Natural language processing for social good : Where we are, what is missing, and where we should go

Ranasinghe, Tharindu (2026) Natural language processing for social good : Where we are, what is missing, and where we should go. Natural Language Processing. pp. 1-6. ISSN 2977-0424

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Abstract

Natural language processing (NLP) technologies increasingly shape public life, yet their deployment for social good remains unevenly distributed across domains, languages, and geographies. This piece inaugurates the NLP for Social Good column in this journal. In this piece, I map the current state of NLP for Social Good (NLP4SG) across nine application domains. The picture that emerges is one of striking imbalance: AI harms, inclusion, and digital violence attract the bulk of research attention, while poverty, peacebuilding, and environmental protection remain critically underexplored. I argue that the field must address three structural gaps, domain coverage, linguistic diversity, and evaluation methodology, if NLP is to fulfil its potential as a force for equitable social progress. The piece concludes with five directions that I believe will define the next chapter of NLP4SG research.