天生害怕机器?遗传和环境对人工智能代理消极态度的影响。

IF 14.1 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Advanced Science Pub Date : 2025-09-01 Epub Date: 2025-06-23 DOI:10.1002/advs.202506262
Xiaojiayu Tan, Yue He, Yuan Zhou, Xinying Li, Qingwen Ding, Yikai Tang, Yu L L Luo, Ruolei Gu
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引用次数: 0

摘要

尽管人工智能(AI)主体发展迅速,但公众接受度的巨大个体差异仍然存在。为了解释对人工智能主体的态度差异,现有的研究主要集中在环境因素上。然而,进化心理学研究表明,外群体排斥机制具有遗传基础,因此需要探索人类社会中对人工智能代理作为外群体的负面态度的潜在遗传基础。本研究考察了对人工智能代理的消极态度的遗传基础及其与相关人格特征的关系,使用双胞胎研究设计来评估对人工智能代理的消极态度、受害者敏感性和道德偏好。单变量遗传分析显示,这些消极态度具有显著的遗传性。双变量分析进一步确定了受害者敏感性和个人对机器人的恐惧和警惕之间的共同遗传影响。同样,在权威的道德偏好和对人工智能主体的社会技术盲目性焦虑之间,也可以观察到共同的遗传基础。这些发现通过强调遗传因素在形成对他们的态度中的作用,扩展了对人工智能代理的社会认知的理解。此外,它们为提高公众对人工智能代理的接受度和优化人机交互提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Born to Fear the Machine? Genetic and Environmental Influences on Negative Attitudes toward AI Agents.

Despite the rapid development of artificial intelligence (AI) agents, substantial individual differences in public acceptance persist. To explain the difference in attitudes toward AI agents, existing research has primarily focused on environmental factors. However, evolutionary psychology research suggests that the mechanism of outgroup rejection has a genetic basis, highlighting the need to explore the potential genetic underpinnings of negative attitudes toward AI agents as an outgroup in human society. This study examines the genetic basis of negative attitudes toward AI agents and their relationship with related personality traits, using a twin study design to assess negative attitudes toward AI agents, victim sensitivity, and moral preferences. Univariate genetic analyses revealed significant heritability of these negative attitudes. Bivariate analyses further identify shared genetic influences between victim sensitivity and personal-level fear and wariness toward robots. Similarly, a shared genetic basis is observed between the moral preferences concerning authority and sociotechnical blindness anxiety toward AI agents. These findings extend the understanding of social cognition in AI agents by emphasizing the role of genetic factors in shaping attitudes toward them. Moreover, they provide new insights for enhancing public acceptance of AI agents and optimizing human-machine interactions.

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来源期刊
Advanced Science
Advanced Science CHEMISTRY, MULTIDISCIPLINARYNANOSCIENCE &-NANOSCIENCE & NANOTECHNOLOGY
CiteScore
18.90
自引率
2.60%
发文量
1602
审稿时长
1.9 months
期刊介绍: Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.
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