论文标题
语言（技术）是力量：对NLP中“偏见”的批判性调查
Language (Technology) is Power: A Critical Survey of "Bias" in NLP
论文作者
论文摘要
我们调查了146篇分析NLP系统中“偏见”的论文，发现他们的动机通常是模糊的，不一致的，并且缺乏规范推理，尽管分析“偏见”是一个固有的规范过程。我们进一步发现，这些论文提出的用于测量或缓解“偏见”的定量技术与它们的动机匹配不佳，并且不与NLP之外的相关文献互动。基于这些发现，我们通过提出三个建议来指导分析NLP系统中的“偏见”的建议，描述了前进道路的开端。这些建议取决于对语言与社会等级之间的关系的更大认识，鼓励研究人员和实践者表达他们对“偏见”的概念化的概念，即哪种系统行为是有害的，哪种方式，与谁，与谁，以及为什么围绕这些陈述的规范性进行的，以及围绕这些陈述的规范性的纽带，以及与社区相关的境内 - 与社区的相关性，这些社区的成员是社区的，这些社区的成员是众所周知的，这些社区的成员存在，以及范围的社区，众所周知，这些言论的范围是，这些言论是众所周知的，这些言论是众所周知的，这些言论是众所周知的，这些陈述的成员是众所周知的，这些言论是众所周知的，这些陈述的范围是，涉及范围的社区，涉及这些言论的社区，这些言论是众所周知的。重新想象技术人员与此类社区之间的权力关系。
We survey 146 papers analyzing "bias" in NLP systems, finding that their motivations are often vague, inconsistent, and lacking in normative reasoning, despite the fact that analyzing "bias" is an inherently normative process. We further find that these papers' proposed quantitative techniques for measuring or mitigating "bias" are poorly matched to their motivations and do not engage with the relevant literature outside of NLP. Based on these findings, we describe the beginnings of a path forward by proposing three recommendations that should guide work analyzing "bias" in NLP systems. These recommendations rest on a greater recognition of the relationships between language and social hierarchies, encouraging researchers and practitioners to articulate their conceptualizations of "bias"---i.e., what kinds of system behaviors are harmful, in what ways, to whom, and why, as well as the normative reasoning underlying these statements---and to center work around the lived experiences of members of communities affected by NLP systems, while interrogating and reimagining the power relations between technologists and such communities.
