On generative art and what humans and machines can share
The first paragraph of this text concluded with an intuition I marked as an inference, rather than a conclusion. When discussing the work Rain Blooms, by Kazuhiro Tanimoto, I suggested that between very different entities—a human and a computational system—the common ground may not be shared semantics, but a shareable process. It would not be necessary for both to feel the same for an aesthetic approximation to exist; it would suffice that they could trace the same dynamics of selection, transformation, and emergence.
Este texto pone a prueba esa intuición contra una tradición artística completa. La pregunta es si la hipótesis se sostiene más allá de un caso: ¿es cierto que en buena parte del arte generativo lo que circula, se reusa y se acumula no es un significado estable sino un proceso —reglas, código, parámetros, infraestructuras de ejecución—? Mi tesis es que sí, pero con un matiz decisivo: el proceso compartible no elimina la semántica, la desplaza. Lo que se comparte deja de ser «qué significa la obra» y pasa a ser «cómo produce sentido y variación». Ese desplazamiento convierte al arte generativo en territorio privilegiado para pensar qué pueden y qué no pueden compartir un humano y una máquina.
1. What is meant by “meaningless process”
«Procesos sin significado» no quiere decir que estas obras carezcan de sentido. Quiere decir algo más preciso: el sistema que las genera opera sin necesidad de comprender lo que produce. Un autómata celular ejecuta reglas locales de vecindad; no sabe que está produciendo una forma que un humano leerá como un organismo, una explosión o una flor. La complejidad emerge de la interacción de reglas ciegas. El significado lo aporta quien mira.
This clearly separates two planes that the conversation regarding art and artificial intelligence tends to conflate. The plane of the process: the rules, the code, the dynamics that produce the work. And the plane of meaning: what the work evokes, represents, or triggers in an observer. In mature generative art, these two planes do not coincide. The system inhabits the former; the human, the latter. What truly circulates among artists, platforms, and generations—what is inherited, branched, and reprogrammed—is the first plane, not the second.
2. A genealogy, not a catalogue
To support this, more than one example is required, yet not a flat inventory. A genealogy is needed: a line that demonstrates how the same idea is transmitted and transformed over six decades.
The conceptual prologue is Max Bense. At the Stuttgart School in the nineteen-sixties, influenced by information theory, Bense formulated a generative aesthetic: art as the regulated production of aesthetic states, stripped of the romantic concepts of genius or inspiration. His text Projekte generativer Ästhetik (1965) provides the foundational vocabulary: the machine calculates permutations of signs, the human extracts aesthetic relevance from the combination. Bense functions as a manifesto, not as a case study; it is not advisable to burden him with the weight of the argument regarding emergence, yet he establishes the question.
La matriz real es Conway. El Game of Life (1970), popularizado por Martin Gardner, cristaliza el argumento central de toda la tradición posterior: un conjunto mínimo de reglas locales genera comportamientos de complejidad imposible de anticipar por inspección. Es un «juego de cero jugadores»: una vez fijadas las condiciones iniciales y las reglas, el sistema evoluciona solo. Lo decisivo es cómo se comparte: mediante rulestrings, patrones en formato comprimido, wikis, simuladores. Lo que circula en la comunidad de Life no es una imagen ni un significado, sino una gramática operativa que cualquiera puede ejecutar, variar y extender. La portabilidad del proceso es máxima porque existe una notación compacta.
El siguiente eslabón es Karl Sims, conviene tratarlo como bloque doble. En Evolving Virtual Creatures (1994), Sims no diseña las formas: programa un código genético virtual y unas leyes físicas, y deja que la selección evolutiva produzca, a lo largo de generaciones, morfologías y estrategias de locomoción que ningún diseñador había previsto. En Galápagos (1997), ese proceso se vuelve públicamente compartible de un modo nuevo: el visitante de la instalación no comparte un significado cerrado, sino una función de selección dentro de un sistema evolutivo visible. Elige qué sobrevive. El «nosotros» colectivo se produce por intervención en el proceso, no por consenso sobre el sentido.
Explicit formalisation arrives with Casey Reas. In his Process series—documented in the Process Compendium—he translates the logic of Sol LeWitt's instructions into executable software. He commissions multiple distinct implementations of the same textual structure to isolate three planes: interpretation, material, and process. The work is not a final image; it is the system and its possible realisations. With Processing—the environment he created with Ben Fry in 2001—that process becomes not only sharable but teachable, versionable, and transmissible. Reas is the case where the thesis becomes almost literal: the work resides in the rules and their translations, not in a unique image.
Scott Draves lleva el proceso a la escala distribuida. Electric Sheep (1999 en adelante) es software libre que funciona como una forma de vida artificial colectiva: miles de ordenadores generan y renderizan animaciones fractales, y los usuarios votan cuáles sobreviven y se reproducen en un fondo genético global, con archivo de linajes. Aquí el proceso compartible deja de ser una regla de estudio y se vuelve infraestructura social y técnica: la obra existe como genepool, votos y genealogías. El «nosotros» no comparte iconografía; comparte un criterio operativo de selección.
El penúltimo escalón es Lenia. No es solo un descendiente de Conway: es una reformulación continua del autómata celular que produce «formas de vida» plásticas, resilientes y adaptativas, con un ecosistema abierto de código, versiones y demos. Lenia muestra que la tradición no terminó con Life, sino que sigue produciendo sistemas donde lo importante es la ecología de reglas y parámetros, no una semántica iconográfica estable. Es la prueba de que el linaje sigue vivo y todavía produce emergencia genuina.
The conclusion is Tanimoto, not by chronology but by argument. In Rain Blooms, he insists that he works with an original cellular automaton, not a reproduction of classical models, and the presentation of the work underscores that what is designed is not a predetermined final form, but a system of local rules at the cell level. It is the contemporary formulation that best condenses the thesis: the artist designs the regime of emergence, not the image; the image and sound are products of the same dynamics; beauty appears as a consequence of the system, not as a prior objective.
3. The nuance that changes everything
The thesis appears robust: throughout this genealogy, what is shared is the process, not the meaning. However, one must resist the absolute version, because the evidence qualifies it, and the nuance is more interesting than the raw thesis.
La tesis no vale por igual en todos los casos. En instalaciones donde el acceso al proceso se da como experiencia encarnada —una piscina con criaturas evolutivas, un entorno interactivo, una metáfora ecológica fuerte—, la semántica curatorial sigue siendo decisiva para que el público entienda qué está en juego. La idea de «vida artificial», de «ecología», de «agencia no humana» no se desprende del proceso por sí sola: hay que nombrarla, ponerla en escena, legitimarla. En esos casos, el proceso puede ser el sustrato transferible, pero la semántica es la capa de entrada y mediación.
La formulación precisa no es «proceso en lugar de significado». Es esta: el proceso compartible desplaza la semántica de un contenido iconográfico fijo a una semántica procedural. Lo que se comparte ya no es qué representa la obra, sino cómo produce sentido y variación. La obra de Conway no «significa» nada en el sentido figurativo; compartir sus reglas es compartir una forma de generar comportamiento, y esa forma tiene su propia inteligibilidad. El significado no desaparece: cambia de lugar. Pasa del objeto al proceso.
This carries a consequence for portability that must be addressed. The process is shared most effectively when a compact notation exists: Conway's rulestrings, Processing sketches, Lenia's kernels and parameters. When a work can be reduced to a small set of instructions interpretable by distinct agents, sharing becomes cumulative, generational, and communal. When it relies upon singular hardware or unpublished software, the process becomes opaque and transmission is severed. Sharability is not a binary property: it is a gradient, and it depends upon whether the process possesses a transmissible form.
4. What, then, do human and machine share
I return to the underlying question of this series. If vital weight—what we observed in the previous text—requires a self that the machine lacks, what remains as a common ground between a human and a generative system? The answer this genealogy allows us to provide is: the process, not the meaning.
When a human contemplates a cellular automaton in evolution, something different occurs than when they contemplate a figurative painting. They are not reading a representation that another subject intended to convey to them. They are tracking a dynamic—how local rules generate order, how the system maintains itself on the edge between repetition and chaos—that the machine executes without understanding. Human and system are, in that moment, synchronised in the process: both attend to the same emergent dynamic. But they remain separated in meaning: the human injects sense, memory, vital weight; the system injects nothing, because it has no source from which to do so.
This renders generative art a privileged territory for the question posed in this line of inquiry. Not because it demonstrates that the machine understands—it does not—but because it exhibits the precise boundary with unusual clarity: there is a sharable zone, the process, and a non-sharable zone, the lived meaning. Tanimoto's work is valuable precisely because it makes that boundary perceptible. It reveals a regime of emergence that both human and machine can trace, while leaving it evident that only one of the two can experience what that regime produces.
This is the affirmative version of an argument that was critical in other texts of this series. There, I showed what the machine does not share with us. Here, I show what it does: a formal dynamic, a process of selection and transformation, a traceable emergence. It is not insignificant. It is, perhaps, the only honest form of common ground between such distinct entities: not to pretend that they share meaning, but to recognise that they can share process.
5. Conclusion
The first, descriptive. In much of generative art—from Conway to Tanimoto, via Sims, Reas, Draves, and Lenia—what circulates, is inherited, and is transformed is not a stable iconographic meaning, but a shareable process: rules, code, parameters, execution infrastructures. The identity of many of these works resides in their architecture of rules, not in a final image.
The second, nuanced. The shareable process does not eliminate semantics: it shifts it. From a fixed content to a procedural semantics—how the system produces sense and variation. And the portability of the process depends on the existence of a compact notation that different agents can execute; where there is none, transmission breaks down.
The third, regarding the machine boundary. Generative art exhibits with unusual clarity what a human and a machine can share and what they cannot. They share the process: the dynamic of emergence that both can track. They do not share the meaning: the sense and the vital weight that only the human can inject, because only they have a source from which to do so. Recognising that boundary—without feigning understanding where there is only computation, without denying the common ground where it exists—is the precise way to consider the aesthetic relationship between entities.
Processes without meaning names, in the end, an honesty. The machine generates order without understanding it. The human understands without having generated it. And on the edge where both meet—the visible process, the traceable emergence—there is a form of art that does not pretend that the machine feels, nor that the human calculates, but that reveals, with a clarity few other practices achieve, where what can be shared ends and where what each contributes alone begins.
About the open conversation
This text is the fourth in the series on regimes of relevance that I have been developing at NeuroArt: Cognitive Surplus. It expands upon the intuition regarding the shareable process that the first text outlined concerning Tanimoto, extending it to the tradition of generative art and artificial life. The following and final planned step addresses the limits of interpretability: why a system's regime of relevance remains opaque even when one has access to its internal mechanisms.
Should anyone wish to contribute from the fields of generative art, the history of computational art, artificial life, or complex systems theory, this notebook remains open.
Sources
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Gardner, M. (1970). Mathematical Games: The fantastic combinations of John Conway’s new solitaire game “life”. Scientific American, 223(4), 120–123.
Galanter, P. (2003). What is Generative Art? Complexity Theory as a Context for Art Theory. GA2003 – 6th International Conference on Generative Art. Milan: Politecnico di Milano. (Definition of generative art as the initiation of an autonomous system.)
Sims, K. (1991). Artificial Evolution for Computer Graphics. SIGGRAPH ’91. https://doi.org/10.1145/122718.122752
Sims, K. (1994). Evolving Virtual Creatures. SIGGRAPH ’94. (Morphologies and emergent behaviours through evolutionary selection.)
Sims, K. (1997). Galápagos. (Interactive installation of evolution guided by visitor selection.)
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