Generative AI skips human practice, divorcing art from the personal growth of creation

A computer scientist at the Hebrew University of Jerusalem argues that artificial intelligence fundamentally alters the meaning of human creativity by separating output from process. Amit Raphael Zoran, who builds fabrication tools in the university’s School of Computer Science and Engineering, presents this view in a new paper.A researcher says AI changes creativity by letting machines make art without the human effort usually needed. His work suggests that the effortless generation of images by machines may erode the personal transformation traditionally associated with making art.

What was released or claimed

Zoran’s paper presents a philosophical argument rather than experimental data. He claims that for most of history, the creation of sophisticated art required years of personal change in the maker. This historical linkage tied the artwork itself to the artist’s development. Generative models now break this link by producing high-quality results without requiring the creator to undergo years of training or practice.

Who it affects

The argument primarily concerns artists and creators who rely on the process of making art for personal growth. It also impacts viewers, who Zoran argues undergo changes in perception when engaging with art. Additionally, the paper addresses broader cultural shifts, noting how historical movements like Renaissance perspective reorganized how societies viewed space and objects.

What is still unknown

The paper does not provide empirical evidence to support its philosophical claims. Zoran acknowledges that his conclusions remain open to debate because the work is theoretical. It is unclear how this decoupling will specifically impact future artistic practices or cultural evolution, as the paper focuses on historical and philosophical analysis rather than predictive modeling or experimental results.

What changes, what does not

The material notes that earlier computer art, such as Harold Cohen’s AARON program, maintained the tie between maker and meaning by supplying precision while requiring human interpretation. Generative models differ by operating on recorded traces of human culture. These models produce images and music with qualities that once demanded years of training, effectively removing the necessity for that prolonged period of human skill acquisition and personal change.

Methods and limits

Zoran’s research tests a philosophical framework rather than a technical hypothesis. He splits art into the product and "artistic becoming," the latter defined as the change in a person through making or viewing art. The reported result is the assertion that AI severs the historical link between these two aspects.reported The stated limitation is the lack of experimental findings; the paper relies on historical analysis and philosophical reasoning, leaving its conclusions open to academic debate without empirical validation.