3 accepted papers
Open source projects have made incredible progress in producing widely usable machine learning models and systems, but open source alone will face challenges in fully democratizing access to AI. Unlike previous generations of open source software, open source and open weight AI models require substa…
This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, small-to-medium sized producers of information (such as journalists, news organizations, researchers, and creative professionals) need to be able to appoint rep…
This paper contributes a formal case study in retrospective dataset documentation and pinpoints several problems with the influential BookCorpus dataset. Recent work has underscored the importance of dataset documentation in machine learning research, including by addressing ``documentation debt'' f…