DidaWiki

Questa pagina è in sola lettura. Puoi visualizzare il sorgente, ma non puoi modificarlo. Contatta l'amministratore se pensi che ci sia un errore.



====== Responsible Artificial Intelligence A.Y. 2024/25 ======

This is the home page of a Ph.D. level course offered at the National Ph.D. in AI - Society.
The course presents technologies enabling the design and development of Responbile Artificial Intelligent (AI) systems. In particular, it first introduces notions of privacy, anonymity, transparency, fairness, and uncertainty in AI considering the Euroepan legal framework and how they can be modelled for enabling the developement of methods for quantitatively  assessing the AI system vulnerabilities and trustworthiness and for mitigating the identified risks and unethical behaviour.    
The course then presents technologies for implementing the privacy-by-design principle, for auditing AI-based predictive models, and for the protection of users rights with the goal of enabling explanable, pribacy-aware, fairness-aware and  self-assessed uncertainty AI models.


=====Instructors=====

  * **Anna Monreale**
    * Università di Pisa
    * [[https://pages.di.unipi.it/amonreale/]]
    * [[anna.monreale@unipi.it]] 
 
  *   * **Francesca Naretto**
    * Università di Pisa
    * [[francesca.naretto@unipi.it]]   

  * **Salvatore Ruggieri**
    * Università di Pisa
    * [[http://pages.di.unipi.it/ruggieri/]]
    * [[salvatore.ruggieri@unipi.it]]   

=====Hours and rooms=====

The course will be offered in the period end of June 2025 - July 2025 (see table below).
A Teams channel will be used to post news, notes, Q&A, and other stuff related to the course. The lectures will be live-streamed and recorded. 

Please subscribe, by using your UNIPI account, the Course Teams channel for updates: 
[[https://teams.microsoft.com/l/team/19%3AFWUf787lQJDl9Z-OemuyZuI9YS5W9tv9Zu4C38muU881%40thread.tacv2/conversations?groupId=80af85b5-20f6-4efb-b618-767018fe6acc&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Team of the Responsable AI Course]]



=====Exams=====

Ph.D. students may do an exam in the form of a report on an advanced topic/survey to be agreed upon. The topic is typically related/relevant to the objectives of the Ph.D. studies of the student.

Attendance (in presence or online) is required for at least 17 hours (70% of 24 hours) of lectures to obtain a certificate. 

=====Class calendar=====

^ # ^ Date ^ Room ^ Topic ^ Mandatory teaching material ^ 
|01| 03.07.2025 - 09:00-13:00| |Overview on AI Act and GDPR|  |
|02| 07.07.2025 - 09:00-13:00| |Privacy in the era of AI| |
|03| 10.07.2025 - 16:00-20:00| |Explainable AI| |
|04| 11.07.2025 - 16:00-20:00| |Bias and Fairness in AI| |
|05| 14.07.2025 - 09:00-11:00| |Case study on Explainable AI - RULEX| |
|06| 14.07.2025 - 11:00-13:00| |Case study on Bias and Fairness| |
|07| 15.07.2025 - 09:00-11:00| |Towards European standard on AI Trustworthiness Framework| |
|08| 15.07.2025 - 11:00-13:00| |Ethics in AI |