Vol. 1 No. 2 (2025)

Articles

From Algorithm to Canvas: An AI-Ethnographic Method for Indigenous Eco-Futurist Art

Published 2025-10-10

  • Metolo Foyet

Metolo Foyet
Department of Geography, University of Florida, Gainesville, FL 32611, USA

DOI: https://doi.org/10.64797/rwas.v1i2.79

Abstract

This study addresses a central problem in artificial intelligence (AI)-generated art: how machine-learning systems trained on culturally narrow datasets distort Indigenous ecological knowledge, yet are increasingly used to visualize conservation and environmental futures. To investigate this tension, the research develops and applies an AI-ethnographic method that treats AI not as a creator but as an interpretive actor whose outputs can be ethnographically analyzed and artistically corrected. Using text from the author’s doctoral research on Indigenous wildlife activism in Southern Africa, the study prompts an AI image generator (DALL·E) to produce visual interpretations of Indigenous land, non-human kin, and resistance. These outputs are then examined for bias, omission, and distortion, before being manually transformed into oil paintings through a process of artistic intervention, curation, and re-authoring. This iterative dialogue between algorithmic rendering and embodied painting functions as a form of digital ethnography through art. The results show that AI consistently abstracts, stereotypes, and de-contextualizes Indigenous ecologies, but also produces unexpected visual fragments that can be reclaimed through human intervention. The hand-painted artworks become sites of epistemic repair, restoring relational meaning, cultural specificity, and narrative sovereignty that the AI cannot generate on its own. The study contributes three things: (1) a replicable AI-ethnographic methodology for analyzing how algorithms construct cultural meaning; (2) an empirical demonstration of how artistic intervention can expose and correct algorithmic bias; and (3) a framework for using AI-assisted art as a tool of Indigenous digital sovereignty and eco-futurist storytelling. By repositioning AI as a flawed but productive collaborator rather than an autonomous artist, the research reframes algorithmic creativity as a site of cultural negotiation, authorship, and decolonial intervention.

Keywords

AI-Assisted Art, Visual Anthropology, Eco-Futurism, Indigenous Knowledge Systems

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