Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages
arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced communities. Yet the infrastructure underlying these tools, including training corpora, tokenization schemes, evaluation benchmarks, and deployment architectures, can systematically disadvantage speakers of underrepresented languages before a model is trained. This paper examines these structural barrier
Record details
Published: 13 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Children & education
Retrieved: 13 August 2026
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ethics.ai (13 August 2026), “Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages,” evidence record 18729, https://ethics.ai/record/18729 (originally published by arXiv cs.CY).
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