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 the study by Li Gu and Yong Li (2022): Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention
Introduction: when the machine signs the work
Does our aesthetic judgment change if we know that a painting has been generated by an algorithm rather than by a human being? Do we feel the same pleasure before a traditional Chinese landscape if we discover that behind it there is not a human brush, but a neural network trained on thousands of examples? And what happens when the judge is an art expert —someone who has spent years developing their sensitivity and knowledge?
These questions, which only a decade ago might have seemed speculative, have become the subject of rigorous empirical research. A study published in 2022 by Li Gu and Yong Li in the journal Frontiers in Psychology addresses precisely this question . The researchers analysed how the identity of the author —human or artificial intelligence— affects aesthetic appreciation, purchase intention, and collection intention for paintings, in both traditional Chinese and Western styles.
The results are revealing and, in a certain sense, counterintuitive. For the general public without specialised artistic training, the author's identity does not modify their appreciation: they like the work or not, regardless of whether it was made by a person or a machine. However, for art experts, things change radically: they evaluate AI-generated paintings less favourably compared to those made by human artists.
This finding, as we shall see, has profound implications for our understanding of art, creativity, and the role of technology in aesthetic experience. From the perspective of our research on the S/Y/C model and Surgical Philosophy, the study by Gu and Li offers valuable empirical evidence on how the distinction between art as product and art as embodied process operates in practice.
The study: how was the research designed?
Gu and Li conducted two complementary experiments to explore the effect of author identity on the reception of AI-generated art .
Study 1: the general public
In the first study, participants had no professional art experience. They were shown two types of paintings: traditional Chinese style and Western style. In addition, information about the author was manipulated: in some cases it was said that the work had been created by a human artist; in others, by an artificial intelligence system. Participants had to rate their liking of the work, as well as their intention to purchase or collect it.
The results were clear. First, author identity did not significantly affect ratings. Participants liked a painting or not based on its perceived aesthetic qualities, not on whether it came from a machine or a person. Second, an ingroup preference bias was observed: participants showed a preference for traditional Chinese-style paintings over Western ones, a finding consistent with previous research on cultural preferences in empirical aesthetics .
This finding suggests that, for the non-specialist public, artificial intelligence is not perceived as a threat or an imposter. Its works are judged by the same criteria as human ones. The "aura" of the human artist, at least for this segment of the population, does not seem to confer automatic added value.
Study 2: art experts
The second study introduced a crucial variable: level of artistic expertise. Both non-specialists and experts (artists, critics, art historians, curators) participated. The results were drastically different.
Art experts evaluated AI-generated paintings less favourably compared to those made by human artists . Non-experts, as in the first study, showed no preference. In addition, significant interactions were found: the effect of author identity depended on the level of expertise, and also interacted with the style of the painting.
In other words, for those who know about art, who is behind the work matters. The machine, however sophisticated its algorithms, does not produce the same effect as the human hand. The knowledge and aesthetic sensitivity acquired through years of training and practice generate a discrimination that the general public does not make.
Why do experts see what the public does not see?
What explains this difference between experts and non-experts? Gu and Li suggest several hypotheses.
First, experts have internalised a narrative of art that places the artist as the creative subject at its centre. The history of art, at least since Romanticism, has exalted the figure of the individual genius, of expressive subjectivity, of the trembling hand, of the gaze that sees what others do not see. Artificial intelligence, by its very nature, lacks that biography, that interiority, that struggle with material. For the expert, the work is not only an object: it is the testimony of an encounter between a subject and the world.
Second, experts possess tacit knowledge about creative processes. They know what it costs to achieve an effect, what it implies to master a technique, what it means to find one's own voice. AI generation, however impressive, does not require that effort, that dedication, that training. It is, from this perspective, a shortcut: it produces brilliant results, but without the journey that gives them meaning.
Third, experts are more sensitive to signals of intentionality. They detect in the work the traces of the artist's decisions —the brushstroke, the choice of colour, the composition— and those traces speak to them of a mind behind them. In the AI-generated work, those traces do not refer to a subjectivity, but to an algorithm. And that, for the expert, impoverishes the experience.
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 difference between the response of the general public and that of experts can be interpreted in light of our three dimensions. The general public, lacking training that refines their perception of the Y and C dimensions, tends to value the work mainly for its superficial impact on the S dimension (pleasure, activation, novelty). If the AI-generated work is visually attractive, it fulfils that function, regardless of its origin.
Experts, on the other hand, have developed a sensitivity that allows them to discriminate between product and process. They do not only see the form: they intuit the work, the intention, the history behind it. Their appreciation integrates the three dimensions more fully:
S (Survival): The work must be aesthetically pleasing, but not only that. It must also connect with the deepest needs for meaning and transcendence.
Y (Symbolon): The work is a symbol, and the symbol only acquires its full meaning when it refers to a subjectivity that inhabited it. AI can manipulate symbols, but cannot inhabit them. The expert detects that absence.
C (Wholeness): The work must offer a sense of achieved totality, of internal coherence. But this wholeness is more satisfying when it is perceived as the result of a human search, not of a probabilistic calculation.
Surgical Philosophy invites us to make a precise analytical cut of these results. It is not about concluding that AI art is "bad" or that experts are elitists. It is about recognising that aesthetic experience is not univocal: there are different layers of appreciation, and each layer mobilises different dimensions of the nervous system. The general public stays on the surface; experts penetrate more deeply. Both are right at their level, but the expert's level is richer, more integrated, closer to what art, in its origin and in its function, has been for the human species.
Implications for the future of art and AI
The study by Gu and Li has important practical implications, both for creators of AI art and for professionals in the art world.
For AI system developers, the results suggest that, if their goal is for generated works to be appreciated by the general public, the current strategy —focusing on visual quality and stylistic variety— is sufficient. The public does not discriminate by origin.
However, if the goal is to reach the serious art market —collectors, museums, critics— things become more complicated. Experts do discriminate, and they do so negatively. To change this perception, improving algorithms will not be enough. It will be necessary, perhaps, to develop new narratives about what it means to "create" with AI, new ways of understanding authorship and intentionality in the context of autonomous systems.
For human artists, the results offer some consolation. Their expertise, their training, their ability to infuse intentionality into the work is still valued by those who truly understand art. AI has not replaced them in the heart of the art world, although it may be transforming its boundaries.
For art educators and critics, the study poses a challenge: how to train new generations of viewers to develop a sensitivity that goes beyond mere superficial appreciation? How to teach them to see not only the form, but the process, the intention, the history?
Final considerations: art as encounter, not only as object
The study by Gu and Li reminds us that art is not only a matter of beautiful objects, but of encounters between subjectivities. The general public can enjoy an AI-generated work without asking about its origin. But the expert, precisely because they have dedicated their life to understanding art, cannot ignore that question. And when they ask it, they discover that, in the machine-made work, something is missing.
That something is, perhaps, what defines human art in its origin and in its essence: the expression of an embodied, finite, mortal subjectivity that uses form to communicate the ineffable, to share the unsharable, to transcend the solitude of the flesh. Artificial intelligence can imitate forms, but it cannot generate that source. Because that source is life itself: a body that feels, a symbol that is inhabited, a wholeness that is yearned for.
Experts, by discriminating between human art and machine art, remind us of something that technological enthusiasm tends to forget: that art is not only a product, but a process; not only an object, but a testimony; not only a form, but an encounter. And that encounter, for now, remains the exclusive patrimony of the living.
References
Gu, L., & Li, Y. (2022). Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention. Frontiers in Psychology, 13, Article 999163. https://doi.org/10.3389/fpsyg.2022.999163
Gu, Li & Li, Yong (2022). Who made the paintings: Artists or artificial intelligence? The effects of identity on liking and purchase intention. Frontiers in Psychology 13.
https://philpapers.org/rec/GUWMT
López Mallo, J. 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
López Mallo, J. 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
López Mallo, J. 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
López Mallo, J. 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
López Mallo, J. 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
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