By Horeb Anthony
AUSTIN, TX, UNITED STATES, January 13, 2026 /EINPresswire.com/ — Artificial intelligence has become a defining force in today’s creative industries, from generative imagery to automated video editing. Yet long before these tools entered the public spotlight, scholars were already examining how early forms of AI quietly reshaped creative work behind the scenes. A 2017 peer-reviewed study by Ms. Halimat Folake Usman is arguable one of the earliest structured analyses of how AI-assisted tools altered creative decision-making in episodic visual effects production. This research has received editorial recognition as Best Paper, highlighting its relevance as the media industry grapples with the implications of AI-driven creativity.
From Manual Craft to Algorithmic Assistance
For decades, visual effects in television were built through painstaking manual processes. Artists layered optical effects, keyed footage by hand, and made creative decisions shot by shot under intense production schedules. By the early 2000s, however, digital compositing platforms such as Nuke began to dominate episodic television workflows, introducing node-based systems and early automation. While these tools promised efficiency, they also raised a critical question: how does automation affect creative control? This question formed the foundation of Ms. Usman’s research, published in Scholars Journal of Arts, Humanities and Social Sciences in 2017.
What the Research Examined
Rather than focusing on algorithms alone, the study took a broader, interdisciplinary approach. Ms. Usman analyzed academic literature, industry publications, software development histories, and production practices spanning 2000 to 2016 to understand how AI-assisted compositing tools influenced creative workflows in episodic television. The research focused on tasks central to visual effects production, including rotoscoping, masking, colour grading, layering strategies, and final approval processes. By examining both technical adoption and artist perception, the study sought to explain who ultimately makes creative decisions when automation enters the pipeline
Key Findings
The study identified several important trends:
• Efficiency gains were most pronounced in technical tasks such as tracking, masking, and rotoscoping, allowing artists to meet increasingly compressed production timelines.
• Creative decision-making shifted from manual construction toward oversight and refinement of algorithmic outputs.
• Artists and directors expressed mixed responses—welcoming time savings while remaining cautious about reduced transparency and loss of fine-grained control.
• Hybrid human–AI workflows emerged as the most sustainable model, balancing automation with deliberate creative checkpoints.
Rather than eliminating artistic input, AI tools redefined it, placing greater emphasis on judgment, review, and intervention.
A Conceptual Framework for Human–AI Collaboration
One of the study’s most influential contributions was the introduction of a conceptual framework mapping creative tasks according to their level of automation and artistic complexity. The framework visually illustrated where automation supports creativity and where it risks constraining it. This model offered a new way for researchers, tool developers, and production teams to evaluate AI integration, not simply in terms of speed, but in terms of creative agency and decision authority.
Why This Matters Now
Although the research examined developments only up to 2016, its insights have taken on renewed significance. As generative AI tools increasingly enter film, television, and digital media production, questions about authorship, artistic control, and human oversight have become central industry concerns. Editors recognized the study’s lasting impact by awarding it a Best Paper, noting its role in shaping early understanding of human–AI collaboration in creative practice. The framework has since informed applied methodologies and professional workflows in visual effects production, demonstrating how theoretical research can influence real-world creative systems.
Looking Ahead
Ms. Usman’s work anticipated many of the debates now unfolding across creative industries. By framing AI not as a replacement for artists but as a collaborator requiring careful governance, the study continues to offer guidance for navigating technological change without sacrificing creative integrity. As media organizations, researchers, and policymakers seek responsible paths forward for AI in the arts, early foundational studies like this one provide essential historical context—and a reminder that the balance between automation and creativity has long been a human concern.
Publication Details
Usman, Halimat Folake. “Evaluating the Impact of AI-Assisted Compositing on Creative Decision-Making in Episodic Visual Effects.” Scholars Journal of Arts, Humanities and Social Sciences, vol. 5, no. 12, 2017, pp. 1968–1973. (2017). DOI:10.36347/sjahss.2017.v05i12.031.
Horeb Anthony
University of Mississippi
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