标题： AI扩散在资源匮乏语言国家 显示英文标题

标题： AI Diffusion in Low Resource Language Countries

摘要： 人工智能（AI）正在以史无前例的速度在全球扩散，但采用情况仍不均衡。 前沿大型语言模型（LLMs）由于数据稀缺，在低资源语言上表现不佳。 我们假设这种性能差距降低了人工智能的实用性，从而减缓了低资源语言国家（LRLCs）的采用速度。 为了验证这一点，我们使用加权回归模型将语言影响与社会经济和人口因素分离，发现相对于基线，LRLCs的AI用户占比大约低20%。 这些结果表明，语言可及性是公平AI扩散的一个重要且独立的障碍。 显示英文摘要

摘要： Artificial intelligence (AI) is diffusing globally at unprecedented speed, but adoption remains uneven. Frontier Large Language Models (LLMs) are known to perform poorly on low-resource languages due to data scarcity. We hypothesize that this performance deficit reduces the utility of AI, thereby slowing adoption in Low-Resource Language Countries (LRLCs). To test this, we use a weighted regression model to isolate the language effect from socioeconomic and demographic factors, finding that LRLCs have a share of AI users that is approximately 20% lower relative to their baseline. These results indicate that linguistic accessibility is a significant, independent barrier to equitable AI diffusion.