Born to Fear the Machine? Genetic and Environmental Influences on Negative Attitudes toward AI Agents.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date:

Abstract

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.

Authors

  • Xiaojiayu Tan
    State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
  • Yue He
    Department of Breast Surgery, Hunan Cancer Hospital, Changsha, Hunan, China.
  • Yuan Zhou
    Department of Pharmacy, Taihe Hospital, Hubei University of Medicine, Shiyan, China.
  • Xinying Li
    Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences Beijing, China.
  • Qingwen Ding
    State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
  • Yikai Tang
    Department of Psychology, University of Toronto, Toronto, ON, M5S 1A1, Canada.
  • Yu L L Luo
    State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China.
  • Ruolei Gu
    Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences Beijing, China.

Keywords

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