German philosopher Catrin Misselhorn argued during the “Pausar la IA” conference that generative artificial intelligence cannot create genuine art, producing instead what she defines as “fake art.” Her latest book, La inteligencia artificial y el fin del arte, published by Herder, examines these philosophical dilemmas through the framework of historical aesthetic theories, Pagina 12 reported.
Assessing the Impact of Generative AI on Creative Labor
- Misselhorn asserts that artificial intelligence systems lack the necessary consciousness and emotional capacity to assume aesthetic responsibility, rendering their outputs functional imitations rather than true artistic creations.
- The philosophical framework builds on concepts from Georg Hegel and Arthur C. Danto, adapting historical ideas about the end of art to the modern realities of algorithmic generation and mass-produced synthetic media.
- Commercial deployment of generative models trained on copyrighted works without authorization or compensation directly threatens the financial stability, exhibitions, and professional livelihoods of human artists and graphic designers.
The German researcher participated as an international speaker at the “Pausar la IA” event, held from 2 to 4 at the Auditorio Amigos del Bellas Artes. Organized by the Goethe-Institut, Fundación Medifé, and Fundación Andreani, the conference explored the friction between technological automation and traditionally human domains. Her newly translated text forms the concluding volume of a trilogy that previously addressed machine ethics and emotional empathy in artificial intelligence.
To analyze the current aesthetic, Misselhorn relies on historical aesthetic theory as analytical beacons. Hegel historically conceptualized art as a phase of the past destined to be superseded by philosophy, while twentieth-century theorist Arthur C. Danto adapted that perspective to accommodate Andy Warhol’s ready-mades. Danto’s assertion that the history of art reaches a concluding phase because everyday objects can become artworks forms the baseline for how modern algorithmic output disrupts traditional classification.
The Structural Boundaries of Turing Machines
Addressing predictions that artificial intelligence might eventually match human creative output, Misselhorn separates qualitative execution from ontological capacity. She maintains that even mediocre or derivative human art carries the fundamental requirement of authorship and aesthetic responsibility. Biological organisms possess consciousness and genuine emotional states, whereas Turing machine models calculate statistical patterns without subjective experience.
Calculations involving human emotionality and internal life remain outside the computational scope of current mathematical architectures. While advanced systems successfully simulate human behavioral patterns, they operate strictly within calculated computational parameters. Establishing an artwork’s identity and cultural value requires an author capable of actual feeling and thought, a criterion synthetic generators cannot fulfill.
Market Realities and Creative Labor Vulnerabilities
| Research Area | Core Investigation | Primary Conclusion |
|---|---|---|
| Moral Agency | Can AI make ethical choices? | Functional decisions are possible, but full moral responsibility is absent. |
| Emotional Empathy | Can AI develop genuine empathy? | It cannot feel empathy, though it can trigger empathetic reactions in humans. |
| Artistic Creation | Can AI produce authentic art? | It generates synthetic imitations lacking aesthetic responsibility. |
Beyond abstract philosophy, the mass generation of algorithmic media creates acute economic pressures for human creators. Commercial sectors, particularly graphic design and visual arts, face widespread displacement as automated models ingest copyrighted portfolios without artist consent or financial remuneration. This practice undermines traditional pathways for grants, gallery exhibitions, and professional recognition.
The systemic expansion of synthetic works threatens the institutional stability of artistic practice. When markets flood with algorithmic output that mimics authentic cultural artifacts, distinguishing genuine creative labor becomes increasingly difficult for society at large.
