@inproceedings{nejadgholi-etal-2026-defining,
    title = "Defining Cultural Capabilities for {AI} Evaluation: A Taxonomy Grounded in Intercultural Communication Theory",
    author = "Nejadgholi, Isar  and
      Kianpour, Masoud  and
      Vishnubhotla, Krishnapriya  and
      Molamohammadi, Maryam",
    editor = "Akhtar, Mubashara  and
      Batzner, Jan  and
      Choshen, Leshem  and
      Ghosh, Avijit  and
      Gohar, Usman  and
      Mickel, Jennifer  and
      Pant, Ichhya  and
      Talat, Zeerak  and
      Lin, Michelle",
    booktitle = "Proceedings of the Workshop on Evaluating Evaluations ({E}val{E}val)",
    month = jul,
    year = "2026",
    address = "San Diego, CA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.evaleval-1.26/",
    pages = "161--173",
    ISBN = "979-8-89176-429-3",
    abstract = "Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities considered in much of the literature remain vaguely defined, are referred to using interchangeable terminology, and are typically limited to recalling accurate information about various demographics, regions, and nationalities. To address this construct ambiguity, we draw from Intercultural Communication scholarship and propose a three-level taxonomy of AI-relevant cultural capabilities: Cultural Awareness answers ``Does the model know?'', Cultural Sensitivity answers ``How does it frame its knowledge?'', and Cultural Competence answers ``Can it adapt as the interaction evolves?''. Beyond conceptual clarification, we position this taxonomy as a practical tool for improving the validity and interpretability of AI evaluation in real-world, multicultural settings. Without such construct clarity, evaluation results risk overstating model capabilities and may lead to inappropriate deployment decisions in culturally sensitive contexts."
}