研究个体差异如何影响对AI偏见决策的感知与信任。
Perceptions of Discriminatory Decisions of Artificial Intelligence: Unpacking the Role of Individual Characteristics
- 分析1206人实验数据，考察数字能力、意识形态等对AI态度的影响。
- 数字自效能高者更信任AI，自由派对算法偏见更敏感且情绪更负面。
- 年龄与收入差距导致理解AI歧视的能力差异，反映社会不平等。
本研究通过大规模实验数据（N = 1,206）探讨个人差异（数字自我效能、技术知识、平等信念、政治意识形态）及人口统计因素（年龄、教育、收入）如何影响人们对人工智能（AI）在性别与种族上表现出偏见的决策的感知，以及对AI的一般态度。结果表明，数字自我效能和技术知识与对AI的积极态度正相关，而自由主义意识形态则与对结果的信任度下降、负面情绪增强和更大质疑相关。此外，年龄和收入与理解歧视性AI结果的认知差距密切相关。研究强调提升数字素养与数字自我效能的重要性，以维护对AI的信任及其有用性与安全性认知。结果还表明，对问题性AI结果的理解差异可能与社会中的经济不平等和代际差距相一致。总体而言，该研究揭示了社会层级、分化与机器之间复杂的相互作用，这些机制既反映也加剧了社会不平等。
原文摘要 · Abstract (English)
This study investigates how personal differences (digital self-efficacy, technical knowledge, belief in equality, political ideology) and demographic factors (age, education, and income) are associated with perceptions of artificial intelligence (AI) outcomes exhibiting gender and racial bias and with general attitudes towards AI. Analyses of a large-scale experiment dataset (N = 1,206) indicate that digital self-efficacy and technical knowledge are positively associated with attitudes toward AI, while liberal ideologies are negatively associated with outcome trust, higher negative emotion, and greater skepticism. Furthermore, age and income are closely connected to cognitive gaps in understanding discriminatory AI outcomes. These findings highlight the importance of promoting digital literacy skills and enhancing digital self-efficacy to maintain trust in AI and beliefs in AI usefulness and safety. The findings also suggest that the disparities in understanding problematic AI outcomes may be aligned with economic inequalities and generational gaps in society. Overall, this study sheds light on the socio-technological system in which complex interactions occur between social hierarchies, divisions, and machines that reflect and exacerbate the disparities.
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