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NLP for Social Good: A Survey of Challenges, Opportunities, and Responsible Deployment

MCML Authors

Abstract

Recent advancements in large language models (LLMs) have unlocked unprecedented possibilities across a range of applications. However, as a community, we believe that the field of Natural Language Processing (NLP) has a growing need to approach deployment with greater intentionality and responsibility. In alignment with the broader vision of AI for Social Good (Tomašev et al., 2020), this paper examines the role of NLP in addressing pressing societal challenges. Through a cross-disciplinary analysis of social goals and emerging risks, we highlight promising research directions and outline challenges that must be addressed to ensure responsible and equitable progress in NLP4SG research.

misc


Preprint

May. 2025

Authors

A. Karamolegkou • A. Borah • E. Cho • S. R. Choudhury • M. Galletti • R. Ghosh • P. Gupta • O. Ignat • P. Kargupta • N. Kotonya • H. Lamba • S.-J. Lee • A. Mangla • I. Mondal • D. Nazarova • P. Nemkova • D. Pisarevskaya • N. Rizwan • N. Sabri • D. Stammbach • A. Steinberg • D. Tomás • S. R. Wilson • B. Yi • J. H. Zhu • A. Zubiaga • A. Søgaard • A. Fraser • Z. Jin • R. Mihalcea • J. R. Tetreault • D. Dementieva

Links


Research Areas

 B2 | Natural Language Processing

 C4 | Computational Social Sciences

BibTeXKey: KBC+25

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