Ensuring the Inclusive Use of Natural Language Processing in the Global Response to COVID-19

TL;DR

This paper discusses how NLP tools used in COVID-19 response can be made more inclusive across diverse populations, languages, and regions, emphasizing future directions for equitable societal impact.

Contribution

It highlights the need for inclusive NLP approaches in pandemic response and proposes strategies to improve coverage of low-resource languages and modalities.

Findings

Current NLP tools are not equally beneficial across all populations.

Inclusive strategies can enhance NLP's societal impact.

Future research should focus on low-resource languages and partnerships.

Abstract

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.