AI for whom and by whom? Cultural bias and the institutional and social shaping of large language models
DETAILS
Call for Papers
AI for whom and by whom? Cultural bias and the institutional and social shaping of large language models
Journal: Technological Forecasting and Social Change
Publisher: Elsevier
Submission Opens: 1 September 2026
Manuscript Submission Deadline: 30 April 2027
Introduction
Large language models (LLMs) embed Western cultural biases through English-centric datasets and concentrated innovation ecosystems, raising concerns about digital colonialism and knowledge extractivism in the Global South. This Special Issue examines LLMs as socio-technical systems shaped by governance, regional AI ecosystems, university-industry collaborations, and their implications for legitimized knowledge and global power asymmetries.
Guest Editors
Beatrice Orlando (Beatrice.orlando@unife.it)
Marcus Wagner (marcus.wagner@uni-a.de)
Janet Rafner (jraf@sam.sdu.dk)
Thierry Burger-Helmchen (burger@unistra.fr)
List of Topic Areas
Submissions invited on:
Cultural/linguistic biases in LLM training data and deployment
Digital colonialism, knowledge extractivism affecting Global South
Comparative regional LLM ecosystems (US, EU, China, Global South)
University roles in LLM research, open models, industry collaborations
Governance frameworks addressing cultural pluralism in AI
Participatory foresight/co-design for socially accountable LLMs
Guest Editors Contact Details
Name | Institution | |
|---|---|---|
Beatrice Orlando | University of Ferrara | |
Marcus Wagner | University of Augsburg | |
Janet Rafner | University of Southern Denmark | |
Thierry Burger-Helmchen | University of Strasbourg |
Submission Process & Deadlines
Submit via Editorial Manager at https://www2.cloud.editorialmanager.com/tfs/default2.aspx, selecting "VSI: AI for whom by whom".
Submission Guidelines
Guide for Authors: https://www.sciencedirect.com/journal/technological-forecasting-and-social-change/publish/guide-for-authors
About the Journal
Technological Forecasting and Social Change (Impact Factor 13.3, CiteScore 26.3) leads research on technology evolution, innovation systems, and societal impacts.
Guest Editors: Beatrice Orlando, Marcus Wagner, Janet Rafner, Thierry Burger-Helmchen
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