Opinion: Apple's translating AirPods won't work without state's language grads

"But the better machines get at translating words, the more essential human expertise becomes in understanding meaning. Far from being obsolete, language degrees are the very foundation for preparing graduates to use, guide and improve these technologies. Universities must train students to do what machines cannot. A degree in Spanish, Arabic or ancient Greek equips students with practical tools for understanding how people think, how history shapes communication and how cultural context changes meaning."

"Last month, Apple unveiled its newest AirPods with a feature straight out of science fiction: slip them in, and they will translate a foreign language directly into your ears. The technology is remarkable. As Brian X. Chen noted in The New York Times, a conversation in Spanish became instantly comprehensible to him, despite his never having studied the language. Such advances might suggest that the study of languages is becoming obsolete."

"These skills are directly useful in business, diplomacy, healthcare, technology and any field where working across cultures is part of the job. In California, with 40% of residents speaking a language other than English at home, these competencies are everyday necessities. Far from being replaced by technology, language graduates are often the ones who make technology work. Universities face pressure to cut programs deemed non-essential. Language departments have too often been the first on the chopping block, especially when enrollments dip."

Apple introduced AirPods that can translate spoken foreign languages in real time, making conversations instantly comprehensible. Such machine progress raises questions about language study, but human expertise remains crucial for interpreting cultural and historical context. Language degrees train students in grammar, corpora curation, and nuanced meaning, skills valuable across business, diplomacy, healthcare, and technology. Large language models rely on human-curated corpora, grammatical analysis, and expert evaluation; without investment in less-commonly-taught languages, AI systems risk bias and shallowness. Universities face pressures to cut language programs; many programs have already disappeared, threatening the pipeline of experts needed to develop and vet translation technologies.

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