Mostrando entradas con la etiqueta AI-generated art. Mostrar todas las entradas
Mostrando entradas con la etiqueta AI-generated art. Mostrar todas las entradas

miércoles, 17 de junio de 2026

The Algorithm and the Aura: Walter Benjamin in the Age of Artificial Intelligence

 

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 Luciano Ambrosini's chapter (2025): The Aura in the Algorithm: Reimagining Walter Benjamin's Aesthetic Theory in the Era of Artificial Intelligence


Introduction: can a machine have an aura?

In 1936, the German philosopher Walter Benjamin published an essay that would become one of the cornerstones of 20th-century art theory: The Work of Art in the Age of Mechanical Reproduction. There he introduced the concept of the aura: that unique, unrepeatable quality linked to the physical presence of the work and its tradition, which is lost when technical reproduction allows copies to be multiplied indefinitely. Photography and cinema, for Benjamin, were symptoms of this loss, but also bearers of new political functions.

Today, nearly a century later, we face an even more radical transformation. Artificial intelligence does not merely reproduce existing works; it generates new works without the need for a physical original. What, then, remains of the aura? Can an algorithm, with its cold mathematical efficiency, produce something that deserves that name?

Luciano Ambrosini, in a chapter published in 2025 within the volume Dialectic of Digital Enlightenment: Reclaiming Radical Philosophy for Our Times (Springer), addresses precisely this question (Ambrosini, 2025). The author proposes the apparently paradoxical notion of an "algorithmic aura" : a form of authenticity that resides not in the work's materiality or its history, but in its computational origin and the singularity of its generative process.

This approach, as we shall see, is not a mere extrapolation of Benjaminian thought, but a critical revision that attempts to account for the specificities of AI-generated art. From the perspective of our research on the S/Y/C model and Surgical Philosophy, Ambrosini's analysis offers valuable tools for thinking about the relationship between technique, authenticity, and aesthetic experience in the context of creative machines (Mallo, 2023, 2025, 2026a, 2026b).


Benjamin and the aura: a necessary reminder

Before delving into Ambrosini's proposal, it is worth recalling the central elements of Benjaminian theory. For Benjamin, the aura of a work of art is linked to its unique presence in space and time, to its unrepeatable "here and now". This presence confers on the work an authority, an authenticity, that tradition had considered inalienable.

Technical reproduction —lithography, photography, cinema— destroys that uniqueness. By multiplying copies, it separates the work from its original context, makes it accessible to the masses, strips it of its ritual character and gives it a political and pedagogical function. Benjamin saw in this process not only a loss, but also a gain: the possibility of an art in the service of collective emancipation, freed from the privileges of the elite.

AI-generated art, Ambrosini argues, poses an unprecedented challenge to this dichotomy. It is not a matter of reproducing an original, but of generation without an original. The AI work is not a copy of something earlier; it is, in principle, a novel creation. But neither does it have the physical uniqueness of traditional art, because it can be easily replicated and modified. Where, then, does the aura reside?


The "algorithmic aura": a productive paradox

Ambrosini's answer is the proposal of an "algorithmic aura" . This is not a contradiction in terms, but an extension of the Benjaminian concept to adapt it to the technical conditions of the present.

What would this new form of aura consist of? Ambrosini suggests that the authenticity of an AI work resides not in its physical materiality, but in the singularity of its generative process. Each time an algorithm produces a work, it does so on the basis of a dataset, parameters, and an architecture that are unique. Even if the code is the same, the conditions of generation —training data, random seeds, previous interactions— can lead to unrepeatable results.

The "algorithmic aura" would thus be the trace of that unique process, the mark of a non-human intelligence that nevertheless produces something that challenges us, moves us, makes us think. It is not the aura of physical presence, but the vestige of a computational complexity that cannot be reduced to mere repetition.

This notion, as Ambrosini himself warns, is not without problems. Can a machine have "authenticity" in the Benjaminian sense? Are we not projecting onto the algorithm categories that only make sense in the context of human subjectivity? The author offers no definitive answers, but opens a path of inquiry worth exploring.


Fluid authorship and digital democratisation

One of the most relevant aspects of Ambrosini's analysis is his treatment of the question of authorship in AI-generated art. Benjamin already noted that technical reproduction dilutes the figure of the traditional author, making it possible for works to circulate and be transformed by multiple agents.

With artificial intelligence, we witness an even deeper dissolution of the authorial figure. Authorship is no longer attributed to an individual consciousness, but is distributed along a chain of decisions and influences that includes the system's architecture, the provenance of the training data, the parameters selected by the operator, and even the randomness inherent to the generative process. The resulting work has no single father, but rather a diffuse network of contributors. This dispersal is not an anomaly, but the defining trait of a new creative ecology where the boundary between the human creator and the technical medium becomes unrecognizable. Ambrosini captures this transformation under the notion of "fluid authorship" , a concept that dismantles the figure of the creative genius and demands a thorough revision of inherited legal and aesthetic categories.

This fluidity has, however, a positive correlate: the democratisation of art. AI puts creative tools within reach of people without technical or artistic training. Anyone with access to a computer can generate images, music, or texts that previously would have required years of learning. This, as Ambrosini notes, challenges the power structures of the art world —galleries, museums, critics— and opens up the possibility of more inclusive and diverse expression.

Nevertheless, the author also warns of the dangers of this democratisation: the homogenisation of styles, the dependence on the same datasets, the risk that AI perpetuates biases and exclusions. The algorithm, like any tool, can be used to emancipate or to dominate. The difference lies in how we use it.


Ethics, bias, and human agency

Ambrosini devotes a section of his chapter to the ethical considerations of AI-generated art (Ambrosini, 2025). From a Benjaminian perspective, he analyses issues such as algorithmic bias, intellectual property, and the potential manipulation of audiences.

Algorithmic bias is one of the most pressing problems. AI systems learn from historical data, and that data reflects the inequalities and prejudices of our societies. An algorithm trained on Western artworks will generate images that reproduce those canons, ignoring or distorting other traditions. Technical democratisation can thus become a reproduction of cultural hegemony, rather than genuine plurality.

The question of intellectual property is equally complex. If an AI generates a work that closely resembles that of a human artist, who is infringing copyright? The programmer? The user? The system itself? Current laws are not prepared to answer these questions, and Ambrosini suggests we need to rethink the legal framework from scratch.

Finally, the author addresses the need to preserve human agency in the creative process. AI should not replace the artist, but expand their capacities. The danger is not that machines will replace us, but that we will delegate to them decisions that only humans can make —what is beautiful, what is meaningful, what deserves to be remembered.


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

Ambrosini'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 (Mallo, 2023, 2025, 2026a, 2026b). His notion of the "algorithmic aura" can be reinterpreted in light of our three dimensions.

The S (Survival) dimension reminds us that human aesthetic experience is rooted in homeostatic needs. Art moves us because it activates our autonomic nervous system, because it regulates our emotions, because it helps us survive symbolically. AI can generate formally complex objects, but it does not experience that need for regulation. Its "aura", if it exists, is not that of a living being seeking its balance, but that of a machine executing functions.

The Y (Symbolon) dimension is central to understanding the difference between human and algorithmic authenticity. Symbolon is an act of recognition through shared codes, a bridge between subjectivities. When a human contemplates a work, they do not only process forms; they recognise intentions, emotions, meanings. AI can produce works that we interpret as if they had intention, but that intention is projected by us. The "algorithmic aura" is, at bottom, an effect of our interpretation, not an intrinsic property of the algorithm.

The C (Wholeness) dimension points to the human need to close forms, to find coherent totalities. Art satisfies us when it achieves that wholeness. AI can generate formally closed objects, but it does not experience the drive toward wholeness. Its "aura" is, in this sense, a simulacrum of human wholeness.

Surgical Philosophy invites us to make a precise analytical cut in Ambrosini's proposal. It is not about rejecting the notion of "algorithmic aura" as false, but about distinguishing levels. At the level of technical production, the concept can be useful for describing the singularity of generative processes. At the level of full aesthetic experience, however, the "aura" remains the patrimony of the living. AI can surprise us, move us, inspire us. But the source of that emotion is not in the algorithm, but in our encounter with the algorithm. It is we who project onto the machine the capacity to move us. And that act of projection is, perhaps, the most human thing about art.


Implications for future research

Ambrosini's chapter opens several promising lines of work. The first is the need for empirical research on how viewers perceive and value AI-generated art. Do they attribute "aura" to these works? Under what conditions? What factors modulate that attribution?

The second line is the development of new legal and ethical frameworks for AI art. Benjaminian categories —original, copy, author, spectator— need to be revised in light of generative technologies. Ambrosini offers clues, but the detailed work remains to be done.

The third line is the exploration of new forms of collaboration between humans and machines. If AI cannot have an aura by itself, perhaps it can help create hybrid works where the human and the algorithmic intertwine. The future of art is not the replacement of the human by the machine, but synergy between the two.

From our perspective, this research should also incorporate a neurobiological dimension. It is not enough to analyse concepts; we must study what happens in the brain when we contemplate an AI work. Are the same regions activated as in human art? Are there differences? Can we measure "aura" in terms of neuronal activation? These are open questions, and answering them is part of the challenge of contemporary neuroaesthetics.


Final considerations: aura as encounter, not as property

Luciano Ambrosini's chapter reminds us that Walter Benjamin's thought, formulated nearly a century ago, remains extraordinarily fertile for thinking about our technological present. His concept of aura, conceived for the age of mechanical reproduction, can be reinterpreted for the age of algorithmic generation.

The notion of "algorithmic aura" is undoubtedly provocative. It forces us to ask what value we attribute to AI-generated works, and why. But perhaps Ambrosini's greatest achievement is to show that the aura is not a fixed property of works, but an effect of our relationship with them. If something has an aura, it is not because it exists in itself, but because we, the viewers, bestow it upon it.

And that is, perhaps, the deepest lesson for our research on the origin of art. Human art does not have an aura because it is "authentic" in a metaphysical sense, but because we treat it as such. We invest it with meaning, connect it with our history, make it part of our world. AI can produce objects that we also invest with meaning. But that act of investiture —that symbolon— remains human. And as long as it does, art, even that generated by algorithms, will continue to be a testimony of our capacity to find meaning in chaos.


References

Ambrosini, Luciano (2025). The Aura in the Algorithm: Reimagining Walter Benjamin’s Aesthetic Theory in the Era of Artificial Intelligence. In Bhabani Shankar Nayak, Dialectic of Digital Enlightenment: Reclaiming Radical Philosophy for Our Times. Cham: Springer Nature Switzerland. pp. 133-160. https://philpapers.org/rec/AMBTAI 

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. (2025). Arte y biología: Una aproximación neurofilosófica al origen de la experiencia estética. Lopez Mallo, Javier Bernabé. https://www.amazon.com/dp/B0E8Y5WZMK

Mallo, B. (2025). Art and biology: A neurophilosophical approach to the origin of aesthetic experience. Lopez Mallo, Javier Bernabé. https://www.amazon.com/dp/B0E8Y6C2XN

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



 

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

 

 

sábado, 13 de junio de 2026

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

 

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 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


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