MACHINE LEARNING for DATA & ALGORITHM-SHARING in SOCIAL SCIENCE

Are recent advances in Machine Learning making the sharing of algorithms preferable to the sharing of data? We are delighted to announce the Workshop on Machine Learning for Data & Algorithm-sharing in Social Science. The workshop, organized by the IMT School for Advanced Studies Lucca, provides a unique opportunity for researchers and practitioners to delve into the transformative power and challenges of algorithm-sharing methods, including, but not limited to, cutting-edge federated learning. These state-of-the-art methodologies are poised to revolutionize empirical research in economics, particularly in contexts where conventional data-sharing is impeded by privacy, security, and commercial constraints.

The workshop seeks to bring together international scholars and practitioners interested in exploring the applications of algorithm-sharing in social science, including economics and cognate disciplines. By offering a showcase for use cases of algorithm-sharing applications, the workshop aims to answer the following questions:

• Which are the ideal applications of data and algorithm-sharing, and when is algorithm-sharing preferable to data-sharing?
• How and when can data and algorithm sharing facilitate the collaboration between stakeholders, such as researchers, policymakers, and entrepreneurs, and accommodate data privacy, security and commercial concerns?
• Which is the state-of-the-art of adopted algorithm-sharing solutions in public and private domains? 

An invited talk will be given by Jermain Kaminski (Maastricht University), Gabriele Tolomei (Sapienza University), Bruno Carballa Smichowski (Researcher, Joint Research Centre - European Commission) and Nathalie Baracaldo, Senior Research Scientist, IBM Research.

Participants will have the opportunity to familiarize themselves with algorithm-sharing methods and software through a special “proof of concept” session using Federated Learning methods on real data.

The workshop is organized and hosted by the IMT School for Advanced Studies Lucca and is open to up to 12 participants.

DEADLINE: If you are interested in presenting, submit a paper or an extended abstract (a minimum of 5 pages) to das_workshop[at]imtlucca[dot]it before March 31st, attaching a copy of your CV. A decision on accepted papers will be made by April 14th. Full papers that do not yet use data or algorithm-sharing techniques but would benefit from such applications will also be considered; in this case, please state in your email how your work would benefit from these methods.

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