Avviso Seminari nell'ambito del corso *Explainable AI* ========================================================= *Tuesday February 8, from 4:00-6:00 PM in Sala Azzurra (Palazzo Carovana)* Within the course *Explainable AI, Prof. Francesca Toni* (Professor in Computational Logic and Royal Academy of Engineering/JP Morgan Research Chair on Argumentation-based Interactive Explainable AI at the Department of Computing, Imperial College London, UK) will give a seminar on "*Explaining with argumentationIt"*. Abstract: Explaining with argumentationIt is widely acknowledged that transparency of automated decision making is crucial for deployability of intelligent systems, and explaining the reasons why some outputs are computed is a way to achieve this transparency. The form that explanations should take, however, is much less clear. In this talk I will explore two classes of explanations, which I call 'lean' and 'mechanistic': the former focus on the inputs contributing to decisions given in output; the latter reflect instead the internal functioning of the automated decision making fed with the inputs and computing those outputs. I will show how both classes of explanations can be supported by forms of computational argumentation, and will describe forms of argumentative XAI in several settings, including multi-attribute decision making and machine learning. Link for on-line participation: https://teams.microsoft.com/l/meetup-join/19%3aV0oVUvttECrk8ErVdnBlqju0VxsLp... ========================================================= *Thuresday February 10, from 4:00-6:00 PM in Aula Bianchi Scienze (Palazzo Carovana)* Within the course *Explainable AI, Prof. **Andrea Omicini*: (Department of Computer Science Univ. Bologna) will give a seminar on “Explaining by design - On the integration of symbolic and sub-symbolic” Link for on-line participation: https://teams.microsoft.com/l/meetup-join/19%3aV0oVUvttECrk8ErVdnBlqju0VxsLp... I seminari si terranno sia in modalità blended. Gli utenti esterni che vorranno partecipare in presenza sono invitati a inviare all'indirizzo classi@sns.it un messaggio entro le ore 14:00 di Martedì 8 febbraio 2022. Classe di scienze ============================= Fosca Giannotti Scuola Normale Superiore - Pisa - Italy KDD Lab. - ISTI - CNR Pisa - Italy, P.I. ERC AG XAI: Science and technology for the eXplanation of AI decision making https://xai-project.eu/ tel.: +39 050 6212999 mob: +39 3483972190 e_mail: fosca.giannotti@sns.it fosca.giannotti@isti.cnr.it https://kdd.isti.cnr.it/people/giannotti-fosca =============================

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