Assessing the Role of Artificial Intelligence in Augmenting Human Creativity in Computational Art Generation
Keywords:
Artificial intelligence, Creativity, Computational art, Co-creation, Creative augmentationSynopsis
Computational art generation driven by artificial intelligence (AI) is reshaping contemporary creative practices. This paper examines the role of AI in augmenting human creativity by analyzing its historical foundations, empirical developments, co-creative frameworks, cognitive evaluation metrics, and ethical considerations. Drawing on quantitative findings from creativity assessment studies and human–AI collaboration research, the study highlights how AI-based tools influence artistic productivity, creative diversity, and perceptual judgments of artistic value. The analysis positions AI not as a replacement for human creativity, but as an enabling partner that expands creative possibilities while introducing new conceptual and ethical challenges.
References
[1] Boden MA (1998) Creativity and artificial intelligence. Artificial Intelligence 103(1–2):347–356
[2] Colton S (2008) Creativity versus the perception of creativity in computational systems. AI and Society 23(2):195–200
[3] Potla, R.B. (2021). Blueprinting a Manufacturing Data Lakehouse: Harmonizing BOM, Routing, and Serialization Data for Advanced Analytics. International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences, 9(1), 1–12. https://doi.org/10.37082/IJIRMPS.v9.i1.232841
[4] Colton S, Pease A, Charnley J (2011) Computational creativity theory: The Creative Tripod. IEEE Intelligent Systems 27(3):51–57
[5] Cohen H (1995) The further exploits of AARON, painter. Stanford Humanities Review 4(2):141–158
[6] Cohen H (2010) What is an image? Proceedings of the International Joint Conference on Artificial Intelligence, Barcelona
[7] Edmonds E, Candy L (2010) Interactive art and creativity. Leonardo 43(5):470–476
[8] Candy L, Edmonds E (2002) Explorations in art and technology. Springer, London
[9] McCormack J (2005) Open problems in evolutionary music and art. Evolutionary Computation 13(4):381–393
[10] Uppuluri, V. (2018). The Future of Business Intelligence in Value-Based Care Models. Journal of Artificial Intelligence, Machine Learning & Data Science, 1(1), 3009–3015. https://doi.org/10.51219/JAIMLD/vijitha-uppuluri/623
[11] McCormack J, d’Inverno M (2012) On the future of computational creativity. Creativity and Cognition Conference Proceedings, ACM
[12] McCormack J, d’Inverno M (2014) Computers and Creativity. Springer, Berlin
[13] Lubart TI (2005) How can computers be partners in the creative process? International Journal of Human-Computer Studies 63(4–5):365–369
[14] Lubart TI (2015) Creativity and collaborative technologies. International Journal of Design Creativity and Innovation 3(1):47–53
[15] Manovich L (2001) The Language of New Media. MIT Press, Cambridge
[16] Manovich L (2013) Software Takes Command. Bloomsbury Academic, New York
[17] Galanter P (2003) What is generative art? Complexity theory as a context for art theory. Generative Art Conference Proceedings
[18] Johnson CG (2002) Fitness in evolutionary art and music. Proceedings of the Genetic and Evolutionary Computation Conference, Morgan Kaufmann
[19] Wiggins GA (2006) A preliminary framework for description, analysis and comparison of creative systems. Knowledge-Based Systems 19(7):449–458
[20] Ventura D (2016) Mere generation: Essential barometer or dated concept? Proceedings of the Seventh International Conference on Computational Creativity
Published
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
