DataLEASH in Action

Objective
The collaborative project DataLEASH in Action aims to develop novel methods that enable the sharing and learning from data. Legal privacy concerns often prevent implementations of technical solutions so that case studies (sandbox pilots) involving legal and technical competences as proposed in this impact project are seen as the most promising strategy forward. These case studies are pivotal in understanding the nuances of legal requirements and developing technically feasible solutions. The objective is to strike a balance where legal requests are not overly demanding yet necessitate state-of-the-art technical solutions.

Background
Digitalization has resulted in more and more data being generated and collected from various sources (such as health care, customer service, surveillance cameras, etc.). The data is valuable for processing and additional analysis to improve predictions and planning. Advances in machine learning have improved this kind of data analysis, while data-protection regulation such as the GDPR has introduced constraints, limiting what data can be used and for what purpose. There is, thus a tension between the utility of data and the privacy of the individuals the data is about.

Cross-disciplinary collaboration
DataLEASH in Action brings together researchers from the School of Electrical Engineering and Computer Science (EECS, KTH), the Department of Computer and Systems Sciences (DSV) and the Department of Law both at Stockholm University