  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.
