Culture perspective shapes natural language processing research
Supporting and Performing Culture from the Inside
Computation and LanguageArtificial IntelligenceComputers and Society
Summary
Understanding culture is important in language technology, but there are different ways to study culture: from inside the culture itself (emic) or from outside as an observer (etic). The authors looked at how language AI research deals with culture throughout its processes, like choosing tasks, gathering data, designing systems, and testing them. They highlight how the general culture within AI research influences what is studied and how. The paper suggests ways to make AI more sensitive to cultural views by including insider perspectives.
What this means in practice
- •For language technology developers: Design AI language systems that incorporate cultural insider perspectives to improve cultural relevance and sensitivity of outputs.
- •For social media platform teams: Improve content moderation tools by accounting for diverse cultural viewpoints, reducing misunderstandings caused by cultural bias.
A position paper. It proposes an approach and reports no results.
Authors
Lea Frermann, Steven Bird
Abstract
Anthropology and related disciplines which study culture have often found it useful to consider their epistemological and methodological approaches in terms of emic versus etic. This is the distinction between the insider perspective, how the world is viewed by a member of the culture, versus the outsider perspective, the scientific cataloguing of cultural knowledge and practice. We adopt this framework to systematically analyse assumptions in recent research on culture in NLP along the full pipeline of task selection, data collection, system design and evaluation. We draw attention to the `culture of NLP' which shapes the research focus and approaches of our field, and suggest pathways towards a more culturally attuned AI.