African Languages AI Safety Readiness Report

African languages are largely absent from AI safety research despite billions of speakers: The report identifies that most African languages lack adequate representation in AI safety discussions and benchmarks, creating a significant gap in ensuring these language communities are protected from potential harms of AI systems.

Four key factors determine a language's readiness for AI safety inclusion: The report evaluates languages based on available AI training data, national policy support, performance on text benchmarks, and speaker population size—revealing that many African languages fall short on multiple fronts simultaneously.

Resource constraints perpetuate inequality in AI safety protections: Because research prioritizes high-resource languages, African language communities face a compounding disadvantage where they have both fewer AI safety protections and fewer resources to develop them independently.

Strategic investment can address the gap: The report's four-tier readiness classification system ("fully ready," "mostly ready," "emerging," and "foundational support needed") provides a roadmap for targeted investment in data development, policy frameworks, and community engagement to systematically improve African language inclusion.

AI safety for African languages requires coordinated action across multiple areas: Improving readiness isn't just a technical problem—it requires simultaneous progress on data availability, government policy support, benchmark development, and engagement with speaker communities.