While the concept of responsible AI is becoming more and more popular, practitioners and researchers may often struggle to characterize responsible practices in their own work. This paper presents a four-day, PhD-level course on Responsible Artificial Intelligence conducted at the University of Udine by Dr. Damiano Spina. Using a hands-on approach, the course aimed to illustrate the application of responsible AI concepts in research. Using case studies based on existing IR research, the course explored responsible AI concepts such as positionality, participatory research, fairness, diversity, and ethics. The course engaged 23 participants, both online and in person, including PhD students at various stages, postdoctoral researchers, professors, and academic staff. It featured four sessions and five interactive group activities. Of the 23 attendees, 20 (87%) actively participated in the activities, and 14 (61%) completed the final survey. We believe the hands-on activities discussed in this paper can assist practitioners and educators in the design of responsible AI content for information retrieval curriculum.

Report on the Hands-On PhD Course on Responsible AI from the Lens of an Information Access Researcher

Kevin Roitero
;
Stefano Mizzaro
;
Vincenzo Della Mea
;
Francesca Da Ros
;
Michael Soprano
;
Hafsa Akebli;Alex Falcon;Mehdi Fasihi;Alessio Fiorin;David La Barbera;Daniele Lizzio Bosco;Riccardo Lunardi;Alberto Marturano;Zaka-Ud-Din Muhammad;Francesco Nascimben;Moritz Nottebaum;Massimiliano Pascoli;Mihai Horia Popescu;Laura Rasotto;Mubashara Rehman;Francesco Taverna;Biagio Tomasetig;Alessandro Tremamunno
2024-01-01

Abstract

While the concept of responsible AI is becoming more and more popular, practitioners and researchers may often struggle to characterize responsible practices in their own work. This paper presents a four-day, PhD-level course on Responsible Artificial Intelligence conducted at the University of Udine by Dr. Damiano Spina. Using a hands-on approach, the course aimed to illustrate the application of responsible AI concepts in research. Using case studies based on existing IR research, the course explored responsible AI concepts such as positionality, participatory research, fairness, diversity, and ethics. The course engaged 23 participants, both online and in person, including PhD students at various stages, postdoctoral researchers, professors, and academic staff. It featured four sessions and five interactive group activities. Of the 23 attendees, 20 (87%) actively participated in the activities, and 14 (61%) completed the final survey. We believe the hands-on activities discussed in this paper can assist practitioners and educators in the design of responsible AI content for information retrieval curriculum.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1298685
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