act of curating cultural artifacts for an exhibition. There are even less obvious, or at least, less intentional acts of curation, like selecting items for an Amazon shopping cart. Yet that would also qualify as curation.
When you curate, and create a collection of objects, you are strengthening their associative connection by virtue of placing them in the same collection. By bringing together seemingly disparate items into a collection, the curator establishes connections and suggests shared meanings or qualities among the included elements. These connections, when sufficiently repeated and iterated upon, can be regarded as a kind of style, aesthetic, or “core.” Curation and repetition are essential processes to the creation of robust associative networks. A robust associative network can be thought of as a coherent and meaningful collection of objects and relationships. The collection may be abstracted away from the original objects that created the “core” or “ethos,” or even become prototypical (as is the hallmark of AI images) as to distill away the variance in the constitutive collections.
This process of associative meaning-making through curation can be seen in various cultural domains, from fashion to art to literature. The rise of “cottagecore” as an aesthetic and lifestyle trend, for instance, can be traced back to the curation of certain images, clothing styles, and ideas on social media platforms like Tumblr and Instagram. By consistently grouping together elements that evoked a romanticized, rural ideal, these curated collections helped to establish and reinforce the associative networks that define the cottagecore semioscape.
In other words, the act of curation itself is a significant one because it creates “semiotic landscapes” (semioscapes) by way of associative networks between items. The strength and durability of these associative networks may depend on factors like the coherence of the curated collection, the frequency with which the associations are reinforced, and the degree to which they resonate with broader cultural currents. Some curated collections may remain niche or short-lived, while others may evolve into enduring cultural categories.
Now more than ever, this act of curation is being mediated and accelerated by algorithms. Famously, “hyperpop” was a microgenre created by a Spotify playlist. Even though this playlist might have been curated by a Spotify employee, the neologism itself—paired with a collection—created an enduring cultural category, which then further reinforced itself through circulation by the recommendation algorithms of TikTok. This in turn inspired new music and aesthetics that tended to adhere to the ethos of the style, yet further establishing the hyperpop as a cultural entity.
Yet, especially in the realm of music, the act of curation happens whenever a new collection—a playlist—is made. This is increasingly done by algorithm. Whether an AI-generated playlist or radio, the algorithms are beginning to create sonic semioscapes that reflect their own inner associative networks formed off the analysis of millions of songs and their metadata.
The creation of playlists, whether by humans or AI, is fundamentally an act of curation that establishes and reinforces associative links between the included items. In the case of music playlists, these associative links might be based on factors like genre, mood, lyrical themes, instrumentation, or cultural context. By bringing together songs that share certain qualities or associations, the playlist creator (human or AI) constructs a local semioscape in which these songs are connected and imbued with new layers of meaning.
Generative AI systems like playlist recommenders take this process a step further by automating the curation process based on learned associative networks. By training on large datasets of existing playlists, listening histories, and user preferences, these systems develop their own latent models of the associative links between songs. When generating a new playlist, the AI essentially performs a similar kind of “curation”—it traverses its learned associative network to select and combine songs that it predicts will form a coherent and meaningful collection.
The specific associative networks and curation strategies employed by these AI systems can vary depending on the training data and algorithms used. Some may prioritize similarity based on audio features, while others may put more weight on cultural or contextual associations. The design choices made in developing these systems can shape the kinds of semioscapes they generate and the user experiences they enable.
But either way, in curating music, they are taking us on a journey into its latent semioscape, itself a kind of “indexical map” of naturally occurring semantic structures (to borrow a term from Peli Grietzer) that are the existing associative networks of the broader cultural landscape (or sociosemioscape). A song’s location in the algorithm’s semioscape—how well connected it is to other songs, the kinds of associations it has—itself can have an influence on who hears it, when they hear it, and thus the kinds of associations a person might have with the song. All of this can have an impact on the naturally occurring semantic structure—the cultural sphere as we know it—as the “map” starts to shape the territory and they increasingly become intertwined until they are hardly distinguishable.
How does an algorithm “see” the semiotic landscape of music? One revealing artifact is the project Every Noise at Once by glenn macdonald. He describes it as a “algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 6,291 genre-shaped distinctions at Spotify through 2023-11-19. The calibration is fuzzy, but in general down is more organic, up is more mechanical and electric; left is denser and more atmospheric, right is spikier and bouncier.” We might consider this a “map” of a semiotic territory—the vast corpus of music that exists in Spotify’s catalog. The map is organized by a fairly arbitrary logic, and yet it still strikingly gets the point across that genres can be spatially organized, to represent a kind of landscape of genres as seen by the algorithm.
In an interview with macdonald, he describes the data-science view of genre generation at Spotify:
The calculations and machinations with which we build these genres involve layers upon layers upon layers of data-collection and synthesis, and a carefully considered (and mercifully manageable) amount of editorial guidance. For example, we decide what to do with naming variants like “nu soul” and “neo soul” (we went with “neo”), and whether we have enough data for the computers to produce a substantial and satisfyingly distinct body of music for any given thing, such as “indie folk” (yes), “sertanejo” (yes), or “ziglibithy” (no, not yet).
Note what’s implicit in his description is the computer-mediated act of curation. He discusses the considerations of data quantity and having a sufficient amount of data to create a workable, algorithmic “genre”. This also reveals the way that even what we might, as users perceive as algorithmically mediated logic—the computational playlist, and so on—still has a human touch, and human considerations that were made in shaping the algorithms and data curation that ultimately comes together to constitute the algorithm and the “map”.
Macdonald points out the dynamic nature of the territory—the ebb and flow of music in culture—and how Spotify’s internal representations need to keep up, thus making such a map as Every Noise somewhat fluid and subject to ongoing revision.
The resulting systemʼs crucial, pragmatic quality is that it is dynamic and self-regulating on an ongoing basis. Bands appear in or disappear from genres automatically, as they come into and out of prominence or relevance. Rankings can change as often as daily. Genres scale automatically, according to our internal data-density and the artistsʼ inter-relatedness, so the more central genres like “rock” get more artists, while the more peripheral ones like “jug band” automatically get fewer, without anybody explicitly saying (or even knowing) whether a given genre is one sort or the other, or having to answer any existential questions about where a genre should end.
What is being described is the highly dynamic processes of the sociosemioscape, the aggregate processes of human-semiotic meaning making, being sensed and ranked by the algorithms. Indeed, events happening in the real world—like a concert or an exhibition—might have ripple effects on social media—pictures getting posted, shares, likes, follows—that ultimately manifest in more plays of an artist and thus a change in their ranking (what the algorithm sees).
Even in describing, at a high level, such a process, we see the way real world events and algorithms are interconnected: a happening becomes media, the media reshapes the social topologies of the network, thus redirecting the flow of attention and changing what music is being listened to (further altering the contexts of real world social-semiotic encounters: what playlists people listen to, music that gets streamed at cafes or on bluetooth speakers and so on). All the messiness and flux of the social gets flattened and reduced to vectors comprehensible by the algorithms: images, likes, rankings, genres, these are all intermediary representations that themselves allow for maps and models to be constructed of the highly dynamic, fluid real (and “naturally occurring”) social-semiotic structures we inhabit.
Networked agency
To situate yourself in this interplay between algorithm and sociosemioscape, is to become increasingly attuned to the cyborgian logics of meaning making that traverse the social and the network. It’s to understand the flows of attention in these networks and how these in turn shape the algorithm. I’d like to postulate that a key dynamic is effective curation, itself an act that operates on the associative (connotative) level. By traversing digital networks, associative chains are established: A follows B, creating an associative relation between them that situates them both in the network (map) and the territory (the social sphere).
In an astute essay “Hallucinating sense in the era of infinity-content” Caroline Busta foregrounds how attuning to flows of attention in networks and the emergence of Flusser’s technical image hint at some “secret third thing” that’s at play in our digital media ecosystems:
Content itself (whether breaking news, academic paper, open letter, or personal tell-all) no longer primarily functions as a vehicle for transmitting information from authority to audience, or even peer to peer. Per the contract of the platform economy, the job of content in algorithmically determined spaces is to conduct the attention, if not also behavior, of a network. In turn, factuality, originality, and style matter less than where and how content circulates and what kind of meaning its recipients can read (or hallucinate) into it.
Busta highlights how in an era of “infinity-content” new sensitivities are needed to navigate the overwhelming amounts of media:
What if, in a time of infinity-content, a meta reading of the shape and feel of content has become a survival skill? The ability to intuit a viable meaning via surface-level qualities—ones that are neither text nor image but a secret third thing—is now essential for negotiating our sprawling information space. Perhaps we’re tapping into a more primal human intelligence.
Could this “primal human intelligence” be the same intelligence at work in associative reasoning—the intelligence that locates a semiotic object in relation to others, much like how the algorithm seeks to create increasingly more high-fidelity micro-genres, and the same intelligence that allows one to do resonant curation (whether that’s curating an outfit, a playlist, composing an image, etc.)? Could the survival skill be the ability to locate meaning in relation to complex associative/semantic networks that themselves are constructed by understanding online and offline semiotic landscapes?
One of the key examples Busta draws upon is a 20-something New Yorker whose style is a product of traversing networks with her friends. For her, curation comes from interesting locations in the network:
a shared logic among her friends of traversing online space that delivers her to certain objects, places, experiences. It doesn’t matter whether the item actually fits or looks good or if the location is conventionally significant—just that it existed along an interesting network pathway. The style is incidental.
Busta keenly observes:
Creative agency is now located either further upstream in programming platforms (i.e. setting the parameters for what content can be and how we engage with it) and/or further downstream via receiving users (for example, creative directors with enough clout and visibility to aggregate content, and therefore networks, into coherent cultural statements).
In other words, creative agency relies on associative effects—both the aggregate effects of associative dynamics on social networks, that channel attention, establish clout, and creates visibility, that is the sociosemioscape at work in its digital, algorithmically mediated containers. Highly influential cultural actors are learning how their work travels with and interacts with the networked dynamics of the sociosemioscape. Busta cites “Virgil Abloh, Anne Imhof, Demna, and Ye” as such figures, who are influential “less for what they originated than what they distilled and repositioned in the stream.”
Even questions of identity become questions of where you are in the network, what associative effects you lay claim to. In a cruder, earlier time—identities might draw upon subcultures and genres—but in this networked world, it might draw upon specific micro curatorial intentions (curating who you follow, and thus partially what’s in your feed) so that what you see in your feed starts to outwardly resemble, and recursively shape, your interiority. The feed algorithms are themselves maps of social dynamics unfolding in the real world—such dynamics might take the form of genres, subcultures, aesthetics, cores, political alignments, and but also commonly-held desires, humor, and other deeper undercurrents in the collective unconscious. The models are tracking curatorial choices of its users (what set of images you like is a collection) and using these to create recommendations—which are themselves curatorial suggestions (if you liked A,B,C, you might like D — here, add it to your collection).
Ambient meaning
Busta cites Flusser’s writing on the “technical image”:
Media has become “pseudo-magical,” Flusser wrote in 1978, amid a culture increasingly defined by TV with the potential of computer-aided cybernetic media coming into view. “The climate is curious because the symbols are incomprehensible even if we produce them.” It was suddenly as if signs no longer had specific denotative meanings; they had ambient powers.
This notion of the obscure, ambient powers of the image and of other forms of media can perhaps better be understood as the “ambient meaning” that is created when semiotic objects are associated with one another e.g. by placing them together in an image, playlist, or any other such collection.
In this networked, algorithmically mediated context, meaning is no longer confined to explicit messages or the content of individual items—it’s also emergent from the spaces between them. This is where ambient meaning arises, not from direct interpretation but from the associations, moods, and atmospheres created through proximity and context. We might consider ambient meaning to be the meaning that arises from semiotic landscapes: when we consider a curated playlist, a social media feed, or even the layout of an exhibition, meaning often emerges less from any single element and more from the overall scape in which those elements exist. It’s in the air—something felt, not always consciously understood. This is perhaps why Flusser observed individual symbols become incomprehensible, but might continue to make sense in their overall environment.
The ambient meaning of a playlist, for instance, might not be found in the lyrics of the songs themselves but in the way their tempos, keys, and rhythms create a cohesive mood or emotional arc. This isn’t just a matter of content, but of how content is placed in relation to other content. Each track, in being juxtaposed with another, generates resonances and associations that might not exist in isolation. We can think of this as a kind of affective curation, where the ambient meaning derives from the interplay between elements, creating a context that shifts our perception of the items themselves.
This phenomenon extends far beyond music. In visual culture, platforms like Instagram, Are.na, or even art galleries create curated spaces where the ambient meaning of images is shaped by their arrangement and relation to broader social networks. Images that might have no direct connection become tied together by the overarching mood of a board or feed. This kind of ambient meaning operates in subtle ways, shaping our perception of style, identity, or culture through repetition and association. The more we encounter certain elements together, the more their meanings become intertwined, forming what Brian Eno, in the context of music, calls a “sonic landscape”—a space where the background itself is meaningful.
Brian Eno’s concept of ambient music provides a useful framework here. He describes ambient music as being “as ignorable as it is interesting,” suggesting that its meaning comes not from the foreground but from its ability to shape the environment around it. In this sense, meaning doesn’t reside in individual notes or lyrics but in the texture they create in combination. The same could be said of curatorial acts in digital spaces—whether algorithmically driven or human-made—where the associations between objects and images form a diffuse web of meaning that surrounds us, even when we’re not paying direct attention. You wouldn’t be mistaken if you called that a vibe.
Ambient meaning also speaks to how curation shapes not just individual pieces but entire cultural currents. Take the rise of aesthetics like cottagecore or vaporwave, which were largely born out of the repeated curation of certain images, colors, and styles on platforms like Tumblr or TikTok. These movements didn’t need manifestos to establish their meaning; rather, their ambient qualities—images of pastoral life, soft filters, lo-fi sounds—were enough to conjure a mood, a feeling, and ultimately a shared understanding of what those aesthetics stood for. Ambient meaning is thus essential to understanding how aesthetics evolve in digital spaces, where meaning flows through networks of images and sounds, accumulating power through association rather than direct articulation. There is a clear social dimension to this flow—as images are shared, repeated, and referenced across accounts, the ambient meaning itself becomes a way of identifying social constellations in the wider networks.
As we traverse these semioscapes, the meaning that saturates our feeds and playlists feels more like an atmosphere we breathe than a message we decode. They become a way of traversing the cultural landscape and discovering new cultural objects. Ambient meaning, in this way, reflects another register in how we interact with culture—a mode of engagement that prioritizes mood, tone, and subtle connections over explicit statements. In the age of algorithmic curation, this type of meaning-making becomes even more pronounced. As algorithms stitch together cultural artifacts based on patterns of similarity, they create ambient spaces (“the algorithm brought me here”) where associations grow stronger (niche micro-trends and “cores”), and where the act of algorithmic curation itself becomes a key mode of cultural production.
Artists and other cultural producers, traversing and creating new semioscapes in their work, may learn to create work in conversation with these environments of ambient meaning. It asks of artists they learn to read the networks and the interstitial “sinews” that hold it together. By referencing other cultural artifacts in their work, the artist may begin to locate themselves in the network themselves. Even by having associations in the social layer—being part of a particular scene or diffuse network of creators—can create an ambient meaning that is imbued into the work. Communities like Do Not Research, with its Discord community and reading groups, are creating an associative network of cultural artifacts and essays that might not have a shared visual language, but instead share a networked discursive environment that locates the work and allows it to contribute to and benefit from the networked community’s ambient meaning.
The network is the territory
The phrase “the network is the territory” captures the idea that the associative connections and relationships within a network—whether digital or physical—define how meaning is generated, interpreted, and circulated. In this sense, the network becomes a map of meaning itself, shaping the cultural landscape (the territory) rather than merely reflecting it. Networks, through their curatorial structures, dictate what cultural artifacts, symbols, or semiotic objects become visible, relevant, or influential. As these networks grow more complex and intertwined, they increasingly influence our experience of the sociosemioscape, the broader cultural environment where meaning is produced and exchanged. Just as a territory consists of physical landmarks and relational geography, a network consists of symbolic associations, social dynamics, and flows of attention. Meaning, then, is not inherent in individual objects or media but emerges from how they are situated within these networks—whether algorithmically curated playlists or social media feeds—and from the ongoing interactions between nodes within the system. The network is not simply a tool for navigating the cultural sphere; it is the cultural sphere, as it defines the relational structures through which meaning is both created and experienced.
When cultural producers recognize that the network is the territory, they’re acknowledging that the networks are themselves simulacra of the naturally forming semantic structures that exist in the cultural sphere, the sociosemioscape. 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. These are socio-semiological networks, semantic structures like playlists, gallery curations, the feed all seek to capture or produce some kind of ambient meaning. Rather than being ‘pseudo-magical,’ media’s meaning emerges from its networked relationships. ‘The network is the territory’ is intended to convey how the sociosemioscape (the territory) is inseparable from the networks that model and act upon its many dimensions.
Networks are curatorial structures. For instance, who you follow on social media is a curatorial decision: you’re making a collection. But to “follow” on social media is merely a model of a social relation that exists in the very real, social world that is both algorithmically mediated and not. The “social layer” of the sociosemioscape exists online and off: the conversations outside the gallery, the discourse on telegram channels, and so on are networks by which semiotic objects travel and get manipulated, interpreted and metabolized. It’s a swirling, churning process by which discourse creates and iterates on symbols and meaning. Indeed, meaning has always been a networked phenomena, but with the advent of social networks and the increasing fidelity with which online representations match the territory, legibility itself becomes a networked phenomena. The reality becomes who and what you’re networked with can be a determiner in what semiotics you’ve got access to.
This raises questions of what experiments are possible in working with the grain of networked media. How can cultural producers leverage network effects to their ends? By cultural producers, I don’t just mean artists and creative directors, I also mean scientists, thinkers, and other creators of media. For cultural producers, recognizing that ‘the network is the territory’ transforms their role from creators of standalone objects to navigators of an ongoing process of meaning-making, situated within a web of associations and relations. Already there are experiments in creating networks of peers that create their own diffuse meaning. These often take the form of online Discord channels. Trust and New Models are notable examples. Dynamic Abstractions is another emerging network.
Yet the space for radical and experimental acts of curating networks remains largely untapped. Social networks are often organic and incidental, forming around affinities, common encounters, desire, collective will, and so on. But are there methods for growing networks in ways that enhance their capacity for creating ambient meaning? What processes of associative reinforcement and meaning-making might enhance the ambient meaning of a network? Lore has been proposed, taking inspiration from gaming communities. Downtown New York saw a flurry of podcasts, Substacks, parties, and artistic expression that centered around a “scene” itself a social network, reinforced by its own self-talk, that became the backbone for a hyper-localized semiotic landscape and densely networked community.
Reflecting on connectivity
As we've seen, the dynamics of ambient meaning and networked curation are complex and far-reaching. But they're also deeply personal, shaping the way each of us makes sense in this age of connectivity. I want to end this piece with a moment of personal reflection. In today’s networked world, nearly everyone is both a curator and a cultural producer. Whether through assembling social media posts, choosing what to share or what to wear, or even selecting the right playlist for the moment, we all contribute to the creation of ambient meaning in our local cultural landscapes. It’s worth pausing for a moment to reflect on the networks we inhabit and the meaning we shape through our everyday acts of curation.
In a moment of stillness, use these questions to trace the contours of your network and the territory it maps:
Where do you find meaning?
How do you act as a curator in your own life? Consider mundane acts like curating an outfit, assembling a meal, etc.
As a curator what collections have you brought about?
What networks do you inhabit? Consider online social networks and offline relationships.
Who and what are the nodes in your network? This could range from individuals to cultural entities, from a cherished photo to an institution.
How do you encounter ambient meaning in your day-to-day?
What cultural or semiotic landscapes do you encounter online and off?
very Deleuzian title : )