The text discusses the importance of trustworthiness in AI standards efforts, particularly in the context of reliability, fairness, and explainability. Graph technology is highlighted as a key enabler for adding contextual information to AI systems, enabling them to be more reliable, fair, and trustworthy. This approach allows for data lineage tracking, guarding against input data manipulation, and avoiding excessive reliance on correlated data. Contextual information also reveals potential biases in existing data and enables situational/contextual fairness. The text concludes that graph technologies are essential for promoting AI aligned to key American values of accountability, fairness, and trust, and that they offer a more human-friendly way to evaluate connected data.