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Article published In: Cultural Turns in Information Design I
Edited by Juhri Selamet and Nina Hansopaheluwakan Edward
[Information Design Journal 30:1] 2025

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Weaving algorithms

Indigenizing an Arizona water chatbot

 | Arizona State University
ORCiD logo with link | Arizona State University
 | Arizona State University
Published online: 2 February 2026
DOI logo with link
https://doi.org/10.1075/idj.25022.cau
Abstract
This paper details the process of indigenizing an Arizona water chatbot. Initial attempts to integrate tribal data, adopt an Indigenous worldview, and apply the Two-Eyed Seeing framework were unsuccessful, leading to inappropriate outputs and potential harm. The turning point came when we reframed bias as evidence and our embodied reactions as data, enabling an epistemological reorientation toward relational sense-making. We argue that, to serve Indigenous communities effectively, information design must address these fundamental epistemological conflicts. Our work offers a model for creating more attuned, decolonial AI chatbot interfaces that have wide-reaching potential.
Article outline
  • 1.Introduction
  • 2.Background
    • 2.1Initial development of the Arizona water chatbot
    • 2.2Default assumptions and approach
    • 2.3Indigenizing and decolonizing
    • 2.4Indigenous epistemologies and learning
    • 2.5Two-Eyed Seeing
    • 2.6Process tracing
  • 3.Building an Indigenized WaterBot
    • 3.1Testing with Indigenous audiences
    • 3.2Indigenizing the voice
    • 3.3Applying the Two-Eyed Seeing framework
    • 3.4Reorientation
  • 4.Introducing RiverBot
  • 5.Conclusion: Weaving algorithms
  • Acknowledgements
  • References
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