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

TL;DR

This paper surveys NLP applications aimed at social good, highlighting current research trends, gaps in domains like poverty and environmental protection, and emphasizing the need for responsible, human-centered deployment to maximize positive societal impact.

Contribution

It provides a comprehensive overview of NLP for Social Good, analyzing trends, identifying underexplored areas, and proposing a framework for responsible and equitable NLP development.

Findings

Research focuses mainly on inclusion and AI harms.

Domains like poverty and environmental protection are underexplored.

Calls for cross-disciplinary and human-centered approaches.

Abstract

Natural language processing (NLP) now shapes many aspects of our world, yet its potential for positive social impact is underexplored. This paper surveys work in ``NLP for Social Good" (NLP4SG) across nine domains relevant to global development and risk agendas, summarizing principal tasks and challenges. We analyze ACL Anthology trends, finding that inclusion and AI harms attract the most research, while domains such as poverty, peacebuilding, and environmental protection remain underexplored. Guided by our review, we outline opportunities for responsible and equitable NLP and conclude with a call for cross-disciplinary partnerships and human-centered approaches to ensure that future NLP technologies advance the public good.