Individual and social biases undermine the effectiveness of human advisers by inducing judgment errors which can disadvantage protected groups. In this paper, we study the influence these biases can have in the pervasive problem of fake news by evaluating human participants' capacity to identify false headlines. By focusing on headlines involving sensitive characteristics, we gather a comprehensive dataset to explore how human responses are shaped by their biases. Our analysis reveals recurring individual biases and their permeation into collective decisions. We show that demographic factors, headline categories, and the manner in which information is presented significantly influence errors in human judgment. We then use our collected data as a benchmark problem on which we evaluate the efficacy of adaptive aggregation algorithms. In addition to their improved accuracy, our results highlight the interactions between the emergence of collective intelligence and the mitigation of participant biases.

翻译：个体和社会偏见会通过引发判断错误来削弱人类顾问的有效性，进而使受保护群体处于不利地位。本文通过评估人类参与者识别虚假标题的能力，研究这些偏见在普遍存在的虚假新闻问题中可能产生的影响。通过关注涉及敏感特征的标题，我们收集了一个全面的数据集，以探索人类反应如何受其偏见塑造。我们的分析揭示了反复出现的个体偏见及其向集体决策的渗透。研究表明，人口统计学因素、标题类别以及信息呈现方式会显著影响人类判断中的错误。随后，我们利用收集的数据作为基准问题，评估自适应聚合算法的有效性。除了提高准确性外，我们的结果还突显了集体智慧涌现与参与者偏见减轻之间的相互作用。