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

Luccioni, Alexandra Sasha; Pham, Katherine Hoffmann; Lam, Cynthia Sin Nga; Aylett-Bullock, Joseph; Luengo-Oroz, Miguel

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.