A new project by Dr Maya Indira Ganesh, Associate Director and Co-director of the Narratives and Justice programme at CFI, asks what it means to be marginalised in the world of the AI.
Digital Ojar is a digital representation of Quilt Ojar, a physical quilt made by the Arctic Indigenous Visual Artists Network (AIVAN). The quilt’s 21 tiles, handmade with materials sourced from Indigenous homelands across the Arctic, tell stories of human and nonhuman ecologies of the region. Visitors to the Digital Ojar website can click on each tile to learn about the artist and the story behind it. “Ojar” in the Saami language is a word for the ripples made by a stone thrown into water.
The project addresses the question: what happens to marginalised stories, languages, and cultural knowledge when they enter the internet and AI’s infrastructures, and who decides?
“The same tools that can help save endangered languages and traditional knowledge can and do copy, strip, and reuse that knowledge without asking permission or giving anything back,” says Dr Ganesh. “Data scraped to train AI, cultural archives digitised by outside institutions, platforms built for growth rather than trust all raise the same question: who is this really for?” These are broader questions of community and cultural resilience that converge with the politics of the internet that AI ethics and data policy will have to confront.
In the Relations section of the website, is a series of new tiles created by the artist Kira Xonorika using open-source AI image generators; they are her interpretations of the AIVAN community’s traditional motifs. They connect the site to a broader network of Indigenous data and AI projects. Kira “My intention was to bring energy and honour into a project that touches artificial intelligence, and to do so with transparency. These are digital images, AI-generated, but deeply guided by human intention, research, and care.” The process of making these tiles was slow and unfolded in conversation with the AIVAN community, explaining how their data will be used.
Digital Ojar offers a provocation to consider both ambivalence and agency in adopting AI, to consider the multiplicity of relationships and impacts in its use and proliferation.
Digital Ojar is part of the Imagine Technoscience Virtual Arts Residency, supported by the Yale University-MacMillan Fund awarded to Kalindi Vora (Yale University), Nishant Shah (Chinese University of Hong Kong), and Maya Indira Ganesh (University of Cambridge). At the centre of the project is a simple idea: communities should have a say in how their own knowledge is collected, stored, used, and shown – including when it ends up feeding an AI system trained on scraped or donated material. Dr. Tatiana Degai and Kira Xonorika were the artists supported by the Cambridge node, and Arunabh Pal Singh worked on the website design and building.
Professor Kalindi Vora commented: “Imagine Technoscience came together as a way to look across several continents (North America, Europe and Asia) to ask: what kind of imagination and knowledge-making specific to art practice do we need in the face of the proliferation of generative AI? The goal was to discover new approaches to imagine, speculate, model, and narrate the not-yet-imagined futures of AI technologies to inspire us to see possibilities of affordances and challenges they offer. We looked to artist practitioners for a virtual residency who were developing new language, lenses, and analytical frameworks to understand the ways that art practice can establish new relationships to the future that depend on these technologies, but reimagined.”
More info: Digital Ojar
Main image credit: Anna Sakmarkina, digitally re-worked by Kira Xoronika.
Facts Only
* Dr Maya Indira Ganesh is the Associate Director and Co-director of the Narratives and Justice programme at CFI.
* Digital Ojar is a digital representation of Quilt Ojar, a physical quilt made by the Arctic Indigenous Visual Artists Network (AIVAN).
* The physical quilt consists of 21 tiles made from materials sourced from Indigenous homelands across the Arctic.
* "Ojar" in the Saami language means ripples made by a stone thrown into water.
* The project addresses what happens to marginalized stories, languages, and cultural knowledge when they enter internet and AI infrastructures, and who decides.
* Dr Ganesh stated that tools for saving knowledge can copy and reuse it without permission or return.
* Data scraped for AI training and cultural archives digitized by outside institutions raise questions about ownership.
* Kira Xonorika created new tiles using open-source AI image generators as interpretations of AIVAN traditional motifs.
* The project is part of the Imagine Technoscience Virtual Arts Residency, supported by the Yale University-MacMillan Fund awarded to Kalindi Vora, Nishant Shah, and Maya Indira Ganesh.
* Dr. Tatiana Degai and Kira Xonorika were artists supported by the Cambridge node; Arunabh Pal Singh worked on website design.
Executive Summary
A project by Dr Maya Indira Ganesh explores the meaning of marginalization within the context of Artificial Intelligence. The core concept involves Digital Ojar, a digital representation of Quilt Ojar, a physical quilt created by the Arctic Indigenous Visual Artists Network (AIVAN). This quilt contains 21 tiles made from materials sourced across the Arctic and tells stories of regional human and nonhuman ecologies. The project examines what occurs to marginalized stories, languages, and cultural knowledge when they enter internet and AI infrastructures, focusing on questions of ownership and decision-making.
The project addresses how tools used to save endangered languages and traditional knowledge can simultaneously copy and reuse that knowledge without consent. It prompts reflection on the ethical implications of data scraping for AI training and the structure of platforms built for growth versus trust. Furthermore, new tiles by artist Kira Xonorika use open-source AI image generators to interpret AIVAN motifs, connecting the project to a wider network of Indigenous data and AI initiatives. The project is supported by the Imagine Technoscience Virtual Arts Residency, involving contributions from Yale University-MacMillan Fund recipients and artists, centering the idea that communities must control how their knowledge is collected, stored, used, and reflected in AI systems.
Full Take
The narrative navigates the tension between technological capability and cultural sovereignty when engaging with AI systems. The central observation is that existing infrastructure, which promises growth, simultaneously operates on principles of extraction, challenging the assumption that digital tools are inherently neutral agents. The juxtaposition of traditional, place-based knowledge (the physical quilt) with ephemeral, scalable digital reproduction (AI generation) exposes a fundamental rift regarding agency: who controls the narrative and the outcome when cultural data feeds these new systems?
The work functions as a provocation by mapping the ambivalent relationship communities have with AI—acknowledging its potential for energy and honour while simultaneously investigating its mechanisms for copying and recontextualizing knowledge. The involvement of artists engaging directly with generative tools, guided by community consultation, suggests a methodology centered on establishing 'human intention' within algorithmic processes. This challenges the purely utilitarian view of AI advancement by foregrounding questions of embeddedness and relationality rather than mere efficiency.
The pattern observed is a structural critique of the data governance model underpinning contemporary AI development. The reliance on "scraped or donated material" reflects an underlying system where value is assigned based on access rather than consent, which echoes historical patterns of colonial extraction of knowledge from marginalized communities. The implication is that addressing AI ethics requires not just technical policy but a fundamental re-evaluation of relational frameworks—demanding systems be built around community self-determination rather than external data flows.
Bridge Questions: If infrastructure must accommodate agency, what tangible mechanisms can bridge the gap between artistic intention and algorithmic control? How can principles of Indigenous knowledge-making inform the architecture of future AI governance, beyond mere consultation? What are the long-term consequences for cultural resilience if decentralized modes of knowing remain marginalized by centralized technological infrastructures?