Maciej joined LeADS in November of 2021 to work on the topic of privacy-enhanced Machine Learning and Personal Data Management at the Institute of Information Science and Technologies “Alessandro Faedo” at the National Research Council of Italy. Formally a law graduate, he developed an interest in quantitative risk assessment on financial markets in the early years of his study, then – after graduating from Harvard’s CS50 classes on computer science, he devoted his research time to the issues connected with accessible Artificial Intelligence tools and privacy-aware Machine Learning. Before obtaining his Master’s Degree, he held internships in, among others, Allen & Overy, DZP Legal and DLA Piper, where he could work at various layers of market, trade, and enforcement analyse. Before joining the project, he also did an internship in the Permanent Mission to the United Nations of the Republic of Poland, where he could acquaint himself with quantitative methods of situational risk analysis.
Project Title: Personal information as currency for the supply of digital content
Objectives: The main objective of this research is to examine various methods of Distributed Machine Learning to assess which ones are the most suitable for creating a more consumer-centric framework for personal data management. The recent advancements in the theory of learning techniques that do not require end-clients to transfer their raw data beyond the devices (such as Federated Learning, Large Batch Stochastic Gradient Descent, and Split Neural Networks) allow us to experiment with approaching data management from a different angle, perhaps proposing more user-centric approach, where the consumers are more aware how to opt-out from the usage of their personal data or how to ask for a certain degree of personalisation of services. However, this all requires many breakthroughs not only in the aspect of technology but also shifts in how we think about our personal data management. The research done by Maciej in that regard should be at least a first step towards it.
- M. Zuziak & S. Rinzivillo (2022), “Federated Learning as an Analytical Framework for Personal Data Management”, in the 1st International Workshop on Imagining the AI Landscape After the AI Act, Networks and Things.
- M. Zuziak, S. Rinzivillo, G. Comande’ (2022), “Use of Distributed Personal Data Management for Personalization of Digital Services”, in 18th Conference on Artificial Intelligence Applications and Innovations (AIAI2022). 17-20 June, 2022. Crete, Greece.