Ensuring the Inclusive Use of Natural Language Processing in the Global Response to COVID-19
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Abstract (arXiv)
Natural language processing (NLP) plays a significant role in tools for the COVID-19 pandemic response, from detecting misinformation on social media to helping to provide accurate clinical information or summarizing scientific research. However, the approaches developed thus far have not benefited all populations, regions or languages equally. We discuss ways in which current and future NLP approaches can be made more inclusive by covering low-resource languages, including alternative modalities, leveraging out-of-the-box tools and forming meaningful partnerships. We suggest several future directions for researchers interested in maximizing the positive societal impacts of NLP.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 43 references that are in the map. First posted on arXiv 11 Aug 2021.
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14 of 43 references.
References · 14
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- 2019Evaluating Language Model Finetuning Techniques for Low-resource Languagescited by 12
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