论文标题
性别偏见评估在单词嵌入中的鲁棒性和可靠性：基本对的作用
Robustness and Reliability of Gender Bias Assessment in Word Embeddings: The Role of Base Pairs
论文作者
论文摘要
已经表明，单词嵌入可以表现出性别偏见，并提出了各种方法来量化这一点。但是，这些方法在捕获从数据中继承的社会刻板印象的程度进行了辩论。偏见是一个复杂的概念，有多种定义它的方法。以前的工作已经利用性别单词对来测量偏见并提取偏见的类比。我们表明，对这些性别对的依赖有很大的局限性：基于它们的偏差措施并不强大，无法识别现实世界中的偏见类型，而利用它们的类比是不合适的偏见指标。特别是，众所周知的类比“男人是对计算机制造商，就像女人对家庭主妇一样”是由于单词相似性而不是社会偏见。这对于衡量嵌入和相关工作偏见的偏见的工作具有重要意义。
It has been shown that word embeddings can exhibit gender bias, and various methods have been proposed to quantify this. However, the extent to which the methods are capturing social stereotypes inherited from the data has been debated. Bias is a complex concept and there exist multiple ways to define it. Previous work has leveraged gender word pairs to measure bias and extract biased analogies. We show that the reliance on these gendered pairs has strong limitations: bias measures based off of them are not robust and cannot identify common types of real-world bias, whilst analogies utilising them are unsuitable indicators of bias. In particular, the well-known analogy "man is to computer-programmer as woman is to homemaker" is due to word similarity rather than societal bias. This has important implications for work on measuring bias in embeddings and related work debiasing embeddings.
