Tener gripe, tener gripa, engriparse, agriparse, estar agripado, estar griposo, agarrar la gripe, coger la influenza. In Spanish, there are at least a dozen ways to say someone has the flu — depending on the country.

Translating “cardiac arrest” into Spanish is also tricky because “arresto” means getting detained by the police. Likewise, “intoxicado” means you have food poisoning, not that you’re drunk.

The examples of how translation could go awry in any language are endless: Words take on new meanings, idioms come and go, and communities adopt slang and dialects for everyday life.

Human translators work hard to keep up with the changes, but California plans to soon entrust that responsibility to technology.

State health policy officials want to harness emerging artificial intelligence technology to translate a broad swath of documents and websites related to “health and social services information, programs, benefits and services,” according to state records. Sami Gallegos, a spokesperson for California’s Health and Human Services Agency, declined to elaborate on which documents and languages would be involved, saying that information is “confidential.”

The agency is seeking bids from IT firms for the ambitious initiative, though its timing and cost is not yet clear. Human editors supervising the project will oversee and edit the translations, Gallegos said.

Agency officials said they hope to save money and make critical health care forms, applications, websites, and other information available to more people in what they call the nation’s most linguistically diverse state.

The project will start by translating written material. Agency Secretary Mark Ghaly said the technology, if successful, may be applied more broadly.

“How can we potentially not just transform all of our documents, but our websites, our ability to interact, even some of our call center inputs, around AI?” Ghaly asked during an April briefing on AI in health care in Sacramento.

But some translators and scholars fear the technology lacks the nuance of human interaction and isn’t ready for the challenge. Turning this sensitive work over to machines could create errors in wording and understanding, they say — ultimately making information less accurate and less accessible to patients.

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