The discussion around AI tools that identify errors in research papers emphasizes the potential benefits and challenges of integrating artificial intelligence into academic publishing. Proponents argue that AI can enhance the quality of research submissions by flagging obvious mistakes before submission, thus improving the peer review process. This shift could elevate the overall standards of academic work, particularly for new authors. However, there are concerns about the accuracy of these tools, particularly regarding false positives and the possibility that reliance on AI could lead to serious oversight of nuanced errors that require expert judgment. Moreover, there is a discourse on the potential misuse of AI in controlling the narrative of scientific topics and research priorities, and worries about bias in how AI tools are implemented within the academic community. Overall, while AI tools present significant opportunities to streamline research error detection, a cautious and critical approach is necessary to balance efficiency with the integrity of scientific discourse.