Descrizione Progetto

Premio Human Centered AI

2021

La Dott.ssa Conati è Prof.ssa di Informatica alla University of British Columbia (Vancouver, Canada). Ha conseguito una Laurea Magistrale in Informatica presso l’Università degli Studi di Milano, nonché un M.Sc. e Ph.D. in Intelligent Systems presso l’Università di Pittsburgh. La ricerca di Conati si focalizza sulla Human-Centered AI, all’intersezione tra Artificial Intelligence (AI), Human Computer Interaction (HCI) e Cognitive Science, con l’obiettivo di costruire sistemi interattivi intelligenti in grado di catturare proprietà rilevanti dell’utente (ad es. stati  mentaile, abilità, bisogni) e di personalizzare l’interazione di conseguenza. Conati ha oltre 130 pubblicazioni peer-reviewed in questo campo e la sua ricerca annovera 8 Best Paper Award conferiti da una varietà di sedi, tra cui UMUAI, il Journal of User Modeling and User Adapted Interaction (2002), ACM International Conference on Intelligent User Interfaces (IUI 2007), International Conference of User Modeling, Adaptation and Personalization (UMAP 2013, 2014), TiiS, ACM Transactions on Intelligent Interactive Systems (2014) e International Conference on Intelligent Virtual Agents (IVA 2016). Conati è editore associato per UMUAI, ACM TiiS, IEEE Transactions on Affective Computing e il Journal of Artificial Intelligence in Education. È stata presidente della AAAC, (Association for the Advancement of Affective Computing), nonché Program o Conference Chair per diverse conferenze internazionali, tra cui UMAP, ACM IUI e AI in Education. È membro del Comitato Esecutivo di AAAI (Association for the Advancement of Artificial Intelligence) e Distinguished Member di ACM (Association for Computing Machinery).

Contributi

La ricerca della Dr.ssa Conati ha portato un contributo significativo nell’ambito di User Modelling, AI-driven Personalization, Affective Computing, Intelligent Virtual Agents, Intelligent Tutoring Systems ed Explainable AI. Il suo obiettivo principale è contribuire a un’intelligenza artificiale incentrata sull’essere umano, che si impegni a creare artefatti in grado sia di svolgere compiti utili che di essere ben accetti dai propri utenti. Un aspetto chiave di questo sforzo è consentire ai sistemi d’intelligenza artificiale di prevedere e monitorare proprietà rilevanti dei propri utenti (ad es. stati, abilità, bisogni) e di personalizzare l’interazione di conseguenza, in modo da massimizzare sia le prestazioni del loro compito che la soddisfazione dell’utente. A tal fine, Conati è particolarmente interessata a indagare su come consentire alla tecnologia basata su AI di trovare il giusto equilibrio tra il fornire delle previsioni e un processo decisionale accurati e il garantire trasparenza e controllo da parte dell’utente, promuovendone la fiducia nel sistema.

Dr. Conati is a Professor of Computer Science at the University of British Columbia, Vancouver, Canada. She received a M.Sc. in Computer Science at the University of Milan, as well as a M.Sc. and Ph.D. in Intelligent Systems at the University of Pittsburgh. Conati’s research is in Human-Centered AI, at the intersection of Artificial Intelligence (AI), Human Computer Interaction (HCI) and Cognitive Science, with the goal to create intelligent interactive systems that can capture  relevant user’s properties (states, skills, needs) and personalize the interaction accordingly.  Conati has over 130 peer-reviewed publications in this field and her research has received 8 Best Paper Awards from a variety of venues, including UMUAI, the Journal of User Modeling and User Adapted Interaction (2002), the ACM International Conference on Intelligent User Interfaces (IUI 2007), the International Conference of User Modeling, Adaptation and Personalization (UMAP 2013, 2014), TiiS, ACM Transactions on Intelligent Interactive Systems (2014), and the International Conference on Intelligent Virtual Agents (IVA 2016). Dr. Conati is an associate editor for UMUAI, ACM TiiS, IEEE Transactions on Affective Computing, and the Journal of Artificial Intelligence in Education. She served as President of AAAC, (Association for the Advancement of Affective Computing), as well as Program or Conference Chair for several international conferences including UMAP, ACM IUI, and AI in Education. She is a member  of  the Executive Committee  of AAAI (Association for the Advancement of Artificial Intelligence) and a Distinguished Member of ACM (Association for Computing Machinery)

Contributions to AI

Dr. Conati’s research has had significant contributions to User Modeling, AI-driven Personalization, Affective Computing, Intelligent Virtual Agents, Intelligent Tutoring Systems, and Explainable AI. Her main objective is to contribute to a human-centered AI striving to create artifacts that are capable of both performing useful tasks and being well accepted by their users. A key aspect of this endeavor is enabling AI systems to predict and monitor relevant properties of their users (e.g., states, skills, needs) and personalize the interaction accordingly, in a manner that maximizes both task performance as well user satisfaction. Towards this goal, Conati is especially interested in investigating how to enable AI technology to strike the right balance between providing accurate predictions and decision making while maintaining transparency, user control and trust.