Generative Visions: AI, Human Imagination, and the Future of Art

Abstract

This study critically examines the evolving relationship between Artificial Intelligence (AI) and contemporary art, exploring how computational systems are reshaping concepts of creativity, authorship, and aesthetic production. Tracing key historical developments—from Harold Cohen’s pioneering AARON program in the 1970s to contemporary practices employing deep learning and Generative Adversarial Networks (GANs)—the research provides a structured and contextualized overview of AI’s integration into artistic processes. Through case studies including Google’s DeepDream, works by the collective Obvious, and artists such as Mario Klingemann and Anna Ridler, the paper analyzes AI’s role as both a tool and a co-creator. Drawing on interdisciplinary insights from art theory, philosophy, and cognitive science—especially the work of Margaret Boden—the study interrogates long-standing assumptions about originality, intention, and human imagination in the context of machine-generated art. Ethical concerns such as dataset bias and algorithmic opacity are examined alongside curatorial and institutional responses to AI art. This research argues that AI-generated art emerges not from autonomous systems alone, but through complex human-machine collaborations that challenge traditional artistic paradigms.  Ultimately, the investigation contributes to a broader understanding of creativity in the digital age and offers a critical framework for navigating the cultural, philosophical, and technological implications of AI in art.