Must NLP be Extractive?

Steven Bird


Abstract
How do we roll out language technologies across a world with 7,000 languages? In one story, we scale the successes of NLP further into ‘low-resource’ languages, doing ever more with less. However, this approach does not recognise the fact that, beyond the 500 institutional languages, the remaining languages are oral vernaculars spoken by communities who use a language of wider communication to interact with the outside world. I argue that such ‘contact languages’ are the appropriate target for technologies like machine translation, and that the 6,500 oral languages must be approached differently. I share a story from an Indigenous community, where local people reshaped an extractive agenda to align with their relational agenda. I describe the emerging paradigm of relational NLP and explain how it opens the way to non-extractive methods and to solutions that enhance human agency.
Anthology ID:
2024.acl-long.797
Volume:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
14915–14929
Language:
URL:
https://aclanthology.org/2024.acl-long.797
DOI:
10.18653/v1/2024.acl-long.797
Bibkey:
Cite (ACL):
Steven Bird. 2024. Must NLP be Extractive?. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 14915–14929, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Must NLP be Extractive? (Bird, ACL 2024)
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PDF:
https://preview.aclanthology.org/landing_page/2024.acl-long.797.pdf