使用人工神经网络合成的人脸吸引力被低估的行为和神经证据

Satoshi Nishida
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摘要

人工智能(AI)的最新进展并没有缓解人类对人工智能的焦虑。如果这种焦虑降低了人类对人工智能合成的视觉信息的偏好,那么这种偏好应该仅仅因为相信信息是人工智能合成的而降低,与信息的外观无关。本研究通过让实验参与者对人工神经网络合成的人脸的吸引力进行评分来验证这一假设,实验参与者被假定一些人脸是真实的,而另一些人脸是合成的。这种实验设计将信念对吸引力评分的影响与实际面部外观隔离开来。此外,实验还使用 fMRI 记录了大脑的反应,以研究这种信念效应的神经基础。结果显示,当参与者认为人脸是合成的时,他们对人脸的评分会明显降低,而且这种信念会改变右侧纺锤形皮层中 fMRI 信号对面部吸引力的反应。这些发现支持了这样一种观点,即人类对视觉信息的偏好降低完全是因为相信信息是由人工智能合成的,这表明人工智能和机器人的设计不仅要关注增强外观,还要关注减轻人类对外观的焦虑。
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Behavioral and neural evidence for the underestimated attractiveness of faces synthesized using an artificial neural network
Recent advancements in artificial intelligence (AI) have not eased human anxiety about AI. If such anxiety diminishes human preference for AI-synthesized visual information, the preference should be reduced solely by the belief that the information is synthesized by AI, independently of its appearance. This study tested this hypothesis by asking experimental participants to rate the attractiveness of faces synthesized by an artificial neural network, under the false instruction that some faces were real and others were synthetic. This experimental design isolated the impact of belief on attractiveness ratings from the actual facial appearance. Brain responses were also recorded with fMRI to examine the neural basis of this belief effect. The results showed that participants rated faces significantly lower when they believed them to be synthetic, and this belief altered the responsiveness of fMRI signals to facial attractiveness in the right fusiform cortex. These findings support the notion that human preference for visual information is reduced solely due to the belief that the information is synthesized by AI, suggesting that AI and robot design should focus not only on enhancing appearance but also on alleviating human anxiety about them.
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