Key Takeaway: As AI-driven information operations become increasingly common, we expect traditional CopyPasta to be replaced by AIPasta, which is harder to detect and mitigate.

AIPasta (vs. Control) also increases belief in the exact false claim of the campaign, depending on political orientation. Current state-of-the-art AI-text detectors fail to detect AIPasta, enabling these operations to scale successfully.

In a preregistered experiment with 1200 U.S. participants, we find that AIPasta (but not CopyPasta) is effective at increasing perceptions of consensus in false claims. Exposure to AIPasta does not change levels of sharing intent compared to a control condition (CopyPasta reduces this).

In this paper, we study how AI-paraphrased messages can enhance information campaigns. We look at how CopyPasta - a single message crafted by adversarial actors & shared repeatedly at scale --- can be paraphrased using LLMs to generate repetitive, non-identical messages i.e., AIPasta.