[Air-L] Synthetic Data for State Statistics/Census

[Katherine Harrison]

*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 at 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”.