mlsanityData to 7 Oct 2026

"It's how you do things that matters": Attending to Process to Better Serve Indigenous Communities with Language Technologies

arXiv 2402.02639 ↗First posted 4 Feb 2024cs.CLcited by 12

Not on the map. Why?

Abstract (arXiv)

Indigenous languages are historically under-served by Natural Language Processing (NLP) technologies, but this is changing for some languages with the recent scaling of large multilingual models and an increased focus by the NLP community on endangered languages. This position paper explores ethical considerations in building NLP technologies for Indigenous languages, based on the premise that such projects should primarily serve Indigenous communities. We report on interviews with 17 researchers working in or with Aboriginal and/or Torres Strait Islander communities on language technology projects in Australia. Drawing on insights from the interviews, we recommend practices for NLP researchers to increase attention to the process of engagements with Indigenous communities, rather than focusing only on decontextualised artefacts.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 11 of its 43 references that are in the map. First posted on arXiv 4 Feb 2024.

Builds on

11 of 43 references.

References · 11

  1. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  2. 2023Scaling Speech Technology to 1,000+ Languagescited by 401
  3. 2023MADLAD-400: A Multilingual And Document-Level Large Audited Datasetcited by 180
  4. 2023Glot500: Scaling Multilingual Corpora and Language Models to 500 Languagescited by 116
  5. 2022Evaluation Gaps in Machine Learning Practicecited by 48
  6. 2023Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakerscited by 26
  7. 2022Not always about you: Prioritizing community needs when developing endangered language technologycited by 21
  8. 2022A Systematic Review and Thematic Analysis of Community-Collaborative Approaches to Computing Researchcited by 13
  9. 2022JamPatoisNLI: A Jamaican Patois Natural Language Inference Datasetcited by 11
  10. 2018Learning to Generate Wikipedia Summaries for Underserved Languages from Wikidatacited by 7
  11. 2022Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languagescited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 5; 2026: 2.

12 papers.

  1. 2024Towards Measuring and Modeling "Culture" in LLMs: A Surveycited by 166
  2. 2024Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Artcited by 26
  3. 2024What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialectscited by 20
  4. 2024Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarcecited by 4
  5. 2025Designing Speech Technologies for Australian Aboriginal English: Opportunities, Risks and Participationcited by 3
  6. 2025What Do Indonesians Really Need from Language Technology? A Nationwide Surveycited by 2
  7. 2024Modeling the Sacred: Considerations when Using Religious Texts in Natural Language Processingcited by 1
  8. 2025Vuyko Mistral: Adapting LLMs for Low-Resource Dialectal Translationcited by 1
  9. 2025On Non-interactive Evaluation of Animal Communication Translatorscited by 0
  10. 2025Big AI is accelerating the metacrisis: What can we do?cited by 0
  11. 2026Vavanagi: a Community-run Platform for Documentation of the Hula Language in Papua New Guineacited by 0
  12. 2026Supporting and Performing Culture from the Insidecited by 0