arXiv Computation and Language

Artificial intelligence is creating a new global linguistic hierarchy

The paper analyzes the distribution of artificial intelligence resources across 6,003 languages, revealing that a small number of languages dominate and that disparities are widening exponentially. It compares the diffusion of AI with earlier information technologies, noting a hype-driven spread pattern. The authors introduce the Language AI Readiness Index (EQUATE) to map technological, socio-economic, and infrastructural prerequisites for AI deployment, aiming to guide equitable diffusion of language AI.

arXiv Computation and Language
Oct 21

African Languages AI Safety Readiness Report

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 Computation and Language
Oct 1

Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigations

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
arXiv Computation and Language
Sep 4

Beyond Accuracy: Community Perspectives on Machine Translation

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 AI
Jun 12

From AGI to ASI

arXiv:2606. 12683v1 Announce Type: new Abstract: Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI organisations.

By Tim Genewein, Matija Franklin, Alexander Lerchner, Laurent Orseau, Samuel Albanie, Adam Bales, Cole Wyeth, Stephanie Chan, Iason Gabriel, Joel Z. Leibo, Allan Dafoe, Marcus Hutter, Thore Graepel, Shane Legg
arXiv AI
Jul 8

Rethinking Indic AI from a Lens of Cultural Heritage Preservation

arXiv:2607. 06544v1 Announce Type: new Abstract: As Artificial Intelligence (AI) makes inroads into different parts of the Indian subcontinent, there is significant interest in studying how AI impacts the linguistic and cultural foundations of this civilization.

By Aparna Madva, Sharath Srivatsa, Srinath Srinivasa, Tulika Saha