Artificial intelligence is increasingly being used to support art classes in schools – whether through the evaluation of student work, feedback on techniques, or assistance with creative development. The goal is to relieve teachers and provide objective feedback.
At first, the AI seems to be a helpful addition: it analyzes formal criteria such as color choice, proportions, and composition rules and gives precise suggestions. But over time, an unexpected problem emerges: the AI primarily evaluates artworks according to predefined norms and patterns, while creative deviations, personal expressions, or cultural diversity are hardly considered. As a result, innovative or unconventional works are systematically rated lower. Students feel discouraged, and artistic freedom is restricted. Moreover, the AI lacks the ability to adequately capture the subjective and emotional aspects of art. Teachers, developers, and education experts face the challenge of understanding the technical and pedagogical causes of these effects and assessing the impact on creativity, motivation, and the role of the teacher in the classroom.
Question:
Which technical and pedagogical factors can cause AI-supported evaluation systems in art classes to restrict creative diversity and individual expressions despite their potential, and how do these factors influence the requirements for algorithm design, integration of human expertise, transparency, and promotion of creativity in school education?
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