ISCA Archive SIGUL 2023
ISCA Archive SIGUL 2023

Reclaiming Our Voices: Imagining Community-led AI/ML Practices

Subhashish Panigrahi

This paper critically examines technology's role in preserving endangered languages and its relationship with social justice. The concepts of "Slow Language Models" and "Small Large-Language Models" are introduced, emphasizing community-led language preservation efforts. The paper highlights the limitations of current large language models, focusing on their text-centric bias and issues of transparency and representation in AI development. The Santali community serves as a case study, illustrating successful community-driven language preservation in the digital age. The research advocates for "Slow Language Models" and "Small Large-Language Models" as collaborative approaches, challenging the rush for technological solutions and calling for ethical, community-centered practices in AI and machine learning development.


doi: 10.21437/SIGUL.2023-1

Cite as: Panigrahi, S. (2023) Reclaiming Our Voices: Imagining Community-led AI/ML Practices. Proc. 2nd Annual Meeting of the ELRA/ISCA SIG on Under-resourced Languages (SIGUL 2023), 1-3, doi: 10.21437/SIGUL.2023-1

@inproceedings{panigrahi23_sigul,
  author={Subhashish Panigrahi},
  title={{Reclaiming Our Voices: Imagining Community-led AI/ML Practices}},
  year=2023,
  booktitle={Proc. 2nd Annual Meeting of the ELRA/ISCA SIG on Under-resourced Languages (SIGUL 2023)},
  pages={1--3},
  doi={10.21437/SIGUL.2023-1}
}