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English(EN) One Confidence Threshold, Unequal Coverage: Language Gaps in Typed Decision Interfaces and How Translating Inputs Reduces Them

研究发现AI决策接口存在显著语言偏见

arXiv上发表的一项新研究揭示了类型化决策接口在性能方面存在显著的语言差异。这些接口用于AI系统中,以确定是自动分类某个项目还是将其转交给人工处理。 当使用0.9的置信度阈值进行测试时,即使在两种语言中都能正确回答请求的情况下,这些接口也始终比其他任何语言更频繁地对英语请求进行分类。这种覆盖范围差距在多个供应商中持续存在,并且在一个接口上未被标准的校准指标检测到。将输入翻译成英语几乎消除了这种差距,这表明语言偏见是AI决策工具公平部署的关键因素。 AI

影响 强调了AI系统在多语言公平性方面的需求,可能影响全球部署和可访问性。

排序理由 该集群包含一篇详细介绍AI系统性能发现的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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研究发现AI决策接口存在显著语言偏见

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该集群包含一篇详细介绍AI系统性能发现的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Junwei Yao, Yongxi Zhou, Zike Yang, Zhijun Wang, Jianan Liu, Yanxian Chen, Wenbo Ye ·

    一个置信度阈值,不平等的覆盖范围:类型化决策界面的语言差距以及翻译输入如何缩小它们

    arXiv:2610.37688v1 Announce Type: cross Abstract: Deployed classifiers often act on a prediction only when its confidence clears a threshold and pass the rest to a person. We ask whether one threshold serves all languages equally on typed decision interfaces, APIs that return a p…