Beyond the ghostwriter: reimaging generative AI as a diagnostic coach in creative media

Abstract

The generative AI has completely changed the creative industries by allowing users to create advanced visual content with minimal effort, which leads to many beginner artists skipping the basics, such as observance, proportion, perspective and correction. This article evaluates the limits of current generative AI in creative education and proposes an approach where generative AI becomes a diagnostic coach instead. Drawing from the idea of skill degradation due to automation, the paper shows how overdependence on image-generating technologies can undermine artists from developing their artistic expertise. It further discusses how imaging technologies can be applied to analyze the drawings and find errors in composition and structure with the necessary feedback provided in real time. The AI-based application for drawing education can help students identify drawing mechanics problems while making sure the learner has the ultimate responsibility in making artistic decisions. A human-based model also works in cases where AI directs attention to problems without taking their place. In this article, it is claimed that instead of positioning AI as a mere instrument of automatic output, it is more reasonable to consider it as a guide for effective learning, which guarantees that skills can be developed whilst preserving the autonomy of creativity. Nevertheless, there are difficulties related to bias in datasets, diversity of styles, and excessive standardization which should be taken into account to make sure that these applications do not inhibit the personal way of expressing oneself artistically.