Machine Thinking and Human Imagination: New Horizons for Creativity in the Digital Age

Abstract

The rise of generative artificial intelligence (AI) technologies challenges traditional notions of creativity and authorship in contemporary media art, prompting a philosophical reconsideration of these foundational concepts. This study aims to analyze and critique current interpretations of creativity and authorship in the context of machine-generated art, and to propose a theoretical framework for understanding emerging forms of distributed creativity. The research methodology involved the systematization of 30 scholarly publications (2020–2025), analysis of 15 media art projects involving AI (2020), and content analysis of eight detailed instances of human-machine creative collaboration. The findings led to the development of a typology of interaction models and a conceptual framework for hybrid authorship. Three dominant models of human-AI interaction were identified: instrumental (60%), collaborative (30%), and autonomous (10%). The study concludes that creative value lies not in algorithmic complexity but in conceptual depth and cultural relevance, reaffirming the centrality of human agency. The proposed model of hybrid authorship shifts away from binary human/machine distinctions, advocating for a procedural and network-based perspective. It outlines four types of hybrid authorship, instrumental, collaborative, distributed, and machine, each with distinct characteristics and implications for intellectual property and authorship rights. Practically, this research highlights the need for new legal frameworks, ethical guidelines for AI use in creative industries, and interdisciplinary training programs for digital-age artists. These measures are essential to navigate the evolving landscape of creativity and authorship in the age of AI.

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