Outsider Theorists, Generative AI and the Participation Threshold

This discussion paper examines how generative AI may alter who is able to participate in theoretical work. Instead of asking whether AI will replace experts, it adopts a narrower focus: whether large language models help non academic authors cross the practical threshold from unstructured ideas to manuscripts that are coherent enough for a field to critically assess. Using a stylised comparison between an academic theorist and an outsider with the same idea and access to the same AI tools, the paper argues that AI may act as a leveller at the participation threshold without equalising expertise or institutional advantage. Outsiders gain scaffolding that was previously inaccessible, while insiders gain acceleration. The paper also explores the risks of homogenisation, the ways AI acts as a mediating translator rather than a neutral bridge, and the tension between enabling legibility and constraining originality. Finally, the paper evaluates how restrictive policies toward AI assisted writing risk disproportionately disadvantaging those who rely on AI to reach the starting line. The aim is not to resolve these issues but to prompt discussion about how AI, outsider participation and publication policy interact at the boundary of examinability.