According to Ethan Mollick on X (Twitter), AI-related science posts have been moving markets by misinterpreting or misdating research papers, with one widely hyped claim traced to a study from April of the prior year rather than a new breakthrough. According to Mollick’s post, the misdated hype originated from accounts amplifying “AI slop” summaries, which led to investor overreactions and short-term volatility. According to the cited X thread by user @jukan05, the referenced paper was published last April, indicating a rerun of old findings framed as fresh news, creating misleading market signals. As reported by the X posts, this pattern underscores a growing risk for traders and enterprises relying on social media AI summaries without source verification, highlighting the need for timestamp checks, DOI validation, and direct journal links in due diligence workflows.