Abstract

The landscape of recommender systems has experienced a transformative shift in recent years, fueled by the urgent need to address the ethical challenges surrounding algorithmic biases and the quest for fairness. In this talk, we delve into the central role of user perspectives, recognizing their significance as key drivers for constructing fair recommendation algorithms. Through real-world case studies, we first unveil the profound impact of biased recommendations on individuals, communities, and society at large. We expose the potential consequences of these biases, shedding light on the necessity for change. With this critical backdrop in mind, we showcase and discuss recent debiasing techniques that, by embracing user perspectives, can lead to more inclusive and representative recommender systems, thereby fostering trust and engagement among users.

About the speaker

Mirko Marras is an Assistant Professor at the Department of Mathematics and Computer Science of the University of Cagliari (Italy), where he co-leads the research unit on responsible machine learning. Prior to that, he has been a postdoctoral researcher at EPFL (Switzerland) and visiting scholar at Eurecat (Spain) and New York University (USA). His research ranges across a wide range of domains impacted by user modelling and personalization, including business, education, entertainment, and healthcare. He has co-authored more than 60 papers in top-tier conferences and journals and has given tutorials on bias and fairness in recommendation at ICDE 2021, ECIR 2021, WSDM 2021, ICDM 2020, and UMAP 2020. He has also co-chaired several workshops on this theme, including the Bias series at ECIR (2020-2023), the L2D workshop at WSDM 2021, the R&PRMI workshop at ICCV 2021, the FATED workshop at EDM 2022, and the RKDE workshop at ECML-PKDD 2023. He serves as an associate editor for Springer's Journal of Ambient Intelligence and Humanized Computing.