*10 June 2024, 13.15-16.00: *Join us for this TEMA DATA LAB session on *Synthetic Data for State Statistics/Census*, in collaboration with the Operationalising Ethics for AI project and the Social Complexity and Fairness in Synthetic Medical Data project. *The seminar will be held at Campus Norrköping, of Linköping University and online*. Census data represent a social contract between citizen and state, with the collection, use and management of these kind of data reflecting spatial and temporal specificities of individual nation states’ policies and practices. Synthetic data, through older techniques of statistical disclosure control, have long been used to guarantee confidentiality as a key part of this contract. New techniques such as differential privacy are changing how state statistics data are prepared and released, challenging common expectations of what such data represent and of their connection to reality. In this workshop, we ask: - What kinds of knowledge do state statistics/census data promise? How are/were these affected through the use of statistical disclosure control techniques? - What are the impacts of new techniques to produce synthetic census data? - Can the trajectory of synthetic data within the census domain give us some insights into what we may see evolving in other contexts of application? Practical details: June 10, 13:15-16:00 at Campus Norrköping, Linköping University or online (zoom link forthcoming to registered participants) Registration: Please send an email indicating your interest to Satenik Sargsyan ( satenik.sargsyan@liu.se ) by 3 June. *About Synthetic Data Seminar series:* This seminar series explores the risks, possibilities, and promises of synthetic data across different application areas. Given the increasingly complicated regulatory environment around data use and the development of AI systems, what kinds of risks are addressed, created or made possible through synthetic data? Where there is much excitement about synthetic data in the machine learning community, there is also apprehension and caution. There is a proliferation of synthetic data generation libraries and pipelines becoming available to the technical community. These promise to get beyond the triple challenges of privacy, bias, and data scarcity, but warrant a critical discussion about how and to what extent these challenges are being addressed. This seminar series explores what the state of the art in synthetic data currently is, and what critical, legal, and ethical issues synthetic data techniques may encounter. This Synthetic Data Seminar series is organized by the Operationalising Ethics for AI project ( https://liu.se/en/research/operationlising-ethics-for-ai). This event is organised in collaboration with the WASP-HS project “Social Complexity and Fairness in Synthetic Medical Data”.