EVALUATING ARTISTIC AUTHENTICITY IN MACHINE-AIDED SCULPTURES
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6898Keywords:
Artistic Authenticity, Machine-Aided Sculpture, Computational Aesthetics, Human–AI Co-Creation, Generative DesignAbstract [English]
he question of artistic originality with machine-aided sculptures involves a strict, multidimensional study involving the intersection of human creativity and algorithmic determination of aesthetic forms that lead to hybrids. With AI-assisted design, generative modelling and robotic fabrication gaining more and more influence over the practice of sculpture, the issue of authorship, intentionality, material fidelity and interpretive meaning is raised. This paper advances a conceptual and methodological model that combines qualitative expert judging and quantitative computational evaluation to measure authenticity in three categories of sculptures, fully human-created, machine-aided, and fully computer-generated sculptures. The study uses refined collection of sculptures and their creation logs, metadata of processes, and parameters of generative models that allow structural comparisons of human- machine agency. Subtle aspects of authenticity, like narrative coherence, expression intentionality and perceived material integrity are evaluated by expert judgment of artists and curators and critics, and structural complexity, stylistic deviation, and form-generation transparency are computed. Findings have shown that machine-assisted sculptures usually exist in a hybrid zone of authenticity, in which the intent of human action is still present, but an introduction of new aesthetic marks happens through the use of algorithmic forms. Analysis of agreement shows that there is moderate correspondence between expert and computational scores but there are patterns of cultural bias and differing tolerance to the involvement of the machines in audience based interpretation. In general, the paper highlights that originality in artificial intelligence-generated sculpture is not lost but rather reconfigured in new structures that should consider co-authorship, repetitive digital art, and new aesthetic reasoning.
References
Al-Kfairy, M., Alomari, A., Al-Bashayreh, M., Alfandi, O., and Tubishat, M. (2024). Unveiling the Metaverse: A Survey of User Perceptions and the Impact of Usability, Social Influence, and Interoperability. Heliyon, 10, Article e31413. https://doi.org/10.1016/j.heliyon.2024.e31413 DOI: https://doi.org/10.1016/j.heliyon.2024.e31413
Alkhwaldi, A. F. (2024). Investigating the Social Sustainability of Immersive Virtual Technologies in Higher Educational Institutions: Students’ Perceptions Toward Metaverse Technology. Sustainability, 16(2), Article 934. https://doi.org/10.3390/su16020934 DOI: https://doi.org/10.3390/su16020934
Cheng, Y., Chen, J., Li, J., Li, L., Hou, G., and Xiao, X. (2023). Research on the Preference of Public Art Design in Urban Landscapes: Evidence from an Event-Related Potential Study. Land, 12(10), Article 1883. https://doi.org/10.3390/land12101883 DOI: https://doi.org/10.3390/land12101883
De Fino, M., Galantucci, R. A., and Fatiguso, F. (2023). Condition Assessment of Heritage Buildings Via Photogrammetry: A Scoping Review from the Perspective of Decision Makers. Heritage, 6(11), 7031–7066. https://doi.org/10.3390/heritage6110367 DOI: https://doi.org/10.3390/heritage6110367
Galani, S., and Vosinakis, S. (2024). An Augmented Reality Approach for Communicating Intangible and Architectural Heritage Through Digital Characters and Scale Models. Personal and Ubiquitous Computing, 28(2), 471–490. https://doi.org/10.1007/s00779-024-01792-x DOI: https://doi.org/10.1007/s00779-024-01792-x
Gong, Z., Wang, R., and Xia, G. (2022). Augmented Reality (AR) as a Tool for Engaging Museum Experience: A Case Study on Chinese Art Pieces. Digital, 2(1), 33–45. https://doi.org/10.3390/digital2010002 DOI: https://doi.org/10.3390/digital2010002
Kovács, I., and Keresztes, R. (2024). Digital Innovations in E-Commerce: Augmented Reality Applications in Online Fashion Retail—A Qualitative Study Among Gen Z Consumers. Informatics, 11(3), Article 56. https://doi.org/10.3390/informatics11030056 DOI: https://doi.org/10.3390/informatics11030056
Matthews, T., and Gadaloff, S. (2022). Public Art for Placemaking and Urban Renewal: Insights from Three Regional Australian Cities. Cities, 127, Article 103747. https://doi.org/10.1016/j.cities.2022.103747 DOI: https://doi.org/10.1016/j.cities.2022.103747
Newman, M., Gatersleben, B., Wyles, K., and Ratcliffe, E. (2021). The Use of Virtual Reality in Environmental Experiences and the Importance of Realism. Journal of Environmental Psychology, 79, Article 101733. https://doi.org/10.1016/j.jenvp.2021.101733 DOI: https://doi.org/10.1016/j.jenvp.2021.101733
Sovhyra, T. (2022). AR-Sculptures: Issues of Technological Creation, their Artistic Significance and Uniqueness. Journal of Urban Culture Research, 25, 40–50.
Sylaiou, S., Dafiotis, P., Fidas, C., Vlachou, E., and Nomikou, V. (2024). Evaluating the Impact of XR on user Experience in the Tomato Industrial Museum “D. Nomikos.” Heritage, 7(3), 1754–1768. https://doi.org/10.3390/heritage7030082 DOI: https://doi.org/10.3390/heritage7030082
Uriarte-Portillo, A., Ibáñez, M.-B., Zataraín-Cabada, R., and Barrón-Estrada, M.-L. (2022). Higher Immersive Profiles Improve Learning Outcomes in Augmented Reality Learning Environments. Information, 13(5), Article 218. https://doi.org/10.3390/info13050218 DOI: https://doi.org/10.3390/info13050218
Wang, Y. (2022). The Interaction Between Public Environmental Art Sculpture and Environment Based on the Analysis of Spatial Environment Characteristics. Scientific Programming, 2022, Article 5168975. https://doi.org/10.1155/2022/5168975 DOI: https://doi.org/10.1155/2022/5168975
Wang, Y., and Lin, Y.-S. (2023). Public Participation in Urban Design with Augmented Reality Technology Based on Indicator Evaluation. Frontiers in Virtual Reality, 4, Article 1071355. https://doi.org/10.3389/frvir.2023.1071355 DOI: https://doi.org/10.3389/frvir.2023.1071355
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Copyright (c) 2025 Sakshi Pahariya, Ms. Meeta Kharadi, Shikha Gupta, Sukhman Ghumman, Dr. V. Sathiya, Vaishali Pawan Wawage
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