Practising the living archive: people-centred AI practice for the Kochi-Muziris Biennale
This article examines AI as an artistic medium through people-centred, practice-based research with student practitioners at OP Jindal Global University, who developed speculative responses to the archives and context of the Kochi-Muziris Biennale. Through a seven-week collaborative programme led by the Electronic Life Research Studio, three groups created experimental prototypes responding to provocations around affective data, spatial mapping, and unofficial knowledge. Rather than implementing finished systems, participants used speculative prototyping to interrogate how authority, accessibility, and voice operate within cultural documentation. Drawing on participatory art practice and collaborative research, the article centres student practitioners’ reflections, positioning them as co-researchers whose making generates knowledge about AI's possibilities and limitations. Their work reveals approaches that are distributed rather than hierarchical, conversational rather than authoritative, and grounded in embodied experience. The first group explored capturing ephemeral encounters through alternative documentation; the second mapped connections between the Biennale and Kochi's broader histories; the third examined boundaries between official and unofficial knowledge through concept notes and translation. Together, these projects show how people-centred approaches to AI can foreground place, participation, and marginal voices, offering insights for cultural institutions seeking more democratic engagement and contributing to discourse on participatory practice and AI as artistic material.
Authors
- Robert E. D’Souza (ORCID: https://orcid.org/0000-0002-0977-0082)
Institutions
- University of Winchester (GB)
- University of Southampton (GB)
Publication Details
- Journal
- Journal of Visual Art Practice
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1080/14702029.2025.2580787
- Citations
- 1
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 2.37