The use of artificial intelligence is exploding around the world, but the technology’s language models are primarily trained in English, leaving many speakers of other languages behind.
Stanford researchers gave a popular A.I. chatbot a language test.
They asked the bot in Vietnamese to write a traditional poem in the form known as “song thất lục bát” that follows a pattern of lines made up of seven, seven, six, then eight words. When the bot spit out an answer, it wrote a poem, but didn’t follow the format.
The team tried a different prompt, asking what the proper Vietnamese word was for a mother’s younger brother, and it responded with the words for a father’s younger and older siblings.
These flaws are not unique to Claude 3.5, the chatbot by the artificial intelligence company Anthropic that the researchers queried, but they illustrate some of the ways in which artificial intelligence can get language outside of standard American English wrong.
While the use of A.I. has exploded in the West, much of the rest of the world has been left out of the conversation since most of the technology is trained in English. A.I. experts worry that the language gap could exacerbate technological inequities, and that it could leave many regions and cultures behind.
A delay of access to good technology of even a few years, “can potentially lead to a few decades of economic delay,” said Sang Truong, a Ph.D. candidate at the Stanford Artificial Intelligence Laboratory at Stanford University on the team that built and tested a Vietnamese language model against others.
The tests his team ran found that A.I. tools across the board could get facts and diction wrong when working with Vietnamese, likely because it is a “low-resource” language by industry standards, which means that there aren’t sufficient data sets and content available online for the A.I. model to learn from.