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ACL 2026aclfindings

LLMs in the Real World: Evaluating “AI” in Emergency Contexts

Sara Court, Lara Downing, Micha Elsner

Ohio State University, Columbus · Community Refugee and Immigration Services · Ohio State University

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2026.findings-acl.1779 ↗

摘要

This paper offers a call to action. We urge our colleagues in the research community to play a greater role in the articulation of our findings to the public. To illustrate the stakes we present a case study on the initial stages of an LLM-based machine translation application’s deployment in a real-world context: a text-2-911 system advertising capabilities in 55 languages for use in emergencies in which it may be difficult to call operators directly. We identify a number of common misconceptions about technologies such as these, concluding with a set of concrete recommendations and best practices for stakeholders at every stage of the development and deployment pipeline. While the advancement of scientific research often lies in solving the "hard" problems, we argue it is often the "easy" ones— problems for which the latest technology is often unnecessary— that are most overlooked.