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1 month ago
Welcome to the third edition of AI expo!
AI expo brings together industry leaders, experts, and innovators to share their knowledge and experience. Explore emerging trends in translation and interpretation through diverse presentations, and uncover the array of possibilities that AI offers to language professionals.
Drawing from real-world experience, she will show how AI can be used not just as a productivity tool, but as a foundation for entirely new services such as AI-assisted workflows, prompt design, quality assurance systems, and consulting. Participants will learn: how the role of translators is shifting in the age of AI, which new services are in demand, how to turn AI skills into paid offerings, and practical examples of AI workflows used in real client projects. This session is designed for freelance language professionals and LSPs who want to stay relevant, increase their value, and explore new revenue streams in an AI-driven industry.
The genre competence is real; the epistemic work behind it may be absent. This session introduces the concept of the "smoothness trap" and offers practical methods for detecting where AI-generated text performs understanding without possessing it. Drawing on three years of teaching critical AI methods to media professionals and humanities scholars, I'll demonstrate specific techniques language professionals can use to audit LLM output — not just for errors, but for the invisible places where fluency silently substitutes for thought.
One paper reveals how the latest MT systems are learning to understand meaning visually, not just statistically, with dramatic quality improvements for under-resourced languages. The other offers a surprising discovery: that how well an AI translates a language tells you almost everything about how well it understands that language — and where it will let you down. We'll use these findings to build a practical collaboration framework: when to trust MT output, when to post-edit lightly, when to intervene heavily, and which domains and language pairs always need your full human expertise.
No prior technical background required — just a curiosity about how AI actually works and a desire to collaborate with it on your own terms. Because mastering human-AI collaboration doesn't mean knowing everything about AI. It means knowing enough to stay in control.
Drawing on the philosophy behind wxrks, Gabriel will demonstrate how the latest advancements in AI aren't meant to replace the human element, but to scale it. He will break down the "Smoothness Trap" of LLMs and show why the translator’s intuition—their "soul"—is the only variable that provides the high-level context and truth that enterprise customers actually value. Attendees will leave with a practical framework for moving from a per-word technician to an AI-augmented architect, learning how to use technology to amplify their unique expertise rather than hide it.
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