How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact
| Autor: | Brian Tse, Rada Mihalcea, Geeticka Chauhan, Mrinmaya Sachan, Zhijing Jin |
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| Přispěvatelé: | Zong, Chengqing, Xia, Fei, Li, Wenjie, Navigli, Roberto |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer science business.industry Social impact Societal impact of nanotechnology Context (language use) computer.software_genre Field (computer science) Machine Learning (cs.LG) Through-the-lens metering Computer Science - Computers and Society Moral philosophy Artificial Intelligence (cs.AI) Computers and Society (cs.CY) Artificial intelligence business Computation and Language (cs.CL) computer Natural language processing |
| Zdroj: | Findings of ACL: ACL-IJCNLP 2021 Findings of ACL Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 ACL/IJCNLP (Findings) |
| DOI: | 10.3929/ethz-b-000527311 |
| Popis: | 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. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 ISBN:978-1-954085-54-1 |
| Databáze: | OpenAIRE |
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