ACL Findings2021
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact
Zhijing Jin, Geeticka Chauhan, Brian Tse, Mrinmaya Sachan, Rada Mihalcea
Abstract
Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. Noting the rising number of applications of other machine learning and AI techniques with pervasive societal impact, we anticipate the rising importance of developing NLP technologies for social good. Inspired by theories in moral philosophy and global priorities research, we aim to promote a guideline for social good in the context of NLP. We lay the foundations via the moral philosophy definition of social good, propose a framework to evaluate the direct and indirect real-world impact of NLP tasks, and adopt the methodology of global priorities research to identify priority causes for NLP research. Finally, we use our theoretical framework to provide some practical guidelines for future NLP research for social good. 1
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Cited by top-tier papers4
- Towards Climate Awareness in NLP ResearchDaniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler et al.EMNLP 2022 · 32 citations
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- The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems FailSamuel R. BowmanACL 2022
Builds on4
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- Language (Technology) is Power: A Critical Survey of "Bias" in NLPSu Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. WallachACL 2020 · 68 citations
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