In the United States, many languages are part of people’s culture and how they communicate. Big cities like Chicago, Los Angeles, and New York have many immigrant communities who speak different languages. Chicago alone has more than 150 languages, such as Spanish, Polish, Mandarin, Arabic, and Tagalog. These languages belong to neighborhoods like Pilsen and Albany Park. As the country becomes more mixed, it is important to study and save both common and endangered languages.
New technology in artificial intelligence (AI) and machine learning is changing how people study languages and keep them alive. This is important for healthcare managers, doctors, and IT workers. They need to know about these changes because they affect how workers and patients talk to each other and how clinics run more smoothly with many languages.
In the past, experts had to do a lot of work by hand to write down and record languages. This work was slow, especially for languages spoken by few people or those without writing systems. Sometimes languages disappeared before enough records were made.
Now, AI and machine learning help speed up this work. Technologies like speech recognition, natural language processing, and machine translation allow researchers to study a lot of recorded speech and text quickly. They can find patterns and organize language information to understand it better.
One example is Dartmouth’s NüshuRescue project. A student named Ivory Yang and her team built a system that uses GPT-4 Turbo to translate and add to a small collection of texts in the rare Nüshu script from China. This system only needed 35 pairs of sentences to start translating well, showing how AI helps even when there is little data.
The University of Chicago also uses AI to study how people talk in daily life within cities. AI looks at billions of words to find changes in language, different dialects, and how people use language, especially in places like hospitals serving immigrant communities. This helps make better ways to communicate and create patient materials in several languages.
UNESCO reports that over 600 languages have disappeared in the last 100 years. It is possible that 90% of the world’s languages could vanish by the end of this century if nothing changes. Many of these languages belong to Indigenous peoples, small immigrant groups, or rural areas with little digital information. Losing these languages means losing history, knowledge, and identity.
AI projects try to stop this loss by making tools to record, learn, and bring back endangered languages. Big tech companies like Google and Microsoft work with universities and Indigenous groups to create automatic speech recognition and translation models for these less common languages.
For example, Google’s Endangered Languages Project digitizes audio recordings and uses AI to make searchable archives. Amazon’s Alexa has a skill for the Oneida language, letting users speak in that Indigenous language. Duolingo offers courses in endangered languages like Hawaiian and Navajo, using AI to personalize learning for new users.
Still, AI has problems with endangered languages because there isn’t much data, and these languages can be complex with tones or mixed language features. AI mostly learns from major languages like English and struggles with dialects or special expressions. For example, Google Translate’s language system often mistakes Native American languages like Navajo. So, Dartmouth researchers created special tools to improve accuracy.
AI developers often work closely with language speakers and experts. They hold training for communities, such as the Cook Islands Māori, teaching members about linguistics and AI tools. This helps people use the technology correctly and keep their language’s true character.
Big U.S. cities like Chicago have many language groups. Hospitals and medical offices must offer services in many languages. Health agencies use bilingual education, translated papers, and interpreters to help patients understand their care.
AI is starting to help with this by offering real-time translation, automated phone answering, and multilingual chatbots. These tools assist patients with booking appointments, paying bills, or understanding medicine instructions in their own language. But it is important the AI does not make mistakes with idioms or medical terms that could confuse people.
Chicago is an example of using AI tools in healthcare. AI can reduce the need for human interpreters in simple front-office tasks. One company, Simbo AI, makes phone systems that recognize many languages and answer calls in Spanish, Mandarin, Arabic, and others common in Chicago. This makes communication faster and easier.
Using AI in healthcare offices helps staff work better and patients wait less. It lets employees focus more on in-person care, billing help, or complex cases that need human attention.
Even with the benefits, AI has problems. If trained on limited or biased data, AI might give wrong results or ignore small languages. Ethical choices in collecting data with permission and protecting privacy are very important to respect communities.
This is especially true in healthcare. Mistakes in language can hurt patients. AI should be tested many times in diverse groups to make sure it is accurate. Experts and community members should always give feedback.
AI should help, not replace, human translators and staff. AI can handle routine tasks well, but it does not understand feelings or cultural details like people do. This is important in medical conversations, especially about tricky or emotional subjects.
Hospital offices have many daily language needs. AI can help by offering services that improve efficiency.
AI phone systems can answer calls and route them by language. They use natural language understanding to get questions right in many languages without human help. They can confirm appointments, share hours, accept prescription refills, or send urgent calls to staff quickly.
AI chatbots on websites or patient portals talk with patients in their first language. Using voice recognition, these tools help people register, confirm insurance, or fill out forms without needing a translator.
For offices, this means fewer phone calls and less work for bilingual staff. IT managers can use AI tools like Simbo AI to improve communication, keep services consistent in many languages, and ensure privacy rules like HIPAA are followed.
The future of AI in language work and healthcare depends on humans and AI working together. Linguists, teachers, and healthcare workers bring deep cultural knowledge and understanding. AI offers fast, repeatable work that saves time and grows reach.
Groups like the Living Tongues Institute and the Indigenous Languages Digital Archive show how technology and Indigenous knowledge can join forces. In healthcare, combining AI with human translators keeps patients safe and improves service in diverse settings.
Training programs now teach healthcare workers how to use AI tools well. Managers will need to guide staff to work side-by-side with AI, fixing errors as they happen.
This mixing of skills helps patients feel understood and fits goals to give fair care to all language groups in the U.S.
Using AI and machine learning in language study and healthcare is a growing field with important effects. Medical managers, clinic owners, and IT staff need to stay updated about these tools. This helps make care clearer, fairer, and kinder to patients who speak many different languages.
Chicago is home to over 150 languages, with significant communities speaking Spanish, Polish, Chinese, Tagalog, and Arabic, among others.
Immigration, particularly in the late 19th and early 20th centuries, has led to the formation of multilingual communities, like Pilsen for Mexicans and Albany Park for Middle Eastern groups.
Language policies support multilingualism by providing language access in government services, education, and community programs, such as translated documents and language assistance.
Preserving linguistic heritage maintains Chicago’s cultural history and enriches its identity, ensuring that diverse voices and traditions are passed on to future generations.
Institutions like the University of Chicago promote linguistic studies through interdisciplinary research, workshops, and seminars that facilitate discussions on language dynamics.
AI and machine learning enhance data analysis in linguistics, enabling real-time language processing and translation, and aiding the preservation of endangered languages.
Community engagement projects allow participants to utilize linguistic insights in real-world contexts, promoting inclusivity and cultural appreciation among diverse backgrounds.
Professional development initiatives often involve workshops and training focused on linguistic skills aimed at educators, community leaders, and professionals in multilingual environments.
Public schools in Chicago often provide bilingual education to foster multilingualism among younger generations and promote the integration of diverse linguistic communities.
Critical race theory informs discussions by highlighting the intersections of language, identity, and power dynamics, emphasizing the value of diverse languages in Chicago’s cultural landscape.
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