What's Happening?
A critical analysis highlights the risks associated with artificial intelligence models that exclude oral histories and lesser-known languages. The article argues that large language models, by omitting
significant sources of information, marginalize people in less dominant cultures. Deepak Varuvel Dennison, a PhD student at Cornell University, emphasizes the importance of preserving diverse knowledge systems to ensure the resilience and diversity of human understanding. The article explores the implications of AI's reliance on predominantly Western and institutional knowledge, which may lead to the erasure of alternative ways of knowing.
Why It's Important?
The exclusion of diverse knowledge systems in AI models poses significant challenges to cultural preservation and the representation of marginalized communities. By prioritizing dominant languages and epistemologies, AI risks perpetuating existing power imbalances and erasing valuable insights and wisdom. This issue highlights the need for responsible AI development that considers the inclusion of diverse perspectives and knowledge sources. Ensuring the representation of lesser-known languages and oral traditions is crucial for maintaining the richness and diversity of human understanding.
