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.

人工智能的生成性进展使真实和机器生成的内容之间的界限变得模糊，尤其在社交媒体上使用 AI 生成的图片来伪造个人资料。我们进行了首次大规模调查，研究发现 Twitter 上的 AI 生成头像占总头像数量的 0.052％。我们对这些账户及其推文内容进行了全面分析，并揭示了协同不真实行为的模式。研究结果还揭示了垃圾邮件和政治放大战略等多种动机。这一研究结果再次证实了需要制定有效的检测和缓解策略来应对未来生成性人工智能可能带来的负面影响。