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Not long from now, we may see simultaneous interpretation move beyond its traditional home, those glass-walled booths at international summits and corporate conferences. For decades, interpreters have worked behind the scenes, their voices flowing invisibly into headsets, turning one language into another with precision and care. It has always been a service reserved for the…

In my career at the intersection of language and technology, I’ve often felt like an outsider in the world of code. I never formally studied informatics or learned programming the “proper” way. Instead, I stumbled into it out of necessity, curiosity, and often frustration that the tools I needed as a linguist or translator and…

Recently, researchers at MIT conducted a striking experiment1. Participants were divided into three groups and asked to write a short composition. One group relied solely on their own cognitive resources. Another could consult the internet. The third turned to automated writing tools, including ChatGPT. Brain scans revealed a clear — and perhaps unsurprising — pattern:…

The field of multilingual communication is undergoing a profound transformation. This transformation is rapidly ushering in an AI-first paradigm, a reality in which AI will be the default agent for translation and interpreting services. This shift is not distant or speculative; it is already underway, albeit still in the early stages for real-time spoken translation….

AI or machine interpreting refers to the use of software to translate one spoken language into another (including sign language) in real-time, without human intervention or post-editing. It’s designed for immediate, dynamic communication, whether remote, face-to-face, simultaneous, or consecutive. Speech translation technology has a fairly long history and has been evolving rapidly in recent years,…

Year 2019. Geneva. At a time when technology still seemed distant from the profession of interpreting, I was a young scholar who dared to advocate for a paradigm shift in interpreting. In a panel on interpreter training, I reminded the interpreting academic community of its duty to prepare students and professionals not just for today…

A few weeks ago, I wrote about the intellectual and practical need to develop a Turing Test for Speech Translation to measure whether AI-driven interpreting systems have achieved high level performance in real-time language translation. The proposed test would be passed only when human judges can no longer distinguish whether a translation was produced by…

Recent advancements in artificial intelligence have seen Large Language Models (LLMs) pass the famous Turing Test in conversational settings, marking a milestone in AI development. This achievement, demonstrated in some recent empirical studies, illustrates just how closely AI-driven dialogue systems have begun to mimic genuine human interactions. This should also serve as a reminder that…

Machine interpreting (MI), like any emerging technology, presents a range of ethical challenges that require careful consideration and governance (Cath, 2018; Floridi, 2021). Designed to enhance communication and understanding across language barriers, from everyday interactions to high-stakes scenarios, this technology has the potential to significantly impact diverse areas of human life. For this reason, its…

In the rapidly evolving approaches to academic work, where digital resources and artificial intelligence are transforming the way research is conducted, there remains a steadfast beacon of scholarly rigor in Interpreting Studies: the CIRIN Bulletin. Compiled biannually by Daniel Gile, one of the most esteemed figures in the discipline, the CIRIN Bulletin is far more…