Before revision:  secondly, to disseminate the latest research and educational materials for uncertainty quantification in machine learning, and encourage further exploration of its utility and connections to other pillars of trustworthy AI such as fairness and explainability .
After revision:  secondly, to disseminate the latest research and educational materials for uncertainty quantification in machine learning, and encourage further exploration of its utility and connections to other pillars of trustworthy AI such as fairness and transparency through the dissemination of latest research and education materials .