arXiv:2608. 12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced communities.
By Avijit Roy, Proma Roy
arXiv:2606. 30656v1 Announce Type: cross Abstract: Artificial Intelligence (AI) has the potential to be transformative for development, but Africa is currently facing a fragmented and challenging "AI divide".
By Abayomi O. Agbeyangi, Jose M. Lukose
arXiv:2610.27269v1 Announce Type: new
Abstract: With the widespread adoption of large language models (LLMs) across languages and domains, AI safety has emerged as a critical global concern. However,...
By Israel Abebe Azime, Jesujoba O. Alabi, Tajuddeen Gwadabe, David Ifeoluwa Adelani
arXiv:2609.38486v1 Announce Type: cross
Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomen...
By Ismael T. Freire, Marceau Nahon, Maud van Lier, Katie Evans, H\'elie Bazin, Michele Farisco, Kathinka Evers, Raja Chatila, Mehdi Khamassi
The paper examines how four stakeholder groups—AI developers, professional translators, language learners, and language service providers—discuss machine translation on social media. Using a dataset of 79,286 posts from Reddit, Facebook, Bluesky, and Mastodon (2019‑2025), the authors find frequent disagreements and strong conflicts over translation quality, efficiency, and reliability. These conflicts arise because AI communities view the issues as technical, while non‑AI users prioritize quality nuances, time savings, trust, and broader social concerns.
By Yujun Wang, Ehud Reiter, Shimei Pan, Steffen Eger, Wei Zhao
arXiv:2607. 19375v1 Announce Type: cross Abstract: Language models perform economically valuable work, yet they are not currently assessed for how well they perform every economically valuable task.
By Alexander Wan, Stephane Hatgis-Kessell, Tom\'as Aguirre, Percy Liang, Rishi Bommasani