ML01: Inference Using Synthetic Data

Music City Center 

As privacy concerns grow and synthetic data becomes an increasingly popular solution, ensuring proper inference remains a critical challenge. This round table session will explore best practices for making valid inferences from synthetic datasets, with a focus on mitigating bias and accurately estimating variance (the uncertainty of results derived from synthetic data). We aim to bring together participants from diverse research areas to share insights, identify gaps in current practices, and discuss the challenges of using and disseminating synthetic data across different fields. The goal is to foster a holistic understanding of these issues and identify key areas for further development in methods and tools as this field evolves.

Privacy

Confidentiality

Variance estimation

Disclosure risk 

Government Statistics Section