THE EVOLUTION OF NOTE-TAKING IN THE AGE OF AI-ASSISTED SIMULTANEOUS INTERPRETING: A THEORITICAL AND CONCEPTUAL REASSESSMENT - ABDUJABBOROVA, Madinakhon Shuhratjon qizi (The Lingua Spectrum, 2025)
Artificial intelligence (AI) is changing interpreting process by introducing tools that offer automatic speech recognition, predictive terminology, and real-time transcription. While AI has been discussed widely in translation studies, its effect on note-taking remains underexplored, particularly in simultaneous interpreting (SI), where note-taking is subtle but significant. This article re-examines the function of note-taking in SI in light of emerging AI-assisted workflows. It is aimed to investigate how interpreters adapt note-taking strategies conceptually while using AI tools, by drawing on Gile’s Effort Model, cognitive load theory and multimodal processing research. AI helps to reorganize not-taking enabling interpreters use it as a tool for monitoring errors, maintaining cognitive stability and ensure quality in the process. Even though AI may increase cognitive load as it causes split attention, it still mitigates other issues, such as terminological retrieval. These changes lead to restructuring the form of note-taking, rather than extinguishing it. The study concludes by proposing a conceptual model of “supervisory note-taking” and offering implications for interpreter training and future research.