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<p>The use of Artificial Intelligence (AI) to effectively support human decision making depends on whether humans are willing to trust in, and thus rely on, AI. Understanding human reliance on AI is critical given controversial reports of AI inaccuracy and bias. Furthermore, the erroneous belief that using technology removes biases may lead to overreliance on AI. To examine humans’ reliance on AI, human participants (<i>N</i> = 295, <i>M</i><sub><i>age</i></sub> = 33.79) judged the authenticity of 80 faces (40 real, 40 AI-synthesized) presented alongside guidance supposedly from humans or from AI. This guidance was correct only half of the time. Participants indicated their confidence in each judgement and completed measures to examine propensity to trust humans and general attitudes towards AI. Participants who received AI guidance and exhibited more positive attitudes towards AI showed poorer discriminability between real and synthetic faces than those with less positive attitudes towards AI. For participants who received human guidance, level of trust in humans did not affect discriminability. Therefore, AI-derived guidance may be uniquely placed to engender biases in humans, leading to less effective decision making. To ensure successful human-AI decision making partnerships, more research is needed to understand precisely how humans use AI guidance in various contexts.</p>

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Examining human reliance on artificial intelligence in decision making

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月5日

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  • Joe Pearson,
  • Itiel E. Dror,
  • Emma Jayes,
  • Grace-Rose Whordley,
  • Georgina Mason,
  • Sophie Nightingale

摘要

The use of Artificial Intelligence (AI) to effectively support human decision making depends on whether humans are willing to trust in, and thus rely on, AI. Understanding human reliance on AI is critical given controversial reports of AI inaccuracy and bias. Furthermore, the erroneous belief that using technology removes biases may lead to overreliance on AI. To examine humans’ reliance on AI, human participants (N = 295, Mage = 33.79) judged the authenticity of 80 faces (40 real, 40 AI-synthesized) presented alongside guidance supposedly from humans or from AI. This guidance was correct only half of the time. Participants indicated their confidence in each judgement and completed measures to examine propensity to trust humans and general attitudes towards AI. Participants who received AI guidance and exhibited more positive attitudes towards AI showed poorer discriminability between real and synthetic faces than those with less positive attitudes towards AI. For participants who received human guidance, level of trust in humans did not affect discriminability. Therefore, AI-derived guidance may be uniquely placed to engender biases in humans, leading to less effective decision making. To ensure successful human-AI decision making partnerships, more research is needed to understand precisely how humans use AI guidance in various contexts.