Researcher Outlines a New Approach to AI-Based Text Detection Systems
Modern academic integrity tools are shifting from policing authors to helping them improve their work.
A new ethics of academic review and a shift from control to support were outlined to IT Russia by Yuri Chekhovich, PhD in physics and mathematics, an expert in academic ethics, machine learning, and AI, head of Laboratory No. 42 at the Institute of Control Sciences of the Russian Academy of Sciences, and founder of the Domate academic text analysis service.
According to Chekhovich, unlike traditional detection systems such as Antiplagiat, which were historically designed as barrier tools for reviewers, Domate is built on a different philosophy. The service is designed to integrate naturally into the learning process, shifting the focus from enforcement to supporting authors.
In his view, a good review report is not a percentage score, but a tool that helps improve a text and provides clear explanations for both authors and reviewers. This is the format Domate is striving to achieve. The goal of the service is to create an environment for constructive dialogue between authors and reviewers, so that learning does not turn into a competition over how to bypass the system.
Designed for Support, Not Control
The Domate service was initially developed for universities and research institutes, but its functionality has also proven useful for academic publishers, libraries, and even commercial organizations. The tool is based on modern AI algorithms for search and in-depth text analysis. It includes the full range of features familiar to universities, including plagiarism detection, identification of citations and self-citations, AI-generated text detection, translated borrowing, and paraphrase detection.
Simply trying to ban AI tools is pointless, the expert argues. Instead, all participants in the process need support in staying within ethical boundaries, turning review into a constructive dialogue rather than a punitive exercise.
