How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866911730868682752 |
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| author | Daepp, Madeleine I. G. Slaughter, Isaac |
| author_facet | Daepp, Madeleine I. G. Slaughter, Isaac |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_30685 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language Daepp, Madeleine I. G. Slaughter, Isaac Computers and Society Artificial Intelligence Computation and Language Human-Computer Interaction J.4; K.4.2; H.4.0 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. |
| title | How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language |
| topic | Computers and Society Artificial Intelligence Computation and Language Human-Computer Interaction J.4; K.4.2; H.4.0 |
| url | https://arxiv.org/abs/2605.30685 |