UConn Studies How Language Shapes AI Understanding

The University of Connecticut is studying how language shapes the way artificial intelligence understands people. Its new project, “Reading Between the Lines: An Interdisciplinary Glossary for Human-Centered AI,” looks at how words such as “intelligence,” “learning” and “ethics” are defined differently across cultures and why those differences matter as AI becomes embedded in daily life.

The programme, featured in UConn Today, brings together researchers to help institutions build systems that reflect cultural diversity rather than erase it. “If we want an expansive, inclusive, liberatory AI, we need to start with how we talk about it,” saeid Anna Mae Duane, director of the UConn Humanities Institute.

UConn’s research comes at a time when global studies are finding persistent gaps in how artificial intelligence models handle different languages and dialects. A 2025 Johns Hopkins University study found that multilingual models still privilege English and other dominant languages,while a MIT Sloan analysis showed that the same AI prompt can produce very different responses depending on the language used. these findings underscore why UConn’s work is focusing on language as the foundation for inclusion, accuracy and trust in AI.

Cultural Framework of Intelligence

The UConn initiative examines three themes: care, literacy and rights, that frame how people and machines understand each other. The “care” dimension focuses on empathy and communication. “Care begins with language,” said Ihsane Hamamouchi of the Université Internationale de Rabat, explaining that AI systems trained on limited datasets