Recent advances in the field of generative artificial intelligence (AI) have blurred the lines between authentic and machine-generated content, making it almost impossible for humans to distinguish between such media. One notable consequence is the use of AI-generated images for fake profiles on social media. While several types of disinformation campaigns and similar incidents have been reported in the past, a systematic analysis has been lacking. In this work, we conduct the first large-scale investigation of the prevalence of AI-generated profile pictures on Twitter. We tackle the challenges of a real-world measurement study by carefully integrating various data sources and designing a multi-stage detection pipeline. Our analysis of nearly 15 million Twitter profile pictures shows that 0.052% were artificially generated, confirming their notable presence on the platform. We comprehensively examine the characteristics of these accounts and their tweet content, and uncover patterns of coordinated inauthentic behavior. The results also reveal several motives, including spamming and political amplification campaigns. Our research reaffirms the need for effective detection and mitigation strategies to cope with the potential negative effects of generative AI in the future.

翻译：近期生成式人工智能（AI）领域的进展模糊了真实内容与机器生成内容之间的界限，使人类几乎无法区分此类媒体。一个显著后果是社交平台上虚假账号使用AI生成图像。尽管过去已报道多类虚假信息活动及类似事件，但系统性的分析仍属空白。本研究首次对Twitter个人资料照片中AI生成图像的普及程度展开大规模调查。我们通过整合多种数据源并设计多阶段检测流程，应对真实世界测量研究中的挑战。对近1500万张Twitter个人资料照片的分析表明，其中0.052%为人工生成，证实了其在平台上的显著存在。我们全面考察了这些账号的特征及其推文内容，并发现了协调性非真实行为的模式。研究结果还揭示了多种动机，包括垃圾信息推送和政治操作活动。本研究重申了制定有效检测与缓解策略以应对未来生成式AI潜在负面影响的必要性。