arXiv:2501.19407cs.CYcs.AI2025-01被引 2

AI偏爱姓氏含财富暗示者,可能固化代际不平等。

Algorithmic Inheritance: Surname Bias in AI Decisions Reinforces Intergenerational Inequality

  • 用600个姓氏分四类,测试其对AI决策影响
  • 精英姓氏使AI判断更聪明富有,影响招聘贷款等关键决策
  • 简历补充无法根除偏见,低资质时问题更严重

姓氏常隐含社会地位、财富和家世信息,可能加剧系统性偏见与代际不平等。本研究首次考察姓氏如何影响人工智能决策,聚焦招聘推荐、领导任命和贷款审批等关键领域。基于美国和泰国共7.2万次对600个姓氏的评估,我们将姓氏分为富人型、传承型、普通型及发音相似的变体型四类。结果表明,精英姓氏显著提升AI对个人权力、智力和财富的感知,进而影响高风险决策。中介分析显示,感知智力是姓氏偏见影响AI决策的关键机制。尽管补充客观资质可缓解多数偏见,但当候选人履历较弱时,偏见仍难以消除。研究呼吁开发公平导向算法与政策,防止AI系统强化由姓氏关联的代际特权,尤其在以择优为原则的系统中更需警惕这一被忽视的偏见。

原文摘要 · Abstract (English)

Surnames often convey implicit markers of social status, wealth, and lineage, shaping perceptions in ways that can perpetuate systemic biases and intergenerational inequality. This study is the first of its kind to investigate whether and how surnames influence AI-driven decision-making, focusing on their effects across key areas such as hiring recommendations, leadership appointments, and loan approvals. Using 72,000 evaluations of 600 surnames from the United States and Thailand, two countries with distinct sociohistorical contexts and surname conventions, we classify names into four categories: Rich, Legacy, Normal, and phonetically similar Variant groups. Our findings show that elite surnames consistently increase AI-generated perceptions of power, intelligence, and wealth, which in turn influence AI-driven decisions in high-stakes contexts. Mediation analysis reveals perceived intelligence as a key mechanism through which surname biases influence AI decision-making process. While providing objective qualifications alongside surnames mitigates most of these biases, it does not eliminate them entirely, especially in contexts where candidate credentials are low. These findings highlight the need for fairness-aware algorithms and robust policy measures to prevent AI systems from reinforcing systemic inequalities tied to surnames, an often-overlooked bias compared to more salient characteristics such as race and gender. Our work calls for a critical reassessment of algorithmic accountability and its broader societal impact, particularly in systems designed to uphold meritocratic principles while counteracting the perpetuation of intergenerational privilege.

AI偏见姓氏歧视算法公平代际不平等

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