Can AI generate hundreds of fake academic papers automatically?

A demonstration paper applied LLMs to generate three distinct complete versions of academic papers for each of 96 stock return predictor signals. Each version included "creative names for the signals, custom introductions providing different theoretical justifications for the observed predictability patterns, and citations to existing (and, on occasion, imagined) literature." This is HARKing (Hypothesizing After Results are Known) industrialized.

The process: mine 30,000+ potential predictor signals from accounting data, apply rigorous statistical filtering to find 96 that pass, then use LLMs to retroactively construct theoretical justifications for why those signals should predict returns. The AI generates the narrative that makes the data mining look like hypothesis-driven research.

This is the academic equivalent of the false punditry described in the social media context — style substituting for thought at industrial scale. Since Does polished AI output trick audiences into trusting it?, the generated papers exploit the same heuristic: professional-looking output implies expert-quality thinking. And since Should we call LLM errors hallucinations or fabrications?, the process that generates valid theoretical justifications is identical to the process that generates fabricated ones.