Legality Attentive Data Scientists

LeADS research and educational program trains a new interdisciplinary professional figure that we call Legality Attentive Data Scientist or LeADS. An expert in data science and law expected to work within and across the two disciplines, a leader in bridging scientific skills with the ethico-legal constraints of their operating environment. LeADS will develop a data science capable of maintaining its innovative solutions within the borders of law - by design and by default - and of helping expand the legal frontiers in line with innovation needs, for instance, preventing the enactments of legal rules technologically unattainable.

LeADS research will set the theoretical framework and the practical implementation template of a common language for co-processing and joint-controlling key notions for both data scientists and jurists. Its outcomes will produce also a comparative and interdisciplinary lexicon that draws experts from these fields to define important crossover concepts. Through a broad, interdisciplinary, inter-sectoral network of academic and non-academic partners, LeADS will provide a cross-disciplinary training to ESRs who will work as (e.g.) data scientists or researchers in general, sales managers, project or general managers management at private entities (tech companies, consultancies and legal advisories) and public entities (research centres, universities and administration). LeADS answers to the lack of programs blending experiential learning and research in the area, offers an innovative curriculum linked to pioneering research results. It includes 6 interdisciplinary modules, sectoral courses; joint mentoring on individual research projects; TILL modules and Discussion Games to help ESRs develop pioneering soft skills; challenging secondments. Overall, LeADS research and training aims at changing the regulatory and business approach to information while training the experts able to drive the process that every data driven society needs to employ.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 956562