You, human – Having got us thinking like robots in his previous article, Michael Farrell explains the solutions – and the thinking behind them
Abstract
In this follow-up to his previous piece on machine-like thinking, Michael Farrell explores the enduring gap between machine translation and human understanding. Using linguistic puzzles and historical context, he revisits Yehoshua Bar-Hillel’s argument that machines, lacking real-world knowledge, cannot fully replicate human translation. Farrell demonstrates that while AI systems can mimic co-textual patterns, they fail to grasp cultural and contextual subtleties, such as film title localization. He argues that generative AI, limited by probabilistic reasoning and unaligned data, cannot replace human inference and critical judgment. The article ultimately reaffirms the indispensable role of human translators in a GenAI-driven world.
Published in
ITI Bulletin, July-August 2024
Engaging copy translated literally into English, without taking account of differences in linguistic, semantic and cultural expressions, at best leaves much to be desired and at worst provokes hysterical laughter.
Thanks to my scientific background, I specialize in technical translations. Over the years I have acquired experience in transcreating advertising copy and press releases primarily for the promotion of technology products.
"My opinion is very positive, both of the person and the service."
