Can AI help save indigenous languages?
Overview
Every two weeks an indigenous language disappears around the world according to the United Nations. This lesson explores how AI, using Natural Language Processing (NLP), can potentially save dying languages by documenting, translating, and making these languages more accessible for learning and communication. Students will also explore how AI bias and cultural concerns play an important role in language preservation and revitalization.
- AI & History-Social Science
- 60 minutes
Digital Materials
- Other
- When A.I. Fails the Language Test, Who Is Left Out of the Conversation?
- The Race to Save the World’s Vanishing Languages
- Listen to Native Americans in their own language
- Will AI be able to speak your language? | Linda Heimisdóttir | TEDxReykjavik
- Why First Languages AI Can Be a Reality | Michael Running Wolf | TEDxBoston
Objectives
- Explain how AI can help preserve and revitalize indigenous languages.
- Discuss ways AI bridges barriers allowing people to learn and practice their original language.
- Summarize key arguments on the limitations of AI in understanding cultural contexts and oral traditions of indigenous languages.
Questions explored
- The challenges of insufficient indigenous audio and text data.
- The importance of involving indigenous researchers and engineers in AI design.
Key Terms
Artificial Intelligence (AI)
- The ability of computers to imitate human-like thinking, learning, and problem-solving.
Large Language Model (LLM)
- A very big AI model that predicts many complicated sequences of text or code, using billions of data points. Some of these can produce text or code that looks more like what humans can do.