2024/03/19 by Robin Quillivic, Quillivic, Robin, Salma Mesmoudi +1
Business, Management and Accounting · #Big Data and Business Intelligence #Computers and Society (cs.CY) #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2403.12774
openalex publication_date 2024/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Language models (LM or LLM) are increasingly deployed in the field of artificial intelligence (AI) and its applications, but the question arises as to whether they can be a common resource managed and maintained by a community of users. Indeed, the dominance of private companies with exclusive access to massive data and language processing resources can create inequalities and biases in LM, as well as obstacles to innovation for those who do not have the same resources necessary for their implementation. In this contribution, we examine the concept of the commons and its relevance for thinking about LM. We highlight the potential benefits of treating the data and resources needed to create LMs as commons, including increased accessibility, equity, and transparency in the development and use of AI technologies. Finally, we present a case study centered on the Hugging Face platform, an open-source platform for deep learning designed to encourage collaboration and sharing among AI designers.