English(EN) Position: Every Ground Truth is a Human Construction, not an Objective Truth

AI研究人员质疑地面真实数据集的客观性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-14 04:00

这篇立场论文认为，对于训练和评估机器学习模型至关重要的地面真实数据集，并非客观测量，而是人类的构建。作者认为，机器学习社区将受益于认识到这些数据集的偶然性和情境依赖性。通过关注地面真实的特定情境下的可靠性，研究人员可以更好地理解模型的局限性和优势，从而提高透明度和问责制。 AI

影响促使对数据局限性产生更深入的理解，可能导致更强大、更可靠的AI模型。

排序理由该条目是一篇在arXiv上发表的学术论文，讨论机器学习数据集的理论方面。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Charlotte H\"ogberg, Ericka Johnson, Kiri L. Wagstaff · 2026-07-14 04:00

立场：每一个地面真实都是人类建构，而非客观真理

arXiv:2607.09668v1 Announce Type: new Abstract: Ground truth datasets play a fundamental role as reference values in the training and evaluation of machine learning models. This position paper argues that ground truths are not neutral objective measurements that are naturally giv…