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 Hengran Yang's article (2025): Artificial intelligence art robots: the future of technological art or the end of the human artist?
Introduction: replacement or collaboration?
In 2018, a portrait generated by artificial intelligence was auctioned at Christie's for $432,500. The work, titled Portrait of Edmond de Belamy, was created by the French collective Obvious and presented a classical appearance —a man with a blurred face, dressed in a dark jacket— reminiscent of Old Regime painting. Its final price far exceeded the initial estimate, and the event was interpreted by many as the starting signal of a new era: the era of art without an artist.
That same year, a robot named Ai-Da —with feminine features, articulated arms, and cameras for eyes— began to draw and paint using deep learning algorithms. Soon after, it would exhibit at the Venice Biennale. The question that these events made inevitable is no longer a futuristic speculation, but an urgent debate: are we witnessing the twilight of the human artist? Or is technology opening new paths for an expanded, hybrid, unprecedented creativity?
Hengran Yang, in an article published in 2025 in the International Theory and Practice in Humanities and Social Sciences, addresses precisely this question . His goal is twofold: on the one hand, to trace the historical evolution of AI-generated art —from the algorithmic experiments of the 1960s to Generative Adversarial Networks (GANs) and contemporary robot artists—; on the other, to assess whether these technologies represent an existential threat to human art or, rather, an opportunity to rethink creativity in collaborative terms.
Yang's conclusion is nuanced but clear: artificial intelligence is not destined to replace the human artist, but to complement them. Its technical capacities are impressive, but they lack something fundamental that only an embodied body, a personal history, and a cultural sensitivity can provide: genuine emotional expression and the ability to infuse shared meaning. Hence the metaphor that gives this review its title: brushes may be made of silicon, but the hands that guide them remain flesh. And in this tension —between the algorithmic and the organic— the future of art is being played out.
From the perspective of our research on the S/Y/C model and Surgical Philosophy, this article offers an opportunity to contrast two approaches: Yang's, focused on technological evolution and sociological implications, and ours, which investigates the biological and symbolic bases of aesthetic experience (Mallo, 2023, 2025, 2026a, 2026b). The result, as we shall see, is complementarity rather than opposition.
A historical journey: from algorithms to Ai-Da
Yang undertakes a historical journey that helps contextualise the present. The first experiments in algorithmic art date back to the 1960s, when pioneers like Harold Cohen developed systems such as AARON, capable of generating autonomous drawings. These early approaches were, however, limited: the algorithms followed explicit rules programmed by humans, and their "creativity" was, at bottom, a projection of the programmer's decisions.
The qualitative leap came with the emergence of Generative Adversarial Networks (GANs), developed by Ian Goodfellow in 2014. This type of architecture, based on competition between two networks —one generating, one discriminating— allowed machines to learn to produce images, music, and texts with an unprecedented level of realism and variety. Notably, the Portrait of Edmond de Belamy was generated using a GAN trained on a dataset of 15,000 portraits painted between the 14th and 20th centuries.
The latest milestone in this journey are robot artists like Ai-Da, an anthropomorphic system capable of drawing and painting using deep learning algorithms. Ai-Da not only generates works; it presents them in galleries, gives interviews, and participates in panel discussions. Its existence raises an uncomfortable question: if a robot can behave like an artist —exhibiting, talking about its work, interacting with the public— how is it different from a human artist?
Yang's answer is that the difference is ontological: the robot has no consciousness, no emotions, no biography, no cultural sensitivity. Its behaviour is simulation, not expression. But simulation, the author warns, can be so effective that the public tends to treat it as if it were real. And therein lies the danger: that technology may make us forget what art, in its origin and function, means for human beings.
Authorship, creativity, and the shadow of intentionality
One of the most valuable contributions of Yang's article is his analysis of the philosophical and ethical questions raised by AI art . Among them, three stand out: authorship, creativity, and intentionality.
Authorship: Yang argues that the emergence of AI dissolves the classic figure of the individual author. Creative responsibility is fragmented and distributed across multiple instances: the system's architecture, the selection of training data, the adjustment of parameters, the operator's decisions, and even the random elements introduced by generative models. The result is a distributed agency network where human and mechanical contributions intertwine without one cancelling out the other. The inherited legal and aesthetic categories —designed for a world of singular authors and original works— fall short in the face of this new complexity.
Creativity: can a machine be creative? Yang answers with a nuance. Machines can generate statistical novelty —unforeseen combinations of learned elements— but they cannot generate ontological novelty —something that radically breaks with the past, that introduces a new way of seeing the world. Human creativity is always, to some extent, transgressive. AI creativity is, for now, combinatorial.
Intentionality: this is the most delicate point. Yang maintains that AI systems do not possess intentionality in the philosophical sense of the term. They do not pursue goals, make deliberate decisions, or 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. And without intentionality, Yang argues, there is no art in the fully human sense.
This lack is not necessarily a flaw. AI can be a powerful tool for human artists, expanding their capacity for exploration, offering them unexpected variations, freeing them from tedious tasks. But the place of the artist —as a source of intentionality, as an embodied subject, as a moral and affective agent— remains, for now, exclusively human.
The emotional and cultural dimension: what AI cannot (yet) simulate
Another notable aspect of Yang's analysis is his emphasis on the emotional and cultural dimension of art. Machines can generate formally complex works, but they lack human emotional expression and cultural sensitivity .
What does this mean in practice? An algorithm can paint a winter landscape, but it has never felt cold. It can compose a funeral march, but it has never lost anyone. It can write a love poem, but it has never loved. Human art is born of lived experience, of the body that feels, of memory that hurts and celebrates. AI, for its part, operates on data, not on experiences. The Portrait of Edmond de Belamy is visually interesting, but behind it there is no biography, no anguish, no desire for transcendence. There is a loss function, an optimiser, a dataset of 15,000 portraits.
Cultural sensitivity is equally irreducible. A work of art does not float in an abstract void; it belongs to a tradition, dialogues with other works, is inscribed in a shared history. AI can learn stylistic patterns, but it cannot understand the cultural meaning of those patterns. It does not know why certain forms move us in one context and not another, nor how an artistic tradition transforms over time in response to social, political, or technological changes.
This limitation does not invalidate AI art, but it does place it in its proper place: not as a substitute for human art, but as a tool for aesthetic exploration that expands the formal repertoire available to artists.
Towards human-machine collaboration: the future according to Yang
Yang's conclusion is explicit: AI will play a complementary, not competitive, role in the artistic ecosystem . The future is not the replacement of the human artist by the machine, but collaboration between them.
What would this collaboration consist of? Yang suggests several lines. First, human artists will be able to use AI as a creative assistant, generating variations, exploring stylistic possibilities, overcoming technical blocks. Second, AI can be used to democratise access to artistic creation, allowing people without technical or artistic training to express themselves. Third, AI can contribute to new forms of hybrid art, where the boundary between the human and the algorithmic becomes intentionally diffuse.
This optimistic vision is not naive. Yang warns of the risks: stylistic homogenisation that may result from dependence on the same datasets; the dispossession of the artist when the system is so autonomous that the human contribution is diluted; the commodification of creativity when AI-generated works flood the market.
To avoid these dangers, Yang proposes technological literacy for artists. It is not about everyone becoming programmers, but about understanding enough to use AI discerningly, to critique its results, to integrate it into their practice without losing themselves.
Connection with research on the origin of art (S/Y/C)
Yang's article 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 conclusions on the limits of AI can be reinterpreted in light of our three dimensions.
The S (Survival) dimension reminds us that human art is rooted in homeostatic needs. The artist creates because they feel —pain, joy, wonder, loss— and because they need to process those sensations to maintain balance. AI has no body, no vital needs. It can produce formal objects, but it does not respond to the survival drive that, in humans, impels creation.
The Y (Symbolon) dimension is central to understanding the difference between human expression and algorithmic generation. 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 manipulate symbols, but it does not inhabit the symbol. There is no one inside who recognises or is recognised. Human art is symbolon lived; AI art is symbolon simulated.
The C (Wholeness) dimension points to the human need to close forms, to find coherent totalities. Art satisfies us when it achieves that wholeness —when the form closes, the rhythm resolves, the meaning emerges. AI can generate formally closed objects, but it does not experience the drive toward wholeness. Its "work" is not the result of a longing, but of a calculation.
Surgical Philosophy invites us to make a precise analytical cut in Yang's debate. It is not about rejecting AI or accepting it uncritically, but about distinguishing levels. At the level of technical production, AI is a powerful tool. At the level of full aesthetic experience —involving survival, symbol, and wholeness— the place of the artist remains human.
Yang is right to point out the lack of intentionality and emotion in AI, but he does not delve into the biological bases of this lack. Our research provides that foundation: AI cannot have intentionality because intentionality is not a computable function, but an attribute of living systems that need to survive, symbolise, and achieve wholeness.
Final considerations: art as an encounter between bodies and meanings
Hengran Yang's article has the merit of offering a balanced and well-informed vision of AI-generated art. It falls neither into technophobic apocalypse nor into uncritical euphoria. It acknowledges the capacities of machines, but also their limits. And it proposes a future of collaboration, not replacement.
From our perspective, that future is desirable and probable. But for collaboration to be genuine, we must not lose sight of what human art has that is irreducible: its origin in a body that feels, its function in homeostatic regulation, its power to create shared symbols, its drive toward wholeness. AI can be an ally in this task, but it cannot undertake it by itself.
Art, ultimately, is not only a matter of producing beautiful objects. It is an encounter between embodied subjectivities. An encounter that requires someone to feel so that someone else can recognise that feeling. AI can facilitate the encounter, but it cannot occupy the place of either pole. Brushes may be made of silicon, but the hands that guide them —and the hearts that beat behind them— remain flesh.
And as long as we remember that, we can use algorithms without fear, but also without naivety. As tools, not as idols. As extensions of our creativity, not as substitutes for our condition.
References
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
Yang, Hengran (2025). Artificial intelligence art robots: the future of technological art or the end of the human artist? International Theory and Practice in Humanities and Social Sciences 2 (1):243-251. https://philpapers.org/rec/YANAIA-4
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