Model Documentation

Model documentation, aiming to ensure transparency and responsible use of increasingly complex AI models, is a burgeoning research area. Current efforts focus on improving the completeness and accessibility of model cards, exploring methods for automated metadata extraction, and developing interactive documentation formats tailored to diverse user expertise levels. Research investigates the impact of improved documentation on model adoption and trust, analyzing both the content of existing documentation and the effectiveness of interventions designed to improve it. This work is crucial for fostering responsible AI development and deployment across various scientific and practical applications.