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This paper explores the philosophical implications of machine learning text-to-image synthesis in a practice-based phenomenology of the computational poetics of a visual art process. It is hypothesized that artificial intelligence (AI) facilitated reflective image development fosters an anticipatory aesthetics in creative interactivity. The concept of AI-mediated “perspectival affordance” is introduced and its application to affective computing design emphasized. It is proposed that positioning intelligent systems as collaborative creativity tools promotes a dynamic interplay that envisions creativity as an anticipatory system, conceived of as those systems where exchange between artist and tool is mediated by future-oriented affective projection upon the system. The paper aims to establish a cognitive framework for AI-mediated creativity grounded in anticipatory interactivity, enhancing understanding of embodied cognition as mediated by AI in human-centered creativity support systems.
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Choi et al. (2023) studied this question.
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