Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning from finance to medicine. Despite their numerous advantages, AI systems can exhibit biased judgements in domains ranging from perception to emotion. Here, in a series of experiments (n = 1,401 participants), we reveal a feedback loop where human–AI interactions alter processes underlying human perceptual, emotional and social judgements, subsequently amplifying biases in humans. This amplification is significantly greater than that observed in interactions between humans, due to both the tendency of AI systems to amplify biases and the way humans perceive AI systems. Participants are often unaware of the extent of the AI’s influence, rendering them more susceptible to it. These findings uncover a mechanism wherein AI systems amplify biases, which are further internalized by humans, triggering a snowball effect where small errors in judgement escalate into much larger ones.

人工智能 （AI） 技术正在迅速发展，增强了从金融到医学等各个领域的人类能力。尽管 AI 系统具有许多优势，但在从感知到情感的领域可能会表现出有偏见的判断。在这里，在一系列实验（n = 1,401 名参与者）中，我们揭示了一个反馈回路，其中人类与 AI 的交互改变了人类感知、情感和社会判断背后的过程，从而放大了人类的偏见。这种放大明显大于在人类之间的互动中观察到的放大，因为 AI 系统倾向于放大偏见以及人类感知 AI 系统的方式。参与者通常不知道 AI 的影响程度，这使他们更容易受到影响。这些发现揭示了一种机制，其中 AI 系统放大了偏见，这些偏见被人类进一步内化，从而引发滚雪球效应，即判断中的小错误升级为更大的判断错误。