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

2025-05-28

AI Summary

This paper addresses the lack of systematic responsible governance in applying NLP technologies to urgent societal challenges—including educational equity, public health, and disaster response—by proposing the NLP4SG (NLP for Social Good) research paradigm. Methodologically, it introduces the first multidimensional evaluation framework, defining a “responsibility readiness” metric system that integrates technical auditing, ethical impact assessment, participatory design, and explainability analysis, while coupling LLM capability mapping with societal need alignment. Key contributions include: (1) identifying 12 high-priority societal application scenarios; (2) uncovering seven recurrent risks—including data colonialism and feedback-loop bias; and (3) proposing 15 actionable, responsibility-oriented deployment guidelines. The work establishes a theoretical anchor, an operational assessment toolkit, and concrete implementation pathways for socially beneficial NLP development and deployment.

Technology Category

• Natural Language Processing: Safety and Robustness
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

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 (Tomav{s}ev 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.

Problem

• Examining NLP's role in solving societal challenges
• Addressing responsible deployment of large language models
• Identifying risks and opportunities in NLP4SG research

Innovation

• Leveraging large language models for societal challenges
• Promoting responsible NLP deployment strategies
• Cross-disciplinary analysis for equitable NLP progress