With the rapid proliferation of artificial intelligence, there is growing concern over its potential to exacerbate existing biases and societal disparities and introduce novel ones. This issue has prompted widespread attention from academia, policymakers, industry, and civil society. While evidence suggests that integrating human perspectives can mitigate bias-related issues in AI systems, it also introduces challenges associated with cognitive biases inherent in human decision-making. Our research focuses on reviewing existing methodologies and ongoing investigations aimed at understanding annotation attributes that contribute to bias.

翻译：随着人工智能的快速普及，人们日益担忧其可能加剧现有偏倚与社会差距，甚至引发新型不公问题。这一议题已引发学术界、政策制定者、产业界及公民社会的广泛关注。尽管有证据表明融入人类视角可缓解人工智能系统中的偏倚问题，但这亦引入了人类决策中固有的认知偏倚相关挑战。本研究聚焦于综述现有方法论及当前研究进展，旨在理解导致偏倚产生的标注属性。