Detecting generative artificial intelligence in scientific articles: Evasion techniques and implications for scientific integrity.

Journal: Orthopaedics & traumatology, surgery & research : OTSR
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI) tools, although beneficial for data collection and analysis, can also facilitate scientific fraud. AI detectors can help resolve this problem, but their effectiveness depends on their ability to track AI progress. In addition, many methods of evading AI detection exist and their constantly evolving sophistication can make the task more difficult. Thus, from an AI-generated text, we wanted to: (1) evaluate the AI detection sites on a text generated entirely by the AI, (2) test the methods described for evading AI detection, and (3) evaluate the effectiveness of these methods to evade AI detection on the sites tested previously.

Authors

  • Guillаumе-Аnthоny Оdri
    Sеrvicе dе chirurgiе оrthоpédiquе еt trаumаtоlоgiquе, cеntrе hоspitаliеr univеrsitаirе Lаribоisièrе, 2, ruе Аmbrоisе-Pаré, 75010 Pаris, Frаncе; Insеrm U1132 BIОSCАR, univеrsité Pаris-Cité, 75010 Pаris, Frаncе. Electronic address: guillaume.odri@aphp.fr.
  • Diаnе Ji Yun Yооn
    Insеrm U1132 BIОSCАR, univеrsité Pаris-Cité, 75010 Pаris, Frаncе.