Neural machine translation (NMT), or AI that can translate between languages, is in widespread use today, owing to its robustness and versatility. But NMT systems can be manipulated if provided prompts containing certain words, phrases, or alphanumeric symbols. For example, in 2015 Google had to fix a bug that caused Google Translate to offer homophobic slurs like “poof” and “queen” to those translating the word “gay” from English into Spanish, French, or Portuguese. In another glitch, Reddit users discovered that typing repeated words like “dog” into Translate and asking the system for a translation to English yielded “doomsday predictions.”

A new study from researchers at the University of Melbourne, Facebook, Twitter, and Amazon suggests NMT systems are even more vulnerable than previously believed. By focusing on a process called back-translation, an attacker could elicit “toxic behavior” from a system by inserting only a few words or sentences into the dataset used to train the underlying model, the coauthors found. Read More