Neurofilosofía y Pensamiento Actual Neurophilosophy and Contemporary Thought

domingo, 14 de junio de 2026

What Is an AI-Generated Artwork? A Transdisciplinary Proposal

Bernabé Mallo

Doctor en Filosofía por la Universidad del País Vasco (UPV/EHU)
Investigador en neurofilosofía, evolución humana y origen del arte. / PhD in Philosophy – University of the Basque Country (UPV/EHU)
Researcher in neurophilosophy, human evolution, and the origins of art.

A review of Leonardo Arriagada's article (2025): Defining an AI-Generated Artwork: A Transdisciplinary Concept for Cognitive Science, Computer Science, and Art Theory

Introduction: the Tower of Babel of artificial intelligence

An AI-generated artwork is, for a computer scientist, a set of probabilistic outputs from a neural network. For a cognitive psychologist, a stimulus that provokes certain responses in the viewer. For an art theorist, an object that challenges traditional categories of authorship, intentionality, and creativity. Each discipline speaks its own language, and the result is often a Tower of Babel where communication is difficult and collaboration nearly impossible.

Leonardo Arriagada, in an article published in 2025 in the journal Calle 14: Revista de Investigación en el Campo del Arte, addresses precisely this problem . His goal is ambitious: to develop a transdisciplinary definition of an AI-generated artwork that serves as a conceptual bridge between cognitive science, computer science, and art theory.

Arriagada's proposal is structured around three essential elements: (1) the autonomous production by AI of a new and surprising idea or artifact; (2) the existence of an internal evaluation mechanism within the system itself; and (3) the consideration of that product as a candidate for appreciation by a human audience.

This definition, as we shall see, is not without philosophical problems, but it has the merit of offering a common starting point for disciplines that often speak without understanding each other. From the perspective of our research on the S/Y/C model and Surgical Philosophy, Arriagada's analysis is especially valuable because it forces us to clarify what we mean by "autonomy", "evaluation", and "appreciation" in the context of machine-generated art.

Why do we need a transdisciplinary definition?

Arriagada starts from a realization: the literature on AI-generated art is abundant but fragmented . Computer scientists focus on the technical aspects of generative algorithms (generative adversarial networks, transformers, diffusion models). Cognitive psychologists study how viewers perceive and value these works. Art theorists debate whether AI can be considered an author or whether its products deserve the status of art.

The problem is not merely academic. It has practical implications for copyright attribution, critical evaluation, conservation, and commercialization of these works. Without a common language, disagreements are inevitable and opportunities for interdisciplinary collaboration are lost.

Arriagada's proposal does not pretend to be the definitive definition, but rather a heuristic tool that allows researchers from different fields to dialogue on common ground. His approach is pragmatic: he does not ask what art is in essence, but rather what characteristics an AI-generated object must meet to be considered a legitimate candidate for artistic appreciation.

The three elements of the definition

Arriagada proposes that an AI-generated artwork must meet three conditions .

1. Autonomous production of novelty

The first element is that the AI must produce something new and surprising autonomously. This excludes cases where the system merely reproduces or combines existing patterns without generating true novelty. It also excludes cases where human control is so direct that the AI acts as a mere tool, not as an agent.

The notion of "autonomy" is key here, but also problematic. How autonomous must the AI be? Is it enough that there is no human intervention at the moment of generation, or must the system have learned its criteria on its own without supervision? Arriagada does not offer a definitive answer, but notes that the degree of autonomy can vary and that this variability should be the subject of empirical study.

2. Internal evaluation mechanism

The second element is that the AI must incorporate an internal evaluation mechanism. It is not enough for it to generate something new; the system must be able to evaluate its own productions, to discriminate between successful and unsuccessful results, to select those that deserve to be presented to the human audience.

This mechanism can be explicit (for example, a loss function that penalizes certain outputs) or implicit (for example, the model's own statistics). But without some kind of internal evaluation, the generation would be blind, and the result a mere product of chance.

The inclusion of this element is interesting because it introduces a form of weak intentionality in AI. The system has no consciousness or purposes, but its architecture incorporates value criteria that guide its production. This brings it, however vaguely, closer to the notion of "judgment" that in humans accompanies creativity.

3. Candidate for human appreciation

The third element is that the AI-generated product must be considered a candidate for appreciation by a human audience. Here Arriagada introduces a social and institutional factor. It is not enough for the AI to produce something novel and evaluate it internally. That something must be presented to humans who can appreciate it, interpret it, value it.

This element recognizes that art is, in part, a social institution. An AI-generated work that remains on a computer's hard drive without anyone seeing it is not art, just as Duchamp's readymade would not be art if no one had exhibited it in a gallery. Human appreciation is the act that completes the circuit, that turns a technical artifact into an aesthetic object.

Strengths and weaknesses of the proposal

Arriagada's definition has several strengths. First, it is operational: it provides criteria that can be applied empirically to classify specific cases. Second, it is inclusive: it does not a priori exclude any type of technique or style, as long as the three conditions are met. Third, it is transdisciplinary: it offers a common language for computer scientists, psychologists, and art theorists.

However, it also has important weaknesses. The most obvious is that the definition depends on notions ("novelty", "surprise", "autonomy", "appreciation") that are themselves controversial and require further precision. What counts as "surprise" for a machine? How do we measure "autonomy"? Who decides what is "worthy of appreciation"?

Furthermore, the definition does not directly address the question of intentionality in the strong philosophical sense. A system can have an internal evaluation mechanism without there being anyone "inside" who actually judges or values anything. Evaluation is a function, not an experience. And that distance between function and experience is, as we have seen in other reviews, crucial for distinguishing human art from machine art.

Connection with research on the origin of art (S/Y/C)

Arriagada's analysis resonates deeply with the research we have been developing on the S/Y/C model of neuronal functioning and the Law of Biological Coherence. His transdisciplinary definition can be reinterpreted in light of our three dimensions.

The S (Survival) dimension reminds us that human appreciation of art is not a purely cognitive act, but is rooted in homeostatic needs. When a human viewer "appreciates" an AI-generated work, their brain is processing stimuli that generate pleasure, activation, curiosity, or emotion. That processing is real, even if the work was made by a machine. Arriagada's definition, by including "human appreciation", implicitly recognizes this dimension.

The Y (Symbolon) dimension is central to understanding the gap between AI's internal evaluation and human appreciation. AI can have evaluation mechanisms that are mathematical functions, but not symbolon: there is no shared recognition, no emergent meaning from an encounter between subjectivities. Human appreciation, by contrast, is always symbolic: we see the work, interpret it, connect it with our personal and cultural history. That is something that AI, by itself, cannot generate. Symbolon —the act of recognition through shared codes— is the patrimony of embodied subjectivity.

The C (Wholeness) dimension points to the human need to close forms, to find coherence. When we appreciate a work, we seek in it a totality that satisfies us. AI can generate formally closed objects, but it does not experience the drive toward wholeness. Its "internal evaluation" is a calculation, not a longing.

Surgical Philosophy invites us to make a precise analytical cut in Arriagada's definition. It is not about rejecting it, but about distinguishing levels. At the level of technical production, the definition is useful: it allows us to identify which AI-generated objects deserve to be considered candidates for artistic appreciation. At the level of full aesthetic experience, however, the definition is insufficient, because it does not capture what human appreciation has that is embodied, symbolic, and yearning.

Arriagada offers a tool for building bridges between disciplines. That is valuable. But to understand art in its origin and its function, we need something more: a theory of embodied subjectivity, of lived intentionality, of the drive toward meaning. That is what our research attempts to contribute, with symbolon as a central concept.

Implications for future research

Arriagada's article opens several lines for future research . First, it suggests that the proposed definition should be applied to various types of AI-generated artworks to assess its scope and limits. An image generated by a neural network is not the same as a poetic text produced by a language model, or a symphony composed by an autonomous system. The definition should be able to encompass them all, or be adjusted to do so.

Second, Arriagada notes that the definition has implications for artistic practices . If human artists begin to collaborate with AI systems that meet the three conditions, how does their way of working change? Do they remain the authors, or is authorship distributed? What happens to the notion of "style" or "voice" when the machine can imitate any style?

These questions have no easy answers, and Arriagada's definition does not pretend to resolve them. His contribution is more modest but equally valuable: to provide a common ground for researchers from different disciplines to begin a dialogue. And that dialogue, as we know, is the condition of possibility for any significant advance.

Final considerations: the need for a common language

Leonardo Arriagada's article reminds us that, in such a novel and controversial field as AI-generated art, the first challenge is not to answer questions, but to formulate them well. And to formulate them well, we need clear and shared concepts. His proposal for a transdisciplinary definition is a step in that direction.

From our perspective, that definition is useful but incomplete. Useful because it allows communication between cognitive science, computer science, and art theory. Incomplete because it does not capture the embodied dimension of human aesthetic experience. AI can produce objects that meet Arriagada's three criteria, but those objects, when appreciated by a human, acquire a meaning that is not in the machine, but in the encounter between the work and a living subjectivity.

The origin of art, in the Homo species, was not the production of novel objects or the internal evaluation of autonomous systems. It was the need to express, to communicate, to share what one feels —it was the need for symbolon. That need remains, today, what defines the human against the artificial. And as long as we do not forget that, we can use AI as a tool without confusing it with the source.

References

Arriagada, L. (2025). Defining an AI-generated artwork: A transdisciplinary concept for cognitive science, computer science, and art theory. Calle 14: Revista de Investigación en el Campo del Arte, 20(38), 95–109. https://doi.org/10.14483/21450706.21009

Mallo, B. (2023). La construcción neuro-simbólica. Una aproximación al funcionamiento del cerebro desde una perspectiva multidisciplinar [Doctoral thesis, University of the Basque Country - Euskal Herriko Unibertsitatea]. ADDI Repository. http://hdl.handle.net/10810/62701

Mallo, B. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo. Lopez Mallo, Javier Bernabé. https://isbn.bibna.gub.uy/catalogo.php?mode=detalle&nt=57196

Mallo, B. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo [Kindle edition]. Amazon. https://www.amazon.com/dp/B0GYGTJD5C

Mallo, B. (2026b). From surgical philosophy to the law of biological coherence S/Y/C: Toward a study of the origin of art in the Homo lineage. Lopez Mallo, Javier Bernabé. https://isbn.bibna.gub.uy/catalogo.php?mode=detalle&nt=57197

Mallo, B. (2026b). From surgical philosophy to the law of biological coherence S/Y/C: Toward a study of the origin of art in the Homo lineage [Kindle edition]. Amazon. https://www.amazon.com/dp/B0GY89SZS1

Autor / Author

Bernabé Mallo
Doctor en Filosofía – Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)
Investigador independiente en neurofilosofía, evolución humana y origen del arte.

Bernabé Mallo
PhD in Philosophy – University of the Basque Country / Euskal Herriko Unibertsitatea (UPV/EHU)
Independent researcher in neurophilosophy, human evolution, and the origin of art.

Enlaces / Links

Página de autor Amazon / Amazon Author Page: https://www.amazon.com/author/bernabemallo
ORCID: https://orcid.org/0000-0001-9002-9728
Plataforma EHUenRed / Link EHUenRed: https://www.ehu.eus/es/web/masterrak-eta-graduondokoak/red-latinoamericana-de-posgrados
Canal YouTube / Channel YouTube: https://www.youtube.com/@neuroideas815
Canal YouTube / Channel YouTube: https://www.youtube.com/channel/UCBsf6OZ482NjST6QA-hvYtQ
Publicaciones y proyectos en desarrollo / Publications and projects:
https://www.amazon.com/author/bernabemallo
https://ehuenred.theglocal.network/ideas/el-origen-del-arte-en-el-cerebro-de-makapansgat-al-moma-del-primate-al-sapiens

¿Qué es una obra de arte generada por IA? Una propuesta transdisciplinar

Bernabé Mallo

Una reseña del artículo de Leonardo Arriagada (2025): Defining an AI-Generated Artwork: A Transdisciplinary Concept for Cognitive Science, Computer Science, and Art Theory

Introducción: la torre de Babel de la inteligencia artificial

Una obra generada por inteligencia artificial es, para un informático, un conjunto de salidas probabilísticas de una red neuronal. Para un psicólogo cognitivo, un estímulo que provoca ciertas respuestas en el espectador. Para un teórico del arte, un objeto que desafía las categorías tradicionales de autoría, intencionalidad y creatividad. Cada disciplina habla su propio lenguaje, y el resultado es a menudo una torre de Babel donde la comunicación es difícil y la colaboración, casi imposible.

Leonardo Arriagada, en un artículo publicado en 2025 en la revista Calle 14: Revista de Investigación en el Campo del Arte, aborda precisamente este problema . Su objetivo es ambicioso: desarrollar una definición transdisciplinar de obra de arte generada por IA que sirva como puente conceptual entre la ciencia cognitiva, la informática y la teoría del arte.

La propuesta de Arriagada se articula en torno a tres elementos esenciales: (1) la producción autónoma por parte de la IA de una idea o artefacto nuevo y sorprendente; (2) la existencia de un mecanismo de evaluación interno al propio sistema; y (3) la consideración de ese producto como candidato a la apreciación por parte de una audiencia humana.

Esta definición, como veremos, no está exenta de problemas filosóficos, pero tiene el mérito de ofrecer un punto de partida común para disciplinas que a menudo hablan sin entenderse. Desde la perspectiva de nuestra investigación sobre el modelo S/Y/C y la Filosofía Quirúrgica, el análisis de Arriagada resulta especialmente valioso porque nos obliga a precisar qué entendemos por "autonomía", "evaluación" y "apreciación" en el contexto del arte generado por máquinas.

¿Por qué necesitamos una definición transdisciplinar?

Arriagada parte de una constatación: la literatura sobre arte generado por IA es abundante, pero fragmentada . Los informáticos se centran en los aspectos técnicos de los algoritmos generativos (redes generativas antagónicas, transformadores, modelos de difusión). Los psicólogos cognitivos estudian cómo los espectadores perciben y valoran estas obras. Los teóricos del arte debaten sobre si la IA puede ser considerada autora o si sus productos merecen el estatus de arte.

El problema no es solo académico. Tiene implicaciones prácticas para la atribución de derechos de autor, la evaluación crítica, la conservación y la comercialización de estas obras. Sin un lenguaje común, los desacuerdos son inevitables y las oportunidades de colaboración interdisciplinar se pierden.

La propuesta de Arriagada no pretende ser la definición definitiva, sino una herramienta heurística que permita a investigadores de diferentes campos dialogar sobre un terreno común. Su enfoque es pragmático: no se pregunta qué es el arte en esencia, sino qué características debe reunir un objeto generado por IA para ser considerado un candidato legítimo a la apreciación artística.

Los tres elementos de la definición

Arriagada propone que una obra de arte generada por IA debe cumplir tres condiciones .

1. Producción autónoma de novedad

El primer elemento es que la IA debe producir algo nuevo y sorprendente de manera autónoma. Esto excluye los casos en los que el sistema se limita a reproducir o combinar patrones existentes sin generar verdadera novedad. También excluye los casos en los que el control humano es tan directo que la IA actúa como una mera herramienta, no como un agente.

La noción de "autonomía" es aquí clave, pero también problemática. ¿Cuán autónoma debe ser la IA? ¿Basta con que no haya intervención humana en el momento de la generación, o es necesario que el sistema haya aprendido sus criterios por sí mismo sin supervisión? Arriagada no ofrece una respuesta definitiva, pero señala que el grado de autonomía puede variar y que esta variabilidad debería ser objeto de estudio empírico.

2. Mecanismo de evaluación interno

El segundo elemento es que la IA debe incorporar un mecanismo de evaluación interno. No basta con que genere algo nuevo; el sistema debe ser capaz de evaluar sus propias producciones, de discriminar entre resultados exitosos y fallidos, de seleccionar aquellos que merecen ser presentados a la audiencia humana.

Este mecanismo puede ser explícito (por ejemplo, una función de pérdida que penaliza ciertas salidas) o implícito (por ejemplo, las propias estadísticas del modelo). Pero sin algún tipo de evaluación interna, la generación sería ciega, y el resultado, un mero producto del azar.

La inclusión de este elemento es interesante porque introduce una forma de intencionalidad débil en la IA. El sistema no tiene conciencia ni propósitos, pero su arquitectura incorpora criterios de valor que guían su producción. Esto la acerca, aunque sea vagamente, a la noción de "juicio" que en los humanos acompaña a la creatividad.

3. Candidato a la apreciación humana

El tercer elemento es que el producto generado por la IA debe ser considerado un candidato a la apreciación por parte de una audiencia humana. Aquí Arriagada introduce un factor social e institucional. No basta con que la IA produzca algo novedoso y lo evalúe internamente. Es necesario que ese algo sea presentado a humanos que puedan apreciarlo, interpretarlo, valorarlo.

Este elemento reconoce que el arte es, en parte, una institución social. Una obra generada por IA que permanece en el disco duro de un ordenador sin que nadie la vea no es arte, del mismo modo que un readymade de Duchamp no sería arte si nadie lo hubiera exhibido en una galería. La apreciación humana es el acto que completa el circuito, que convierte un artefacto técnico en un objeto estético.

Fortalezas y debilidades de la propuesta

La definición de Arriagada tiene varias fortalezas. En primer lugar, es operativa: proporciona criterios que pueden ser aplicados empíricamente para clasificar casos concretos. En segundo lugar, es inclusiva: no excluye a priori ningún tipo de técnica o estilo, siempre que cumpla las tres condiciones. En tercer lugar, es transdisciplinar: ofrece un lenguaje común para informáticos, psicólogos y teóricos del arte.

Sin embargo, también presenta debilidades importantes. La más evidente es que la definición depende de nociones ("novedad", "sorpresa", "autonomía", "apreciación") que son ellas mismas controvertidas y requieren ulterior precisión. ¿Qué cuenta como "sorpresa" para una máquina? ¿Cómo medimos la "autonomía"? ¿Quién decide qué es "digno de apreciación"?

Además, la definición no aborda directamente la cuestión de la intencionalidad en el sentido filosófico fuerte. Un sistema puede tener un mecanismo de evaluación interna sin que haya nadie "dentro" que realmente juzgue o valore nada. La evaluación es una función, no una experiencia. Y esa distancia entre función y experiencia es, como hemos visto en otras reseñas, crucial para distinguir el arte humano del arte de máquina.

Conexión con la investigación sobre el origen del arte (S/Y/C)

El análisis de Arriagada resuena profundamente con la investigación que venimos desarrollando sobre el modelo S/Y/C del funcionamiento neuronal y la Ley de coherencia biológica. Su definición transdisciplinar puede reinterpretarse a la luz de nuestras tres dimensiones.

La dimensión S (Supervivencia) nos recuerda que la apreciación humana del arte no es un acto puramente cognitivo, sino que está enraizada en necesidades homeostáticas. Cuando un espectador humano "aprecia" una obra generada por IA, su cerebro está procesando estímulos que le generan placer, activación, curiosidad o emoción. Ese procesamiento es real, aunque la obra haya sido hecha por una máquina. La definición de Arriagada, al incluir la "apreciación humana", reconoce implícitamente esta dimensión.

La dimensión Y (Symbolon) es central para entender el salto entre la evaluación interna de la IA y la apreciación humana. La IA puede tener mecanismos de evaluación que son funciones matemáticas, pero no symbolon: no hay reconocimiento compartido, no hay significado emergente de un encuentro entre subjetividades. La apreciación humana, en cambio, es siempre simbólica: vemos la obra, la interpretamos, la conectamos con nuestra historia personal y cultural. Eso es algo que la IA, por sí misma, no puede generar. El symbolon —el acto de reconocimiento mediante códigos compartidos— es patrimonio de la subjetividad encarnada.

La dimensión C (Completitud) apunta a la necesidad humana de cerrar formas, de encontrar coherencia. Cuando apreciamos una obra, buscamos en ella una totalidad que nos satisfaga. La IA puede generar objetos formalmente cerrados, pero no experimenta la pulsión hacia la completitud. Su "evaluación interna" es un cálculo, no un anhelo.

La Filosofía Quirúrgica nos invita a aplicar un corte analítico preciso a la definición de Arriagada. No se trata de rechazarla, sino de distinguir niveles. En el nivel de la producción técnica, la definición es útil: permite identificar qué objetos generados por IA merecen ser considerados candidatos a la apreciación artística. En el nivel de la experiencia estética plena, sin embargo, la definición es insuficiente, porque no capta lo que la apreciación humana tiene de encarnado, simbólico y anhelante.

Arriagada ofrece una herramienta para tender puentes entre disciplinas. Eso es valioso. Pero para comprender el arte en su origen y en su función, necesitamos algo más: una teoría de la subjetividad encarnada, de la intencionalidad vivida, de la pulsión hacia el sentido. Eso es lo que nuestra investigación intenta aportar, con el symbolon como concepto central.

Implicaciones para la investigación futura

El artículo de Arriagada abre varias líneas para la investigación futura . En primer lugar, sugiere que la definición propuesta debería ser aplicada a diversos tipos de obras de arte generadas por IA para evaluar su alcance y sus límites. No es lo mismo una imagen generada por una red neuronal que un texto poético producido por un modelo de lenguaje, o una sinfonía compuesta por un sistema autónomo. La definición debería ser capaz de abarcarlos a todos, o de ajustarse para hacerlo.

En segundo lugar, Arriagada señala que la definición tiene implicaciones para las prácticas artísticas . Si los artistas humanos empiezan a colaborar con sistemas de IA que cumplen las tres condiciones, ¿cómo cambia su forma de trabajar? ¿Siguen siendo ellos los autores, o la autoría se distribuye? ¿Qué ocurre con la noción de "estilo" o "voz" cuando la máquina puede imitar cualquier estilo?

Estas preguntas no tienen respuesta fácil, y la definición de Arriagada no pretende resolverlas. Su contribución es más modesta pero igualmente valiosa: proporcionar un terreno común para que investigadores de diferentes disciplinas puedan empezar a dialogar. Y ese diálogo, como sabemos, es la condición de posibilidad de cualquier avance significativo.

Consideraciones finales: la necesidad de un lenguaje común

El artículo de Leonardo Arriagada nos recuerda que, en un campo tan novedoso y controvertido como el arte generado por IA, el primer desafío no es responder preguntas, sino formularlas bien. Y para formularlas bien, necesitamos conceptos claros y compartidos. Su propuesta de una definición transdisciplinar es un paso en esa dirección.

Desde nuestra perspectiva, esa definición es útil pero incompleta. Útil porque permite la comunicación entre la ciencia cognitiva, la informática y la teoría del arte. Incompleta porque no capta la dimensión encarnada de la experiencia estética humana. La IA puede producir objetos que cumplan los tres criterios de Arriagada, pero esos objetos, cuando son apreciados por un humano, adquieren un significado que no está en la máquina, sino en el encuentro entre la obra y una subjetividad viva.

El origen del arte, en la especie Homo, no fue la producción de objetos novedosos ni la evaluación interna de sistemas autónomos. Fue la necesidad de expresar, de comunicar, de compartir lo que se siente —fue la necesidad de symbolon. Esa necesidad sigue siendo, hoy, lo que define lo humano frente a lo artificial. Y mientras no olvidemos eso, podremos usar la IA como herramienta sin confundirla con la fuente.

Referencias bibliográficas

Mallo, B. (2023). La construcción neuro-simbólica. Una aproximación al funcionamiento del cerebro desde una perspectiva multidisciplinar [Tesis doctoral, Universidad del País Vasco - Euskal Herriko Unibertsitatea]. Repositorio ADDI. http://hdl.handle.net/10810/62701

Mallo, B. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo [Versión Kindle]. Amazon. https://www.amazon.com/dp/B0GYGTJD5C

Autor / Author

Bernabé Mallo
Doctor en Filosofía – Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)
Investigador independiente en neurofilosofía, evolución humana y origen del arte.

Bernabé Mallo
PhD in Philosophy – University of the Basque Country / Euskal Herriko Unibertsitatea (UPV/EHU)
Independent researcher in neurophilosophy, human evolution, and the origin of art.

Enlaces / Links

sábado, 13 de junio de 2026

AI Art Through Danto's Lens: Rupture or Continuity?

Bernabé Mallo

A review of Raquel Cascales' article (2023): Interpreting AI-Generated Art: Arthur Danto's Perspective on Intention, Authorship, and Creative Traditions in the Age of Artificial Intelligence

Introduction: what would Danto have thought of AI-generated art?

Arthur C. Danto, one of the most influential philosophers of art of the 20th century, passed away in 2013, just before artificial intelligence began to make its mark on the world of aesthetic creation. He did not live to see paintings generated by neural networks, poems written by algorithms, or symphonies composed by autonomous systems. But his philosophy, as Raquel Cascales argues in an article published in 2023 in the Polish Journal of Aesthetics, offers valuable conceptual tools for interpreting this phenomenon .

Cascales asks: how would Danto have applied his ideas about contemporary art, intention, interpretation, and authorship to AI-generated works? And, beyond that, does the irruption of AI into art constitute a new rupture with previous traditions or, on the contrary, does it fall within the same narrative that Danto considered already concluded?

This article, as we shall see, does not offer definitive answers, but it does raise fundamental questions for the philosophy of art in the digital age. From the perspective of our research on the S/Y/C model and Surgical Philosophy, Cascales' analysis is especially valuable because it forces us to refine concepts —intention, authorship, tradition— that are central to understanding the origin of art and its future.

Danto and the end of art: a brief introduction

To understand the relevance of Cascales' analysis, it is necessary to recall some key ideas of Danto. The American philosopher is famous for his thesis of the "end of art" , which should not be misinterpreted as an apocalyptic prophecy. Danto did not argue that art had ceased to be produced or that it had lost its value. Rather, he argued that the master narrative that had guided the history of Western art —the pursuit of faithful representation, the expression of beauty, the exploration of form— had reached its end.

Contemporary art, since the advent of Duchamp's readymade, is characterised as posthistorical: it no longer progresses toward a determined end, but unfolds in an open field of possibilities where anything is permitted, as long as it is accompanied by an interpretation that establishes it as art. What defines a work as art, for Danto, is not any perceptible property, but its inscription in an art world and the interpretation that can be offered of it.

This conception has radical implications for the question of AI. If art is whatever can be interpreted as art within a tradition and a theory, then perhaps a work generated by an algorithm could, in principle, be considered art. But Danto also gave a central role to the intention of the author and belonging to a creative tradition. And here is where tensions arise.

Intention and authorship: can an algorithm have intentions?

Cascales analyses in detail the question of intentionality in AI-generated art . For Danto, the artist's intention is a crucial component of interpretation. Not just any object can be art, but only those that have been made with the intention of being art, or that can be interpreted as if they had been made with that intention within an appropriate historical and theoretical context.

The problem, as Cascales notes, is that AI systems do not have intentions in the human sense of the term. They do not pursue goals, they do not make deliberate decisions, they do not seek to communicate something to a viewer. They process data, optimise functions, generate outputs. But there is no one "inside" who wants to say something. Can an AI-generated work then be considered art in the Dantoian sense?

Cascales suggests that, at this point, Danto's philosophy shows its limits. If intention is indispensable, then AI art would not properly be art. But it is also possible to reinterpret the notion of intention, broadening it to include the intentions of the system's designers, or the uses that viewers make of the work. This is an open path, but not without difficulties.

The question of authorship is parallel. Who is the author of an AI-generated work? The programmer who designed the algorithm? The user who entered the parameters? The system itself? Cascales does not offer a single answer, but points out the complexity of the problem and the need to revise our traditional categories.

Creative tradition and rupture: a new chapter or the definitive end?

One of the most fascinating questions posed by Cascales is whether the irruption of AI into art constitutes a rupture with previous artistic traditions or, on the contrary, falls within the same posthistorical narrative that Danto considered already concluded .

On the one hand, it could be argued that AI represents something radically new. Never before have we had the possibility of delegating the generation of works to autonomous non-human systems. For some, this is an ontological change that redefines what it means to "create". AI is not a tool like the brush or the camera: it is an agent with a certain degree of autonomy, although not of consciousness.

On the other hand, it could be argued that AI is just the latest in a long series of technological innovations that have expanded the possibilities of art. Photography, cinema, and digital imaging were already received with scepticism and finally integrated into artistic practices. AI, from this perspective, would not be a rupture, but a continuation of the same logic of media expansion.

Cascales does not clearly opt for either option. Her main contribution is to show that Danto's philosophy provides a framework for formulating the question with precision, although not for answering it definitively. And that, in itself, is an advance.

Connection with research on the origin of art (S/Y/C)

Cascales' analysis resonates deeply with the research we have been developing on the S/Y/C model of neuronal functioning and the Law of Biological Coherence. The question of intention and authorship in AI art forces us to clarify what we understand by these notions and how they relate to the fundamental dimensions of our thesis.

The S (Survival) dimension reminds us that human artistic intention is not a purely rational or disembodied act. It is rooted in homeostatic needs: the artist creates because they feel, because they hurt, because they rejoice, because they need to process the world in order to survive in it. AI, lacking a body and vital needs, cannot have intentions in this full sense. Its "outputs" are not expressions of an internal state, but probabilistic calculations.

The Y (Symbolon) dimension is central to understanding authorship. The artist is, in essence, a living symbolon: a subject who inhabits symbols and shares them with others. The work of art is a symbolon that refers to a subjectivity that inhabited it. AI can manipulate symbols, but cannot inhabit them. Therefore, speaking of "authorship" in the case of AI is, at the very least, problematic.

The C (Wholeness) dimension speaks to the human need to close forms, to achieve coherent totalities. The artist seeks, through their work, to satisfy this drive. AI can generate formally closed objects, but does not experience the need for wholeness. Its "work" is a product, not an act.

Surgical Philosophy invites us to make a precise analytical cut in this debate. It is not about rejecting AI art nor accepting it uncritically. It is about distinguishing levels: the level of the product (the generated work) and the level of the process (the embodied creative act). At the first level, AI can produce artefacts that the artistic community may decide to call "art". At the second level, however, AI cannot occupy the place of the human artist, because it lacks the S, Y, C dimensions that define embodied creativity.

Cascales, by drawing on Danto, offers us a way to think about this distinction. Danto taught us that art is not only a matter of visible properties, but of interpretation and inscription in a tradition. AI can produce works that are interpreted as art within our practices. But what interpretation cannot replace is the absence of an intentional subjectivity that underpins them. And that absence, for those of us who value art as an expression of the living, is insurmountable.

Final considerations: art after Danto and after AI

Raquel Cascales' article has the merit of applying the Dantoian framework to the question of AI-generated art with rigour and balance. It falls neither into uncritical technological enthusiasm nor conservative rejection. It points out tensions and aporias, and invites us to continue thinking.

From our perspective, the question of whether AI produces art is not an empirical question, but a conceptual one. It depends on what we understand by art. If we understand art as a formal product that can be interpreted aesthetically, then AI can produce art. If we understand art as an act of expression of an embodied subjectivity, then AI cannot, in principle, produce art.

Our research on the origin of art in the Homo species inclines us toward the second option. Human art, from its earliest manifestations in Makapansgat or in the caves of the Palaeolithic, has been a testimony of life that knows itself alive. A testimony that implies a body that feels, a symbol that is inhabited, a wholeness that is yearned for. AI can imitate forms, but it cannot generate that source. Because that source is life itself.

And that, perhaps, is what Danto, with his sensitivity for grand narratives, would have understood. Posthistorical art is not art without an artist. It is art in which the artist, aware that all forms are possible, freely chooses to express their embodied, finite, mortal condition. AI cannot make that choice. And that is why, however sophisticated its algorithms, it cannot occupy the place of the creator.

References

Cascales, R. (2023). Interpreting AI-generated art: Arthur Danto's perspective on intention, authorship, and creative traditions in the age of artificial intelligence. Polish Journal of Aesthetics, 71(4), 17–29. https://doi.org/10.7311/2665-2023-4-17

Mallo, Bernabé. (2023). La construcción neuro-simbólica. Una aproximación al funcionamiento del cerebro desde una perspectiva multidisciplinar [Doctoral thesis, University of the Basque Country - Euskal Herriko Unibertsitatea]. ADDI Repository. http://hdl.handle.net/10810/62701

Mallo, Bernabé. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo. Lopez Mallo, Javier Bernabé. https://isbn.bibna.gub.uy/catalogo.php?mode=detalle&nt=57196

Mallo, Bernabé. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo [Kindle edition]. Amazon. https://www.amazon.com/dp/B0GYGTJD5C

Mallo, Bernabé. (2026b). From surgical philosophy to the law of biological coherence S/Y/C: Toward a study of the origin of art in the Homo lineage. Lopez Mallo, Javier Bernabé. https://isbn.bibna.gub.uy/catalogo.php?mode=detalle&nt=57197

Mallo, Bernabé. (2026b). From surgical philosophy to the law of biological coherence S/Y/C: Toward a study of the origin of art in the Homo lineage [Kindle edition]. Amazon. https://www.amazon.com/dp/B0GY89SZS1

Autor / Author

Bernabé Mallo
Doctor en Filosofía – Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)
Investigador independiente en neurofilosofía, evolución humana y origen del arte.

Bernabé Mallo
PhD in Philosophy – University of the Basque Country / Euskal Herriko Unibertsitatea (UPV/EHU)
Independent researcher in neurophilosophy, human evolution, and the origin of art.

Enlaces / Links

El arte de la IA a la luz de Danto: ¿ruptura o continuidad?

Bernabé Mallo

Una reseña del artículo de Raquel Cascales (2023): Interpreting AI-Generated Art: Arthur Danto‘s Perspective on Intention, Authorship, and Creative Traditions in the Age of Artificial Intelligence

Introducción: ¿qué pensaría Danto del arte generado por IA?

Arthur C. Danto, uno de los filósofos del arte más influyentes del siglo XX, falleció en 2013, justo antes de que la inteligencia artificial comenzara a irrumpir con fuerza en el mundo de la creación estética. No llegó a ver las pinturas generadas por redes neuronales, los poemas escritos por algoritmos o las sinfonías compuestas por sistemas autónomos. Pero su filosofía, como sostiene Raquel Cascales en un artículo publicado en 2023 en la Polish Journal of Aesthetics, ofrece herramientas conceptuales de gran valor para interpretar este fenómeno .

Cascales se pregunta: ¿cómo habría aplicado Danto sus ideas sobre el arte contemporáneo, la intención, la interpretación y la autoría a las obras generadas por IA? Y, más allá de eso, ¿constituye la irrupción de la IA en el arte una nueva ruptura con las tradiciones anteriores o, por el contrario, se inscribe en la misma narrativa que Danto consideraba ya concluida?

Este artículo, como veremos, no ofrece respuestas definitivas, pero sí abre preguntas fundamentales para la filosofía del arte en la era digital. Desde la perspectiva de nuestra investigación sobre el modelo S/Y/C y la Filosofía Quirúrgica, el análisis de Cascales resulta especialmente valioso porque nos obliga a precisar conceptos —intención, autoría, tradición— que son centrales para entender el origen del arte y su futuro.

Danto y el fin del arte: una breve introducción

Para comprender la relevancia del análisis de Cascales, es necesario recordar algunas ideas clave de Danto. El filósofo estadounidense es famoso por su tesis del "fin del arte" , que no debe malinterpretarse como una profecía apocalíptica. Danto no sostenía que el arte hubiera dejado de producirse o que hubiera perdido su valor. Sostenía, más bien, que la narrativa maestra que había guiado la historia del arte occidental —la búsqueda de la representación fiel, la expresión de la belleza, la exploración de la forma— había llegado a su término.

El arte contemporáneo, desde la irrupción del readymade de Duchamp, se caracteriza por ser posthistórico: ya no progresa hacia un fin determinado, sino que se despliega en un campo de posibilidades abierto donde todo está permitido, siempre que sea acompañado de una interpretación que lo instituya como arte. Lo que define a una obra como arte, para Danto, no es ninguna propiedad perceptible, sino su inscripción en un mundo del arte y la interpretación que de ella puede ofrecerse.

Esta concepción tiene implicaciones radicales para la cuestión de la IA. Si el arte es aquello que puede ser interpretado como arte dentro de una tradición y una teoría, entonces quizás una obra generada por un algoritmo podría, en principio, ser considerada arte. Pero Danto también otorgaba un papel central a la intención del autor y a la pertenencia a una tradición creativa. Y aquí es donde surgen las tensiones.

Intención y autoría: ¿puede un algoritmo tener intenciones?

Cascales analiza con detalle la cuestión de la intencionalidad en el arte generado por IA . Para Danto, la intención del artista es un componente crucial de la interpretación. No cualquier objeto puede ser arte, sino solo aquellos que han sido hechos con la intención de ser arte, o que pueden ser interpretados como si hubieran sido hechos con esa intención dentro de un contexto histórico y teórico adecuado.

El problema, como señala Cascales, es que los sistemas de IA no tienen intenciones en el sentido humano del término. No persiguen fines, no toman decisiones deliberadas, no buscan comunicar algo a un espectador. Procesan datos, optimizan funciones, generan salidas. Pero no hay nadie "dentro" que quiera decir algo. ¿Puede entonces una obra generada por IA ser considerada arte en el sentido dantiano?

Cascales sugiere que, en este punto, la filosofía de Danto muestra sus límites. Si la intención es indispensable, entonces el arte de IA no sería propiamente arte. Pero también es posible reinterpretar la noción de intención, ampliándola para incluir las intenciones de los diseñadores del sistema, o los usos que los espectadores hacen de la obra. Esta es una vía abierta, pero no exenta de dificultades.

La cuestión de la autoría es paralela. ¿Quién es el autor de una obra generada por IA? ¿El programador que diseñó el algoritmo? ¿El usuario que introdujo los parámetros? ¿El sistema mismo? Cascales no ofrece una respuesta única, sino que señala la complejidad del problema y la necesidad de revisar nuestras categorías tradicionales.

Tradición creativa y ruptura: ¿un nuevo capítulo o el fin definitivo?

Una de las preguntas más fascinantes que plantea Cascales es si la irrupción de la IA en el arte constituye una ruptura con las tradiciones artísticas anteriores o, por el contrario, se inscribe en la misma narrativa posthistórica que Danto consideraba ya concluida .

Por un lado, podría argumentarse que la IA representa algo radicalmente nuevo. Nunca antes habíamos tenido la posibilidad de delegar la generación de obras en sistemas autónomos no humanos. Esto, para algunos, es un cambio ontológico que redefine qué significa "crear". La IA no es una herramienta como el pincel o la cámara: es un agente con cierto grado de autonomía, aunque no de conciencia.

Por otro lado, podría sostenerse que la IA es solo la última de una larga serie de innovaciones tecnológicas que han ampliado las posibilidades del arte. La fotografía, el cine, la imagen digital ya fueron recibidas con escepticismo y finalmente integradas en las prácticas artísticas. La IA, desde esta perspectiva, no sería una ruptura, sino una continuación de la misma lógica de expansión del medio.

Cascales no se decanta claramente por ninguna de las dos opciones. Su contribución principal es mostrar que la filosofía de Danto proporciona un marco para formular la pregunta con precisión, aunque no para responderla definitivamente. Y eso, en sí mismo, es un avance.

Conexión con la investigación sobre el origen del arte (S/Y/C)

El análisis de Cascales resuena profundamente con la investigación que venimos desarrollando sobre el modelo S/Y/C del funcionamiento neuronal y la Ley de coherencia biológica. La cuestión de la intención y la autoría en el arte de IA nos obliga a precisar qué entendemos por estas nociones y cómo se relacionan con las dimensiones fundamentales de nuestra tesis.

La dimensión S (Supervivencia) nos recuerda que la intención artística humana no es un acto puramente racional o desencarnado. Está enraizada en necesidades homeostáticas: el artista crea porque siente, porque le duele, porque le alegra, porque necesita procesar el mundo para sobrevivir en él. La IA, al carecer de cuerpo y de necesidades vitales, no puede tener intenciones en este sentido pleno. Sus "salidas" no son expresiones de un estado interno, sino cálculos probabilísticos.

La dimensión Y (Symbolon) es central para entender la autoría. El artista es, en esencia, un symbolon viviente: un sujeto que habita los símbolos y los comparte con otros. La obra de arte es un symbolon que remite a una subjetividad que la habitó. La IA puede manipular símbolos, pero no habitarlos. Por eso, hablar de "autoría" en el caso de la IA es, cuando menos, problemático.

La dimensión C (Completitud) nos habla de la necesidad humana de cerrar formas, de alcanzar totalidades coherentes. El artista busca, a través de su obra, satisfacer esa pulsión. La IA puede generar objetos formalmente cerrados, pero no experimenta la necesidad de completitud. Su "obra" es un producto, no un acto.

La Filosofía Quirúrgica nos invita a aplicar un corte analítico preciso en este debate. No se trata de rechazar el arte de IA ni de aceptarlo acríticamente. Se trata de distinguir niveles: el nivel del producto (la obra generada) y el nivel del proceso (el acto creativo encarnado). En el primer nivel, la IA puede producir artefactos que la comunidad artística puede decidir llamar "arte". En el segundo nivel, sin embargo, la IA no puede ocupar el lugar del artista humano, porque carece de las dimensiones S, Y, C que definen la creatividad encarnada.

Cascales, al recurrir a Danto, nos ofrece una vía para pensar esta distinción. Danto nos enseñó que el arte no es solo cuestión de propiedades visibles, sino de interpretación y de inscripción en una tradición. La IA puede producir obras que sean interpretadas como arte dentro de nuestras prácticas. Pero lo que la interpretación no puede suplir es la ausencia de una subjetividad intencional que las respalde. Y esa ausencia, para quienes valoramos el arte como expresión de lo vivo, es insalvable.

Consideraciones finales: el arte después de Danto y después de la IA

El artículo de Raquel Cascales tiene el mérito de aplicar el marco dantiano a la cuestión del arte generado por IA con rigor y equilibrio. No cae en el entusiasmo tecnológico acrítico ni en el rechazo conservador. Señala las tensiones y las aporías, y nos invita a seguir pensando.

Desde nuestra perspectiva, la pregunta de si la IA produce arte no es una pregunta empírica, sino conceptual. Depende de lo que entendamos por arte. Si entendemos el arte como un producto formal que puede ser interpretado estéticamente, entonces la IA puede producir arte. Si entendemos el arte como un acto de expresión de una subjetividad encarnada, entonces la IA no puede, por principio, producir arte.

Nuestra investigación sobre el origen del arte en la especie Homo nos inclina hacia la segunda opción. El arte humano, desde sus primeras manifestaciones en Makapansgat o en las cuevas del Paleolítico, ha sido un testimonio de la vida que se sabe viva. Un testimonio que implica un cuerpo que siente, un símbolo que se habita, una totalidad que se anhela. La IA puede imitar las formas, pero no puede generar esa fuente. Porque esa fuente es la vida misma.

Y eso, quizás, es lo que Danto, con su sensibilidad para las grandes narrativas, habría comprendido. El arte posthistórico no es el arte sin artista. Es el arte en el que el artista, consciente de que todas las formas son posibles, elige libremente expresar su condición encarnada, finita, mortal. La IA no puede hacer esa elección. Y por eso, por muy sofisticados que sean sus algoritmos, no puede ocupar el lugar del creador.

Referencias bibliográficas

Mallo, Bernabé. (2023). La construcción neuro-simbólica. Una aproximación al funcionamiento del cerebro desde una perspectiva multidisciplinar [Tesis doctoral, Universidad del País Vasco - Euskal Herriko Unibertsitatea]. Repositorio ADDI. http://hdl.handle.net/10810/62701

Mallo, Bernabé. (2026a). De la filosofía quirúrgica a la ley de coherencia biológica S/Y/C: Hacia una investigación sobre el origen del arte en la especie Homo [Versión Kindle]. Amazon. https://www.amazon.com/dp/B0GYGTJD5C

Autor / Author

Bernabé Mallo
Doctor en Filosofía – Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)
Investigador independiente en neurofilosofía, evolución humana y origen del arte.

Bernabé Mallo
PhD in Philosophy – University of the Basque Country / Euskal Herriko Unibertsitatea (UPV/EHU)
Independent researcher in neurophilosophy, human evolution, and the origin of art.

Enlaces / Links

jueves, 11 de junio de 2026

The Trace of the Soul: How We Detect Human Intentionality in Abstract Art

Bernabé Mallo

A review of the study by Straffon, Perea-García, den Blaauwen, and Kret (2026): Traces of Intentionality: Balance, Complexity, and Organization in Artworks by Humans and Apes

Introduction: can a chimpanzee be an artist?

In the 1950s, the psychologist Desmond Morris, known for his studies on animal behaviour, taught a chimpanzee named Congo to paint. Congo's works were exhibited in London galleries and even acquired by art collectors. The question raised then, and still open today, is unsettling: can a chimpanzee create art? What differentiates an accidental splatter of pigment from a work with aesthetic intention? And, above all, are we humans able to distinguish between the stroke of a non-human primate and that of a person?

A recent study by Larissa M. Straffon, Juan O. Perea-García, Tijmen den Blaauwen, and Mariska E. Kret (2026), published in the journal Topics in Cognitive Science, addresses precisely this question . The researchers presented participants with images of paintings made by humans without artistic training and by captive chimpanzees. The results are fascinating: participants were able to distinguish between the two with a remarkable degree of accuracy, and attributed higher levels of intentionality, organisation, and balance to human-made paintings.

This finding has profound implications for research on the origin of art. It suggests that the ability to produce and perceive cues of intentionality is not a privilege of great artists, but a ubiquitous feature of human visual production, even among those without artistic training. And that ability, as we shall see, connects directly with our thesis on the S/Y/C model and the Law of Biological Coherence.

The study: how do people distinguish human art from chimpanzee art?

Straffon and colleagues designed two complementary experiments to explore the ability of human beings to distinguish between paintings made by humans without artistic training and paintings made by chimpanzees .

Study 1: the visual discrimination task

In the first study, participants viewed pairs of paintings —one human and one chimpanzee— and had to identify which painting had been made by a human and which by a chimpanzee. The results were clear: participants successfully distinguished between human and chimpanzee paintings at a level significantly above chance .

It is important to note that the humans who made the paintings were not trained artists. They were individuals without specialised artistic training. This rules out the possibility that the distinction is based on mastery of sophisticated techniques or adherence to academic aesthetic canons. Even without training, the human stroke seems to leave an invisible signature that other humans can detect.

Study 2: the assessment of aesthetic criteria

In the second study, participants rated the paintings according to several criteria: perceived intentionality, organisation, balance, and complexity . In addition, they were asked which painting they preferred.

The results were consistent with those of the first study. Participants attributed significantly more intentionality, organisation, and balance to human-made paintings compared to chimpanzee-made paintings. Complexity, on the other hand, showed no systematic differences.

Furthermore, it was found that preference for a painting was directly related to the perception of intentionality. That is, participants preferred works that seemed more intentional, regardless of their origin. Since human paintings were perceived as more intentional, they were also preferred.

The authors identified three key characteristics that influence preference for abstract artwork: balance, complexity, and organisation . These three traits, they suggest, are indicators of the presence of an intentional mind behind the work.

What is intentionality and why do we detect it?

Intentionality is, in philosophical terms, the property of mental states of being directed toward something, of being about something. In the context of art perception, intentionality refers to our ability to infer that behind an object there is an agent who has acted with a purpose, who has wanted to achieve something, who has made decisions.

The study by Straffon and colleagues demonstrates that human beings are extraordinarily sensitive to cues of intentionality in visual production. Even when the works are abstract, even when they do not depict recognisable objects, even when they have been made by people without artistic training, we are able to detect the trace of the human mind.

This ability is not trivial. It has deep evolutionary roots. In the history of our species, the ability to infer the mental states of others —their intentions, their beliefs, their desires— has been crucial for cooperation, communication, and group survival. This ability is called theory of mind or social cognition.

Art, from this perspective, would not be a late cultural luxury, but an expression of this fundamental capacity. By creating art, human beings leave traces of their intentionality that others can read. Art is, in this sense, a means of communication that transcends explicit language.

Why doesn't chimpanzee art deceive?

If chimpanzees can paint —and they do, as Desmond Morris demonstrated with Congo— why are their works not perceived as equally intentional? The answer, the study suggests, has to do with the formal properties of the work.

Chimpanzees, when painting, produce configurations of strokes that, to human eyes, appear less organised and balanced. It is not that they lack patterns; it is that their patterns do not exhibit the same kind of compositional structure that humans generate, even without training.

Straffon and colleagues identified three key dimensions: balance, complexity, and organisation. Human paintings scored higher on these dimensions, and these dimensions predicted aesthetic preference. In other words, humans have an innate or early-acquired sensitivity to certain types of spatial configuration that we consider "well-made" or "harmonious".

This sensitivity is not arbitrary. It is likely grounded in principles of visual perception shared by our species —and perhaps by other primates, though with important differences. A clear example can be found in Gestalt psychology, which has shown how the human brain structures visual stimuli into global, coherent configurations. This is manifested through fundamental principles such as the law of continuity and the law of Prägnanz (or good form). Human art, even the most abstract, tends to satisfy these perceptual expectations more consistently than art generated by chimpanzees.

Connection with research on the origin of art (S/Y/C)

This experimental study connects directly with the research we have been developing on the S/Y/C model of neuronal functioning and the Law of Biological Coherence.

The ability to detect intentionality in art is, in essence, the ability to recognise the Y (Symbolon) dimension in action. Symbolon is not only the capacity to create symbols, but also to recognise symbolic activity in others. When we look at a painting and perceive that there is an intentional mind behind it, we are exercising our fundamental symbolic competence: the one that allows us to share meanings, coordinate actions, and build culture.

The three characteristics identified by Straffon and colleagues —balance, complexity, and organisation— can be reinterpreted in light of our dimensions:

Balance refers to the C (Wholeness) dimension. An achieved balance —between lights and shadows, between forms and spaces, between tension and rest— is a form of wholeness. The human brain finds pleasure in configurations that resolve tensions into a coherent totality. Human paintings, even those by untrained artists, tend to satisfy this search for balance more than those of chimpanzees.
Organisation also refers to the C (Wholeness) dimension, but also to Y (Symbolon). Organisation implies that the elements are not arranged by chance, but follow a structuring principle that can be recognised by others. That structure is an implicit symbol: it says "this has been made with a purpose". The ability to generate organisation is, therefore, a manifestation of the symbolic function.
Complexity is the most ambiguous. It showed no systematic differences between humans and chimpanzees, but it did influence aesthetic preference. Complexity is likely related to the S (Survival) dimension: our brain is designed to pay attention to stimuli with an optimal level of complexity —neither too simple (boring) nor too chaotic (overwhelming). Human art navigates this frontier with special skill.

Surgical Philosophy invites us to make a precise analytical cut of these results. It is not about concluding that chimpanzees "have no art" in a derogatory sense. It is about recognising that human visual production, even in its simplest and non-academic forms, bears the mark of an intentionality that distinguishes it from the production of other primates. That mark is, probably, the result of the evolution of our symbolic capacity —the same one that enables language, mathematics, myth, and, of course, art.

Implications for research on the origin of art

The study by Straffon and colleagues has profound implications for research on the origin of art in the Homo species.

First, it suggests that the ability to produce and perceive cues of intentionality is not a trait that appears only with the figurative art of the Upper Palaeolithic. It is already present in present-day humans without artistic training, and it is likely that it was present in our ancestors from very early phases of the evolution of the genus Homo.

Second, the study demonstrates that aesthetic sensitivity to properties such as balance, organisation, and complexity is not a product of culture or artistic education. It is a widespread capacity that manifests even in people without training. This supports the hypothesis that aesthetic experience has deep biological roots, predating the emergence of historical artistic traditions.

Third, the study opens the door to comparative research with other primates. If chimpanzees produce visual configurations that humans distinguish from their own, what about Neanderthals? Could we analyse their symbolic productions —such as the Gorham engravings or the paintings of the Ardales Cave— using these same criteria of intentionality, organisation, and balance? Our research on the origin of art in the Homo species could benefit from applying these analytical tools to archaeological remains.

Final considerations: the invisible signature of the human

The study by Straffon, Perea-García, den Blaauwen, and Kret reminds us that art is not only a matter of objects, but of minds. When we look at a painting —even an abstract painting made by someone without training— we do not only see forms and colours. We see, or intuit, the presence of another mind. We detect its intentionality, its organisation, its search for balance.

That ability to detect the other's mind in the stroke is, perhaps, the deepest origin of art. We are not born with brushes, but we are born with brains designed to leave traces and read the traces of others. Art is, in this sense, an extension of our cognitive sociability: a means of transmitting not only information, but mental states, emotions, intentions.

Chimpanzees can paint, and their paintings may be interesting from a formal point of view. But humans, even without training, paint differently. Their strokes carry an invisible signature that other humans can detect. That signature is that of a mind that seeks to organise the world, that yearns for balance, that leaves traces of its passage. It is the signature of life that knows itself alive and wants to record it.

And that, perhaps, is the true origin of art: the need to say, through the stroke, "I was here, I saw this, I felt this". A need that chimpanzees do not share, or not to the same degree, and that defines what is most human about the human.

References

Straffon, L. M., Perea-García, J. O., den Blaauwen, T., & Kret, M. E. (2026). Traces of intentionality: Balance, complexity, and organization in artworks by humans and apes. Topics in Cognitive Science, 18(2), e70022. https://doi.org/10.1111/tops.70022

Autor / Author

Bernabé Mallo
Doctor en Filosofía – Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)
Investigador independiente en neurofilosofía, evolución humana y origen del arte.

Bernabé Mallo
PhD in Philosophy – University of the Basque Country / Euskal Herriko Unibertsitatea (UPV/EHU)
Independent researcher in neurophilosophy, human evolution, and the origin of art.

domingo, 14 de junio de 2026

What Is an AI-Generated Artwork? A Transdisciplinary Proposal

Bernabé Mallo

A review of Leonardo Arriagada's article (2025): Defining an AI-Generated Artwork: A Transdisciplinary Concept for Cognitive Science, Computer Science, and Art Theory

Introduction: the Tower of Babel of artificial intelligence

Why do we need a transdisciplinary definition?

The three elements of the definition

1. Autonomous production of novelty

2. Internal evaluation mechanism

3. Candidate for human appreciation

Strengths and weaknesses of the proposal

Connection with research on the origin of art (S/Y/C)

Implications for future research

Final considerations: the need for a common language

References

Autor / Author

Enlaces / Links

¿Qué es una obra de arte generada por IA? Una propuesta transdisciplinar

Bernabé Mallo

Una reseña del artículo de Leonardo Arriagada (2025): Defining an AI-Generated Artwork: A Transdisciplinary Concept for Cognitive Science, Computer Science, and Art Theory

Introducción: la torre de Babel de la inteligencia artificial

¿Por qué necesitamos una definición transdisciplinar?

Los tres elementos de la definición

1. Producción autónoma de novedad

2. Mecanismo de evaluación interno

3. Candidato a la apreciación humana

Fortalezas y debilidades de la propuesta

Conexión con la investigación sobre el origen del arte (S/Y/C)

Implicaciones para la investigación futura

Consideraciones finales: la necesidad de un lenguaje común

Referencias bibliográficas

Enlaces / Links

sábado, 13 de junio de 2026

AI Art Through Danto's Lens: Rupture or Continuity?

Bernabé Mallo

A review of Raquel Cascales' article (2023): Interpreting AI-Generated Art: Arthur Danto's Perspective on Intention, Authorship, and Creative Traditions in the Age of Artificial Intelligence

Introduction: what would Danto have thought of AI-generated art?

Danto and the end of art: a brief introduction

Intention and authorship: can an algorithm have intentions?

Creative tradition and rupture: a new chapter or the definitive end?

Connection with research on the origin of art (S/Y/C)

Final considerations: art after Danto and after AI

References

Autor / Author

Enlaces / Links

El arte de la IA a la luz de Danto: ¿ruptura o continuidad?

Bernabé Mallo

Una reseña del artículo de Raquel Cascales (2023): Interpreting AI-Generated Art: Arthur Danto‘s Perspective on Intention, Authorship, and Creative Traditions in the Age of Artificial Intelligence

Introducción: ¿qué pensaría Danto del arte generado por IA?

Danto y el fin del arte: una breve introducción

Intención y autoría: ¿puede un algoritmo tener intenciones?

Tradición creativa y ruptura: ¿un nuevo capítulo o el fin definitivo?

Conexión con la investigación sobre el origen del arte (S/Y/C)

Consideraciones finales: el arte después de Danto y después de la IA

Referencias bibliográficas

Autor / Author

Enlaces / Links

jueves, 11 de junio de 2026

The Trace of the Soul: How We Detect Human Intentionality in Abstract Art

Bernabé Mallo

A review of the study by Straffon, Perea-García, den Blaauwen, and Kret (2026): Traces of Intentionality: Balance, Complexity, and Organization in Artworks by Humans and Apes

Introduction: can a chimpanzee be an artist?

The study: how do people distinguish human art from chimpanzee art?

Study 1: the visual discrimination task

Study 2: the assessment of aesthetic criteria

What is intentionality and why do we detect it?

Why doesn't chimpanzee art deceive?

Connection with research on the origin of art (S/Y/C)

Implications for research on the origin of art

Final considerations: the invisible signature of the human

References

Autor / Author

Enlaces / Links

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