Analysis of Digital Illustrator Nathaniel Jonathan's Responsibility from the Perspective of Work Originality - Robhani, Shidqan Aulia; Prasetyo, Abdul Rahman (IJESS International Journal of Education and Social Science, 2025)
The rapid development of Generative AI has intensified the unauthorized extraction of digital artwork as training data, creating vulnerabilities that threaten the integrity and career sustainability of young digital artists. This urgency is reinforced by the limited legal and practical protections available to prevent data scraping, style imitation, and attribution loss in the digital environments. This research aims to describe the creative process, publication strategies, copyright-related experiences, and the forms of artistic responsibilities demonstrated by digital artist Nathaniel Jonathan in maintaining the originality of his work within the development of technology. Employing qualitative research with a single case study approach, data is collected through in-depth interviews, online observation, and documentation study, which were then analyzed using Miles and Huberman's interactive model with source triangulation validation and member check. The findings show that Nathaniel’s creative process is done systematically and research based, while his publication practices emphasize transparency through process documentation, Creative commons licensing, and the routine inclusion of detailed tool and software descriptions in social media posts as informal markers of authorship. His encounters with plagiarism and AI reflect a critical yet pragmatic stance, where AI is used only for early ideation and always subjected to substantial modification and explicit disclosure. Overall, the study demonstrates that contemporary artistic responsibility involves integrating personal accountability, ethical communication, and community education to reinforce originality and support a sustainable digital art ecosystem in the era of generative technology.