The AI in Science Report скачать в хорошем качестве

The AI in Science Report

AI in Science ReportL https://royalsociety.org/news-resourc... Summary • Rethinking Reproducibility: A universal approach to achieving reproducibility may not be desirable, as it demands high control over environmental and social conditions. • Context-Dependent Models: Models that are not generalizable across contexts can offer valuable insights while explainability answers why certain conclusions are reached or what else the model can tell us. • Explainable AI (XAI): XAI methods are emerging in fields such as material science, biomedicine, and earth science to improve the interpretability and trustworthiness of AI systems. • Documentation and Transparency: Providing context-aware documentation, involving diverse actors in defining reproducibility, and promoting reporting mechanisms can address variability and idiosyncrasies in scientific research. These points highlight the importance of considering contextual factors when evaluating AI models and the need for transparent and explainable AI systems in various scientific disciplines.