Whose Knowledge Counts? Co-Designing Community-Centered AI Auditing Tools with Educators in Hawai'i

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Authors: Dora Zhao, Hannah Cha, Michael J. Ryan, Angelina Wang, Rachel Baker-Ramos, Evyn-Bree Helekahi-Kaiwi, Rebecca Diego, Josiah D. Hester, Diyi Yang
Cited by: 1
References: 121

Abstract

Although generative AI is being deployed into classrooms with promises of aiding teachers, educators caution that these tools can have unintended pedagogical repercussions, including cultural misrepresentation and bias. These concerns are heightened in low-resource language and Indigenous education settings, where AI systems frequently underperform. We investigate these challenges in Hawai‘i, where public schools operate under a statewide mandate to integrate Hawaiian language and culture into education. Through four co-design workshops with 22 public school educators, we surfaced concerns about using generative AI in educational settings, particularly around cultural misrepresentation, and corresponding designs for auditing tools that address these issues. We find that educators envision tools grounded in specific Hawaiian cultural values and practices, such as tracing the genealogy of knowledge in source materials. Building on these insights, we conceptualize AI auditing as a community-oriented process rather than the work of isolated individuals, and discuss implications for designing auditing tools.

Fields of Study & Subjects

Teaching and Learning Programming ICT in Developing Communities AI in Service Interactions

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–24
Publication date
13 April 2026