AI is being used by people globally, but not everyone is using it in the same ways. Using a large-scale dataset of anonymized, de-identified, and privacy-scrubbed interactions with a widely available and free AI chatbot, we empirically characterize differences in early adopters' usage across countries. Schooling is the most common domain of use in most countries, particularly low-income countries, with a strong inverse association evident between schooling and country-level GDP. Leisure-related use, by contrast, is positively associated with country-level income. Language, we find, also shapes use: English-language interactions are overrepresented in places where the predominant languages were not well-served by existing models during the period of the study. Improving performance across languages may be a key factor, our work suggests, in whether this technology expands digital divides or enables leapfrogging.

翻译：人工智能正被全球各地的人们所使用，然而其使用方式并非千篇一律。基于一个大规模数据集，其中包含与一款广泛可用的免费AI聊天机器人之间匿名的、去标识化的且经隐私处理的交互记录，我们通过实证方式刻画了不同国家早期采用者在使用模式上的差异。在大多数国家，尤其是低收入国家，教育是最普遍的应用领域；显而易见，教育用途与国家层面的GDP之间存在强烈的负相关关系。相比之下，与休闲相关的使用与国家层面的收入水平呈正相关。我们发现，语言同样塑造着使用模式：在研究期间，那些主流语言未能得到现有模型良好服务的地区，英语交互的比例异常偏高。我们的研究指出，提升跨语言性能可能是决定该技术究竟是扩大数字鸿沟，还是助力实现跨越式发展的关键因素。