Post by Sama

AI governance often focuses on model outputs, but the foundations matter too. The decisions organizations make when sourcing, labeling, or validating training data have real implications for both model performance and the people who help build these systems. Through our work with organizations like Partnership on AI, we’ve contributed to conversations around responsible sourcing practices for data enrichment services, helping advance greater transparency and accountability across the AI supply chain. As AI adoption continues to grow, the quality of training data — and the conditions under which it is produced — remain an important part of building responsible AI. Learn more about our approach: https://lnkd.in/gnheFhzs