The integration of Artificial Intelligence (AI) into African Studies offers transformative potential for cultural preservation (Olukoya et al., 2025; Ndede, 2026), yet it risks the “flattening” of indigenous epistemologies and authenticities (Moatemsu & Nigamananda, 2026). This study investigates the re-mediation of Ìtàn Ìjàpá (Yorùbá tortoise folktales) through AI-generated videos. It explores the relational dynamics between the AI-content creators and digital audiences on TikTok and Facebook. Historically, Ìjàpá has served as a pedagogical and performative tool for negotiating Yorùbá morality and identity (Taiwo, 2019). However, as creators “re-code” these oral traditions into AI-generated videos, the figure of the trickster (Ìjàpá) becomes a site of tension between what is presented through our ancestral orature versus the modern day algorithmic AI architecture.
This research addresses a critical methodological gap in Digital Humanities: how to evaluate the “cultural accuracy” and “narrative authority” of AI-generated indigenous content. Adopting a Relational Digital Ethnographic framework, I move beyond a unidirectional analysis of AI “outputs.” Instead, I examine the “collaborative authority” (Kashaemei & Sousa, 2026) that emerges when AI-content producers, platform algorithms, and digital audiences interact. The study interrogates how the “uncanny” visuality of AI-generated characters triggers performative responses from Yorùbá audiences that either affirm or reject the digital “re-shelling” of their heritage.
Methodologically, the study employs a three-generational interview framework (Kashaemei & Sousa, 2026). By conducting paired interviews with AI-creators and viewers across different age cohorts, alongside traditional Yorùbá cultural custodians, the research explores how “authority” is renegotiated in networked spaces. This approach is synthesised with systematic observation of platform-specific engagement patterns on Facebook and TikTok, building on established methods for analysing creator-algorithm relationships (Jerasa & Burriss, 2024).
To conclude, this research is a response to the workshop’s call, moving from “description to design” focusing on the Yorùbá epistemologies utilising digital and relational methods. It argues that AI-generated folktales are not static digital artefacts but “relational events” that test the limits of Western-centric AI models. This study will also contribute to the decolonial project by questioning whether AI serves as a tool for cultural reclamation or a new frontier for indigenous displacement.