Detailed Program
The school is organized in two parts: in the morning students will attend lectures with different speakers, while in the afternoon they will work on group projects guided by dedicated tutors.
TIME | Sunday 20 | Monday 21 | Tuesday 22 | Wednesday 23 | Thursday 24 | Friday 25 |
|---|---|---|---|---|---|---|
09:00 09:30 | Internal meeting for the organization | Registration | ||||
09:30 10:00 | Round of presentations (Students) | From Interpretability Methods to Interpretable Models | Meaningful Human Control over Autonomous Systems | Policies and Data | ||
10:00 10:30 | SoBigData RI & School Introduction | |||||
10:30 11:00 | Tutorial SoBigData Lab | Student Projects Presentations | ||||
11:00 11:30 | Coffee Break | Coffee Break | Coffee Break | Coffee Break | Coffee Break | |
11:30 12:00 | Project Challenges Presentation | Human–AI Coevolution | The AI Act and transparency rules for generative AI | Data Representation | Projects Presentations | |
12:00 12:15 | Social Science Data Archives | |||||
12:15 12:30 | Enabling the Human in the Loop | Explainability | ||||
12:30 12:45 | Group Decision Challenge | |||||
12:45 13:00 | Monitoring Electoral Democracy | |||||
13:00 13:30 | Human–AI Interaction | Personal and Non-personal Data Governance | ||||
13:30 15:00 | Lunch Break | Lunch Break | Lunch Break | Lunch Break | Lunch Break | |
15:00 16:00 | Developing Student Projects with Tutors | Developing Student Projects with Tutors | Developing Student Projects with Tutors | Developing Student Projects with Tutors | Internal Meeting | |
16:00 16:30 | Coffee Break | Coffee Break | Free Afternoon | Coffee Break | ||
16:30 18:00 | Developing Student Projects with Tutors | Developing Student Projects with Tutors | Developing Student Projects with Tutors | |||
18:00 18:30 | Social Event | |||||
18:30 20:30 | Welcome Cocktail | |||||
20:30 | Dinner | Dinner | Social Event |
Daily Program
The opening day starts with a round of presentations of the participants, followed by an introduction to the SoBigData Research Infrastructure and to the school, and a tutorial on the SoBigData Lab. The project challenges are then presented and, in the Group Decision Challenge session, participants form the multidisciplinary groups that will work on them throughout the week. In the afternoon, groups start developing their projects with the guidance of dedicated tutors.
The second day focuses on how people and AI systems interact and influence each other. Lectures cover the path from interpretability methods to interpretable models, the concept of human–AI coevolution, how to enable the human in the loop, and human–AI interaction. The afternoon is dedicated to project work with tutors.
This day addresses how humans can keep meaningful control over autonomous systems. Lectures cover meaningful human control, the relationship between humans and AI, explainability, and the governance of personal and non-personal data. After a project session with tutors, the rest of the afternoon is free.
The fourth day connects data and AI with policy and society. Lectures cover the relationship between policies and data, data representation, the role of social science data archives, and the monitoring of electoral democracy. The afternoon is dedicated to finalising the projects with tutors.
The final day is dedicated to the presentation of the projects developed by the groups during the week. Results will be presented to a panel of experts, who will evaluate them on relevance to the challenge, methodological rigour, innovation, feasibility, quality of the presentation and the group’s ability to integrate interdisciplinary skills and ethical considerations.