Summary
High-quality data are increasingly central to modern machine learning and artificial intelligence, enabling advances in scientific discovery, automated decision-making, and emerging AI technologies. Yet there often lack transparent and reliable mechanisms to appropriately credit and compensate those who contribute data used to train AI systems. This project will develop statistical and machine-learning methods for measuring the value of data in AI model training and data-driven decision systems. The work addresses fundamental challenges in data valuation, including robustness to strategic mani
