Journal of Business and Technical Communication Jan 2025

Technical Communication's Fight Against Extractive Large Language Modeling by Applying FAIR and CARE Principles of Data

Chris A. Lindgren ; Erin Yunes Virginia Tech ; Cana Uluak Itchuaqiyaq Virginia Tech

Abstract

This article assesses the data practices of Grammarly, the prominent AI-assisted writing technology, by applying data principles that advocate for empowering Indigenous data sovereignty. The assessment is informed by the authors’ work with an Inuit tribal organization from rural Arctic Alaska that generated data and metadata about potentially sacred tribal activities. Their analysis of Grammarly's large-language modeling practices demonstrates how technical communication can hold businesses to principled data practices created by Indigenous nations and communities that understand how to create more just futures.

Journal
Journal of Business and Technical Communication
Published
2025-01-01
DOI
10.1177/10506519241280587
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Topics
assessment technical communication artificial intelligence
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Citation Context

Cited by in this index (3)

  1. Mallette et al. (2026)
    Preparing to Edit Ethically with and for AI Contexts
    Technical Communication Quarterly
  2. Muthyala et al. (2025)
    Demystifying Chatbot Creation: A Comparative Case Study of Available Approaches
    IEEE Transactions on Professional Communication
  3. Long et al. (2025)
    Reimagining Archives in the Age of Automation: A Decolonial and Relational Approach
    Technical Communication Quarterly

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CrossRef global citation count: 5 View in citation network → Build reading path →

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