Abstract

As a collaboratively edited and open-access knowledge archive, Wikipedia offers a vast dataset for training artificial intelligence (AI) applications and models, enhancing data accessibility and access to information. However, reliance on the crowd-sourced encyclopedia raises ethical issues related to data provenance, knowledge production, curation, and digital labor. Drawing on critical data studies, feminist posthumanism, and recent research at the intersection of Wikimedia and AI, this study employs problem-centered expert interviews to investigate the relationship between Wikipedia and large language models (LLMs). Key findings include the unclear role of Wikipedia in LLM training, ethical issues, and potential solutions for systemic biases and sustainability challenges. By foregrounding these concerns, this study contributes to ongoing discourses on the responsible use of AI in digital knowledge production and information management. Ultimately, this article calls for greater transparency and accountability in how big tech entities use open-access datasets like Wikipedia, advocating for collaborative frameworks prioritizing ethical considerations and equitable representation.