Summary:
As generative artificial intelligence rapidly synthesizes paintings, music, and literature, a new theoretical framework published in AI & Society reframes what human creative cognition truly means. The paper presents the “decoupling thesis,” arguing that while AI can bypass years of technical training to produce accomplished works, it separates the act of creating from the personal cognitive and experiential transformation that historically defined artistic practice. The most lasting creative value, the author contends, lies less in finished artifacts than in the human journeys of perception, practice, and interpretation that reshape how people engage with the world.
Key Facts:
- The Decoupling Thesis: Generative AI severs the traditional coupling between producing high-level aesthetic works and the long-term cognitive development artists underwent to master their craft.
- Process Over Product: As algorithms commodify polished deliverables, the emphasis of human artistry shifts from technical execution to experimentation, sensory exploration, and philosophical reflection.
- Redesigning Creative AI: The study calls on technologists and cultural institutions to judge AI tools not only by speed or realism, but by their capacity to spark curiosity, deepen perception, and encourage embodied interaction with the environment.
Source: The Hebrew University of Jerusalem
Generative artificial intelligence can now assemble gallery-ready oil paintings, compose complex symphonic passages, write evocative poetry, and draft architectural designs in seconds. Across many measures, these machine-produced artifacts match works that once required decades of disciplined apprenticeship.
This capability forces a central question: if algorithmic systems can generate convincing art instantly, what remains unique about human creativity? Amit R. Zoran, PhD, associate professor at the Rachel and Selim Benin School of Computer Science and Engineering at the Hebrew University of Jerusalem, addresses this question by shifting the debate away from whether machine outputs qualify as “art” and toward what creative practice does for human minds and cultures.
The “Decoupling Thesis”
Historically, learning an art demanded sustained deliberate practice, sensorimotor refinement, emotional growth, and perceptual recalibration. A painter gradually restructured visual processing and internal models of light and form; a cellist integrated fine motor control, acoustic feedback, and affect into a coherent expressive skill. Those embodied transformations were inseparable from the works those creators produced.
Zoran’s decoupling thesis proposes that generative AI disrupts this unity. AI enables individuals to generate refined aesthetic objects without undergoing the specific developmental, perceptual, and emotional pathways that once conditioned those forms. In other words, AI makes sophisticated artifacts accessible without the long, formative human process that used to accompany their creation.
Zoran writes that this separation does not imply the end of human creativity. Instead, it invites a re-evaluation of where creative value resides. When technical barriers fall away, the scarcity shifts from executional skill to imaginative interpretation, conceptual depth, and the relational meanings that humans bring to artifacts.
Reimagining Technology as an Experiential Catalyst
Rather than replacing human creative impulse, algorithmic tools can be recast to amplify multisensory exploration and collaborative discovery. The paper highlights hybrid projects where computation expands bodily and environmental awareness instead of producing yet more consumable imagery.
One example describes an installation centered on a living tree that becomes a shared point of engagement. The work layers scent, taste, environmental field recordings, adaptive AI-generated music, and spatial projections to heighten visitors’ attention to the living system. In these projects, technology functions as a sensory amplifier, prompting participants to notice patterns and relationships that ordinary perception might miss.
By routing generative fluency back into embodied, situated experience, such tools can help restore the developmental aspects of creativity—encouraging people to change how they sense, think, and relate to the world rather than merely consuming polished outputs.
Metrics for the Next Generation of Creative Tools
Zoran’s analysis challenges how engineers, educators, and cultural organizations evaluate creative technologies. He proposes several shifts:
- Engineering Benchmarks: Move beyond latency, photorealism, and benchmark scores to measure whether systems provoke curiosity, connect disparate ideas, and support reflective practice.
- Cognitive Reallocation: Use AI to offload routine execution so artists can invest saved time in conceptual experimentation, critique, and developing richer interpretive frameworks.
- Education and Assessment: Cultural institutions and universities should broaden evaluation criteria to reward the introspective and developmental arcs of students’ work, not only the final artifact.
If technical execution no longer determines artistic worth, a new opportunity emerges: to treat creative practice as a path for ongoing human transformation. Under conditions of symbolic abundance, the most valuable creative endeavors may be those that use generative tools to deepen embodied perception, social connection, and experiential learning.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The journal paper was reviewed in full.
- Additional context was added by the editorial staff.
About this AI and creativity Research:
- Media Contact: Yarden Mills
- Source: Hebrew University of Jerusalem
- Image Credit: Image credited to Neuroscience News
- Original Research: AI & Society (Oct 1, 2026). “More than we can make: Generative AI, artistic forms, and artistic becoming.” Author: Amit R. Zoran.
- DOI: 10.1007/s00146-026-03379-x
Abstract
More than we can make: Generative AI, artistic forms, and artistic becoming
Public discussion of generative AI and creativity has centered on artifacts: who or what produced an image or text, whether machine outputs count as art, and how authorship and value should be assigned. Drawing on aesthetics, craft theory, anthropology, human–computer interaction, hybrid craft, digital fabrication, and rematerialization, this article argues that artistic practice historically involved two intertwined dimensions.
First, artistic forms stabilize and transmit meaning through artifacts. Second, artistic becoming encompasses the developmental and transformative processes through which new modes of perception, interpretation, and experience arise in makers, recipients, and cultures. The central claim—the decoupling thesis—is that for most of history these dimensions were contingently coupled: producing sophisticated forms normally required the maker’s becoming. Generative AI loosens this coupling by enabling such forms to appear without the specific developmental pathways that traditionally conditioned them.
Rather than signaling the end of creativity, the decoupling thesis relocates creative value and makes visible aspects of practice that mass production and technical demands have long obscured. The article places generative AI within a broader history of hybrid and distributed creativity, develops the thesis across multiple levels, and argues for a normative orientation: in an era of symbolic abundance, the most important creative practices are those that channel generative fluency back into embodied, situated experience.