To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing

Sireesh Gururaja, Amanda Bertsch, Clara Na, David Widder, Emma Strubell


Abstract
NLP is in a period of disruptive change that is impacting our methodologies, funding sources, and public perception. In this work, we seek to understand how to shape our future by better understanding our past. We study factors that shape NLP as a field, including culture, incentives, and infrastructure by conducting long-form interviews with 26 NLP researchers of varying seniority, research area, institution, and social identity. Our interviewees identify cyclical patterns in the field, as well as new shifts without historical parallel, including changes in benchmark culture and software infrastructure. We complement this discussion with quantitative analysis of citation, authorship, and language use in the ACL Anthology over time. We conclude by discussing shared visions, concerns, and hopes for the future of NLP. We hope that this study of our field’s past and present can prompt informed discussion of our community’s implicit norms and more deliberate action to consciously shape the future.
Anthology ID:
2023.emnlp-main.822
Volume:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13310–13325
Language:
URL:
https://aclanthology.org/2023.emnlp-main.822
DOI:
10.18653/v1/2023.emnlp-main.822
Bibkey:
Cite (ACL):
Sireesh Gururaja, Amanda Bertsch, Clara Na, David Widder, and Emma Strubell. 2023. To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 13310–13325, Singapore. Association for Computational Linguistics.
Cite (Informal):
To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing (Gururaja et al., EMNLP 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.emnlp-main.822.pdf
Video:
 https://aclanthology.org/2023.emnlp-main.822.mp4