对人工智能标记与人类标记艺术作品的评价偏见的神经相关性。

IF 3.1
Wenyu Zhang, Cong Xie, Liuqing Jiang, Li Yang, Zhe Hu, Ning Hao
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引用次数: 0

摘要

生成式人工智能(AI)的快速发展使机器能够生产出与人类创作相媲美的创造性产出,例如艺术品。然而,尽管取得了这些技术成就,公众对人工智能创意产品的接受程度和估值仍然不确定。本研究通过使用脑电图(EEG)和功能性近红外光谱(fNIRS)检查行为和神经反应来调查对人工智能生成艺术品的偏见。在两项预先注册的研究中(总N = 125),参与者评估了标记为人类创作或人工智能生成的画作,这些艺术品在客观上是相同的。行为结果显示,人们对人工智能标记的画作存在一致的偏见,参与者在不同的评估维度上对它们的评价较低。脑电图的神经数据显示,在评估人类标记的绘画时,P300振幅和α功率相对较高,表明潜在的更大的注意力分配和认知参与。fNIRS结果进一步表明,对于人类标记的艺术品,右侧角回的活动增加,额下回和角回之间的功能连接更强,这可能表明更深层次的语义和情感处理。这些发现强调,对人工智能生成的艺术品的偏见不仅在明确的评估中很明显,而且在潜在的神经过程中也很明显,反映了对人类创造力的持续偏好。该研究强调了解决公众偏见以促进对人工智能技术的接受和信任的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural correlates of evaluative bias against AI-labeled versus human-labeled artworks.

The rapid advancement of generative artificial intelligence (AI) has enabled machines to produce creative outputs, such as artworks, that rival human creations. However, despite these technological achievements, public acceptance and valuation of AI-generated creative products remain uncertain. This study investigates the bias against AI-generated artworks by examining both behavioral and neural responses using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Across two pre-registered studies (total N = 125), participants evaluated paintings labeled as either human-created or AI-generated, with the artworks being objectively identical. Behavioral results revealed a consistent bias against AI-labeled paintings, with participants rating them lower in different evaluative dimensions. Neural data from EEG indicated relatively higher P300 amplitudes and alpha power during the evaluation of human-labeled paintings, suggesting potentially greater attentional allocation and cognitive engagement. The fNIRS results further demonstrated increased activity in the right angular gyrus and stronger functional connectivity between the inferior frontal gyrus and angular gyrus for human-labeled artworks, which may indicate deeper semantic and emotional processing. These findings highlight that biases against AI-generated artworks are not only evident in explicit evaluations but also manifest in underlying neural processes, reflecting a persistent preference for human creativity. The study underscores the importance of addressing public biases to foster acceptance and trust in AI technologies.

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