Programme
An interdisciplinary programme on AI, technology and society
The Cruise School combines Artificial Intelligence, data-driven methods and Futures Studies to explore technological innovation and social transformation through lectures, applied activities and interdisciplinary project work.
The programme corresponds to 7 ECTS/CFU, subject to recognition by the participant’s home institution.
Common Core AI, Data & Futures Studies
All participants share a common interdisciplinary foundation covering key concepts and methods such as:
- Artificial Intelligence and machine learning
- Data-driven decision-making
- Causal analysis and modelling
- Futures Studies and scenario development
- AI governance, ethics and societal impact
The Common Core provides the methodological basis for the two thematic tracks and project activities.
Technological Change Track
This track focuses on the application of AI and advanced data-driven approaches to technological and industrial systems.
Main topics include:
- Industrial AI
- Control and optimisation
- Digital and cognitive twins
- Data pipelines and decision-support systems
- Energy and infrastructure systems
- Operational efficiency and sustainability
Social Change Track
This track explores the economic, institutional and societal implications of Artificial Intelligence.
Main topics include:
- AI governance and regulation
- Causal inference and policy evaluation
- Public-sector innovation
- Ethics-by-design
- Data-informed public policy
- Organisational and societal transformation
Preparation Before the Cruise
Before embarkation, participants receive preparatory materials and introductory activities to establish a shared knowledge base and support interdisciplinary collaboration.
Preparation may include readings, methodological resources, preliminary challenges and thematic orientation activities.
Studio Projects
Participants work in interdisciplinary teams on real or realistic challenges connecting AI, technological innovation and societal transformation.
Projects may address areas such as industry, energy, logistics, healthcare, public administration, governance and sustainability.
Each team develops its work through a structured process:
Problem framing → Data & AI approach → Impact analysis → Governance & ethics → Future scenarios → Implementation roadmap
Lectures, laboratories, simulations and selected Business Game activities support the project development.
Final Academic Showcase
The programme concludes with a Final Academic Showcase, where teams present their projects to participants, faculty and invited experts.
Presentations focus on the challenge addressed, the proposed approach, expected impact, risks and limitations, future scenarios and implementation strategy.
For more information on the academic governance of the Cruise School, see the Scientific Committee.
Academic Recognition
The complete academic workload corresponds to 7 ECTS/CFU.
Assessment is based on participation in academic activities and completion of the interdisciplinary project work. Participants who successfully complete the programme receive documentation supporting academic recognition according to the rules of their home institution.