人工智能对就业的未来影响的看法中的脆弱性偏见
Felipe Barrera-Jimenez1, Jose Luis Arroyo-Barrigüete2, Eduardo C Garrido-Merchán3,4
1Universidad Pontificia Comillas, Santalucía Chair of Analytics for Education, Calle de Alberto Aguilera, 23, Madrid, 28015, Spain. fbarrera@comillas.edu.
Scientific reports
|August 6, 2025
概括
工人经常认为人工智能 (AI) 将比他们自己更影响他人,这种偏见被称为不易受伤害偏见. 人工智能知识的增加可以减少这种看法,特别是在技术领域.
科学领域:
- 劳动经济学 劳动经济学
- 认知心理学 认知心理学
- 技术社会学技术的社会学.
背景情况:
- 人工智能 (AI) 的采用正在改变劳动力市场.
- 工人对人工智能的影响的看法是不一致的,受认知偏见的影响.
- 了解这些偏见对于劳动力适应策略至关重要.
研究的目的:
- 调查AI对就业的影响的脆弱性偏见 (IB) 和按影响类型 (OBTI) 的乐观偏见的流行情况.
- 确定影响这些偏见的因素,例如人工智能知识和专业部门.
- 为旨在提高工人对人工智能的劳动力市场影响意识的干预措施提供信息.
主要方法:
- 通过社交媒体方便抽样招募的201名参与者的调查数据.
- 包括威尔科克森测试和普通最小平方回归在内的统计分析.
- 机器学习技术,如集群,随机森林和决策树.
主要成果:
- 证实了显著的不易受伤害偏见 (IB),工人低估了人工智能对自己工作的影响.
- 对影响类型 (OBTI) 的乐观偏见并不显著;很少有人认为人工智能对他们的工作的影响比对其他人更积极.
- 较高的AI知识与较低的IB相关;偏见因行业而异,医疗保健,法律和公共行政部门的IB高于技术部门.
结论:
- 工人倾向于认为人工智能的工作影响对他人来说比对自己更大 (IB).
- 熟悉人工智能似乎可以减轻被认为是就业风险的外部化.
- 需要有针对性的教育干预措施来解决与人工智能相关的偏见,并改善不同专业领域的劳动力准备.
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