AI Literacy in Low-Resource Languages:Insights from creating AI in Yoruba videos
To effectively navigate the AI revolution, AI literacy is crucial. However, content predominantly exists in dominant languages, creating a gap for low-resource languages like Yoruba (41 million native speakers). This case study explores bridging this gap by creating and distributing AI videos in Yoruba.The project developed 26 videos covering foundational, intermediate, and advanced AI concepts, leveraging storytelling and accessible explanations. These videos were created using a cost-effective methodology and distributed across YouTube, LinkedIn, and Twitter, reaching an estimated global audience of 22 countries. Analysis of YouTube reveals insights into viewing patterns, with the 25-44 age group contributing the most views. Notably, over half of the traffic originated from external sources, highlighting the potential of cross-platform promotion.This study demonstrates the feasibility and impact of creating AI literacy content in low-resource languages. It emphasizes that accurate interpretation requires both technical expertise in AI and fluency in the target language. This work contributes a replicable methodology, a 22-word Yoruba AI vocabulary, and data-driven insights into audience demographics and acquisition channel
Code (0)
등록된 구현이 없습니다.
Tasks
NavigateSimilar Papers 제목 키워드 기반
Cost Analysis of Human-corrected Transcription for Predominately Oral Languages
Creating speech datasets for low-resource languages is a critical yet poorly understood challenge, particularly regarding the actual cost in human labor. This paper investigates the time and complexity required to produc…
Multilingual Dependency Parsing for Low-Resource African Languages: Case Studies on Bambara, Wolof, and Yoruba
This paper describes a methodology for syntactic knowledge transfer between high-resource languages to extremely low-resource languages. The methodology consists in leveraging multilingual BERT self-attention model pretr…
Dependency ParsingMultilingual Word EmbeddingsTransfer LearningWord Embeddingsyosm: A new yoruba sentiment corpus for movie reviews
A movie that is thoroughly enjoyed and recommended by an individual might be hated by another. One characteristic of humans is the ability to have feelings which could be positive or negative. To automatically classify a…
Opinion MiningSentiment AnalysisSentiment ClassificationYankari: A Monolingual Yoruba Dataset
This paper presents Yankari, a large-scale monolingual dataset for the Yoruba language, aimed at addressing the critical gap in Natural Language Processing (NLP) resources for this important West African language. Despit…
Yor\`ub\'a Dependency Treebank (YTB)
Low-resource languages present enormous NLP opportunities as well as varying degrees of difficulties. The newly released treebank of hand-annotated parts of the Yoruba Bible provides an avenue for dependency analysis of …
Articles