The rapid advancement of generative artificial intelligence (AI) presents significant challenges as well as opportunities in education. This paper examines the current state of AI technology as it relates to education, with a particular focus on transformer models and their implications for teaching and learning within the creative disciplines.

While technological innovations have come and gone before, the enormous disruptive nature of this particular technological development is underlined by two key paradoxes: the Black Box Paradox, which highlights our limited understanding of transformer efficacy and therefore why AI models work as well as they do, and the Deep Double Descent Paradox, which challenges traditional notions of AI model training and improvement and emphasizes our incomplete understanding about the limits of AI.

Given these unprecedented technological developments and their potential impacts, it is of critical importance that educators reevaluate their approach to teaching and learning. In this paper we propose a framework for adapting educational approaches to address these challenges.

Our approach consists of three core principles:
1. Critical Skill Enhancement: As AI systems become increasingly proficient at content generation, we argue for a renewed emphasis on developing students' critical evaluation skills. This includes fostering advanced capabilities in critical reading, visual analysis, auditory discernment, and higher-order thinking processes.
2. Process-Centric Pedagogy: We posit that shifting focus from final outputs to the creative process itself is crucial in an AI-augmented environment. This principle advocates for increased implementation of rigorous design critique sessions and process-oriented evaluations across diverse disciplines, emphasizing the unique human elements of creativity that AI cannot replicate.
3. Agile Institutional Structures: To effectively respond to rapid technological shifts, we propose that educational institutions must optimize for organizational flexibility and expedited decision-making processes. This principle calls for a critical reassessment of traditional academic structures in favor of more adaptable models.

Our analysis suggests that these principles can serve as a foundation for educational institutions to effectively prepare students for the evolving demands of creative fields. By cultivating critical skills, emphasizing creative processes, and fostering institutional agility, educators can equip the next generation of creatives with the tools necessary to navigate and shape the emerging technological landscape.

This paper contributes to the ongoing discourse on the future of creative education in the face of technological disruption. It offers a structured approach for educators, administrators, and policymakers to proactively address the challenges and opportunities presented by generative AI and related technologies. Our framework not only addresses the immediate challenges posed by AI but also aims to foster a more resilient and adaptive approach to creative education in the face of future technological disruptions.

Keywords: Generative AI, Creative Education, Critical Skills, Process-Centric Pedagogy, Institutional Agility, Technological Uncertainty.