ONLINE  |  APPLICATION

Deadline for Registration - EXTENDED

March 1^st, 2021

Learning objectives

The digital economy harnesses the power of big data, modern high computing capacity, Artificial Intelligence, and innovation. It also leverages their interconnection allowing information technology to mediate all human activities. These innovations should be properly framed within the existing legal and ethical framework, in order to strike the right balance between the protection of fundamental rights and freedoms and the need to preserve the regulatory flexibility necessary for all market players to enjoy and be empowered by the wealth of big data in an open society. Data protection plays a significant role for these purposes. Although the legal and ethical framework of the data society is increasingly central to the international debate and for future jobs, there are few opportunities for would-be jurists, technologists and social scientists to acquire the necessary skills to govern the interaction between technological innovation in data science and the regulatory and fundamental rights protection framework. The Responsible Data Society School intervenes on this gap, with the aims of enabling students: i) to develop a responsible approach to Machine Learning techniques, data mining, algorithms, AI in technical, as well as social analytics activities; ii) to be aware of the interaction between technologies and regulatory standards; iii) to develop, by design, a robust methodology to comply with the applicable legal framework.

Teaching methodologies

Students will find an interactive and cross-disciplinary learning environment to enhance theoretical and empirical skills to strengthen problem solving, as well as strong decision-making attitudes within various scenarios. Several experts coming from e.g. research & innovation, industries, policy-making, and public authorities will participate in the programme addressing the identified challenges from a multidimensional perspective. This will help to improve transversal skills, for example, strategic communication, teamwork and leadership.

Who should attend this Seasonal School?

Undergraduate, postgraduate and PhD students from different backgrounds (e.g. law, economics and political sciences, life sciences, computer science, physics, and engineering) who are interested in understanding the legal and ethical thorns and twists of big data and AI.

Coordinator

Prof. Giovanni Comandé

Key teaching staff

• Dr. Denise Amram
• Prof. Maria Gagliardi
• Prof. Caterina Sganga

Period

March 15^th - 20^th, 2021

RESERVED AREA