One-fifth of computer science papers may contain AI-generated content as surge in AI use is detected across academic fields since ChatGPT's launch

A growing number of computer science research papers may now include content generated by artificial intelligence, with early estimates suggesting that as many as one in five papers published in the field could contain AI-written text. This trend has emerged in the wake of the widespread release of generative AI tools like ChatGPT, which have made it easier than ever to draft, edit, and even generate technical content. Researchers and academic institutions are increasingly grappling with the implications of AI use in scholarly work. While some scientists are using AI tools to assist with writing literature reviews, drafting code comments, or refining language, others are raising concerns about transparency, originality, and the integrity of the research process. A recent analysis of preprints and published papers in computer science found a sharp increase in the use of AI-generated language, particularly in sections such as abstracts, introductions, and methodology descriptions. The study, which examined thousands of papers from major academic repositories, noted that AI-generated phrases often appear in patterns consistent with automated text—such as repetitive sentence structures or overly formal language. The rise in AI use has prompted debate within the academic community. Some experts argue that AI can be a valuable tool for improving efficiency, especially in time-intensive tasks like writing and editing. Others warn that unchecked use could blur the line between human contribution and machine-generated content, potentially undermining the credibility of research. In response, several major conferences and journals in computer science have begun updating their policies to require authors to disclose any use of AI tools in their work. Some have gone further, banning AI-generated text outright or restricting its use to non-substantive tasks. The situation underscores a broader challenge facing academia: how to adapt to rapidly evolving technology while preserving the principles of honesty, rigor, and accountability. As AI becomes more embedded in research workflows, institutions are under pressure to develop clear guidelines that balance innovation with academic integrity.