Understanding "Democratization" in NLP and ML Research
Not on the map. Why?
Abstract (arXiv)
Recent improvements in natural language processing (NLP) and machine learning (ML) and increased mainstream adoption have led to researchers frequently discussing the "democratization" of artificial intelligence. In this paper, we seek to clarify how democratization is understood in NLP and ML publications, through large-scale mixed-methods analyses of papers using the keyword "democra*" published in NLP and adjacent venues. We find that democratization is most frequently used to convey (ease of) access to or use of technologies, without meaningfully engaging with theories of democratization, while research using other invocations of "democra*" tends to be grounded in theories of deliberation and debate. Based on our findings, we call for researchers to enrich their use of the term democratization with appropriate theory, towards democratic technologies beyond superficial access.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 12 of its 54 references that are in the map. First posted on arXiv 17 Jun 2024.
Builds on
12 of 54 references.
References · 12
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2024Collective Constitutional AI: Aligning a Language Model with Public Inputcited by 120
- 2020Participation is not a Design Fix for Machine Learningcited by 110
- 2023The Semantic Scholar Open Data Platformcited by 109
- 2020The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Researchcited by 67
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- 2022Rethinking Fairness: An Interdisciplinary Survey of Critiques of Hegemonic ML Fairness Approachescited by 23
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- 2020A Framework for Democratizing AIcited by 4
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.