Artificial intelligence (AI)

AI for research, education and administration

Artificial intelligence, commonly known as AI, includes a range of technologies that can make predictions, provide recommendations, or make decisions with varying levels of autonomy, affecting both real and virtual environments. Recently, there have been significant advancements in a new area known as "generative AI". This technology can create content such as text, images, animations, sounds, or source code based on user instructions (prompts).

  • Advancements in this field are creating more opportunities to support and partially automate research-related processes. This includes enhancing productivity in tasks that are time-consuming, repetitive, or require minimal intellectual input, as well as improving the quality of scientific work in areas such as bibliographic searches, word processing, and data analysis.
  • Recent advancements in generative AI have created new opportunities in learning and teaching. For example, AI can assist teachers in designing innovative, interdisciplinary educational activities that incorporate creative methods and the latest digital tools. Additionally, AI can support students' learning processes in a highly personalised manner, adapting to various cognitive abilities, linguistic backgrounds, and accessibility requirements. This fosters inclusion and provides tailored resources to meet individual needs.
  • The implementation of artificial intelligence systems can offer many advantages for the University's administrative processes. It can enhance operational efficiency, particularly in specific areas, provide more responsive and tailored services and make the most of emerging technologies.

AI tools also raise questions about what responsible use actually means. While these tools can generate syntactically correct documents, they may still contain false or misleading information, untrue bibliographic references, fabricated data, or errors in data analysis and output. Identifying these issues can be extremely difficult, if not impossible.

University guidelines on AI

The following guidelines are designed to establish a strategic vision for the use of AI. They aim to clarify what the University considers appropriate when faculty, researchers, technical-administrative staff, and students use these tools in research, teaching, learning, and administration. The guidelines will highlight limitations and potential risks, providing examples and case studies to illustrate these points.

The guidelines aim to promote and support the responsible use of AI, particularly generative AI. They are designed to help monitor the use of these tools within an organisation, spread ethical principles, and establish safeguards to ensure security, privacy, and compliance with copyright regulations. Additionally, the guidelines encourage collaborative projects within the university community to foster the development and sharing of best practices.

The Rector's Delegates for Digital innovation in teaching and research, supported by the staff of the Computer Services and Telecommunications Area (ASIT), have prepared the following guidelines:

file pdfGuidelines for the Responsible Use of Artificial Intelligence in Research
by the "Working Group for ICT Research Support Activities”, coordinated by Prof. Marco S. Nobile and advised by Chiara Gallese, Marie Curie Fellow at the University of Turin and member of the EU’s AI Office Working Group on “General-Purpose AI Code of Practice”
439 K
file pdfGuidelines for the Responsible Use of Generative AI in Teaching and Learning
by the Working Table on the use of AI for Teaching, coordinated by Prof. Sabina Rossi and Dr. Teresa Scantamburlo, Ca' Foscari's representative in the Working Group on the “General-Purpose AI Code of Practice” of the AI Office of the European Community
308 K

The Computer Services and Telecommunications Area (ASIT) also offers the following reference guidelines for administrative staff:

The guidelines also provide a framework for the recently launched Microsoft 365 Copilot testing project. This project involves faculty, researchers, managers, and the university's technical and administrative staff members to evaluate its applicability, benefits, and challenges across various areas.

Last update: 12/02/2025