Machine Thinking and Human Imagination

New Horizons for Creativity in the Digital Age

Bibliographic Data

ID22275207
AuthorsAdriana Skoryk (0000-0002-4158-8352, Ukrainian National Tchaikovsky Academy of Music), Inna Antipina (0000-0003-3845-9629, Ukrainian National Tchaikovsky Academy of Music), Oksana Havrosh (0000-0002-9456-1460, FORZA, Agency For Sustainable Development of The Carpathian Region), Yevgeniia Shunevych (0009-0009-6657-625X, Drohobych Ivan Franko State Pedagogical University), Viktor Shvets (0000-0001-8403-1813, Interregional Academy of Personnel Management)
Year2025
Volume7
IssueSI1
Pages115-139
Publication date2025-07-19
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal on Culture History and Religion (JOURNAL)
Journal identifiersISSN: 3028-1318 • E-ISSN: 3028-1318
PublisherInternational Journal on Culture, History, and Religion (PUBLISHER)
DOI10.63931/ijchr.v7isi1.156
OpenAlexW4412967165
LanguageEN
Citations received2
References cited32

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

Computational Creativity · Creativity · Data science · Epistemology · Generative grammar · Knowledge management · Political science · Social science · Sociology · Computer Science · Psychology · Social Psychology · Virtual Reality Applications and Impacts · Artificial Intelligence

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