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

arXiv: https://arxiv.org/abs/2505.22327 · HTML: https://mlsanity.com/paper/2505.22327/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 May 2025.

## Built on by (most cited first, 3 of 3)

- [RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models](https://mlsanity.com/paper/2506.02726/) (2025)
- [AI Application Gives Users Real-Time Feedback on the Level of Peace in the Social Media Videos They Watch](https://mlsanity.com/paper/2601.05232/) (2026)
- [Grounded, Compute-Efficient LLM Policy Agents for Energy-Poverty Equity in Physically-Constrained Peer-to-Peer Energy Markets](https://mlsanity.com/paper/2609.01918/) (2026)

## Abstract (arXiv)

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.