AI-generated media has become a threat to our digital society as we know it. These forgeries can be created automatically and on a large scale based on publicly available technology. Recognizing this challenge, academics and practitioners have proposed a multitude of automatic detection strategies to detect such artificial media. However, in contrast to these technical advances, the human perception of generated media has not been thoroughly studied yet. In this paper, we aim at closing this research gap. We perform the first comprehensive survey into people's ability to detect generated media, spanning three countries (USA, Germany, and China) with 3,002 participants across audio, image, and text media. Our results indicate that state-of-the-art forgeries are almost indistinguishable from "real" media, with the majority of participants simply guessing when asked to rate them as human- or machine-generated. In addition, AI-generated media receive is voted more human like across all media types and all countries. To further understand which factors influence people's ability to detect generated media, we include personal variables, chosen based on a literature review in the domains of deepfake and fake news research. In a regression analysis, we found that generalized trust, cognitive reflection, and self-reported familiarity with deepfakes significantly influence participant's decision across all media categories.

翻译：人工智能生成的媒体已成为我们数字社会所面临的威胁。这些伪造内容可以基于公开可用的技术自动大规模生成。认识到这一挑战后，学者和从业者提出了多种自动检测策略来识别此类人工媒体。然而，与技术进展相比，人们对生成媒体的感知能力尚未得到充分研究。本文旨在填补这一研究空白。我们首次开展了针对人类检测生成媒体能力的全面调查，覆盖美国、德国和中国三个国家，共3002名参与者，涉及音频、图像和文本三种媒体类型。结果表明，最先进的伪造品与"真实"媒体几乎难以区分，大多数参与者在被要求判断其为人类生成还是机器生成时，仅凭猜测作答。此外，在所有媒体类型和所有国家中，AI生成的媒体被认为更接近人类生成。为了进一步理解影响人们检测生成媒体能力的因素，我们基于深度伪造和假新闻研究领域的文献综述选取了个体变量。通过回归分析发现，普遍信任、认知反思能力以及自我报告的深度伪造熟悉程度显著影响参与者对所有媒体类别的判断。