The ACM Conference on Recommender Systems (RecSys) is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. 

In the frame of the conference, Emilia Gómez is one of the Keynote speakers of the Workshop on Online Recommender Systems and User Modeling (ORSUM): https://orsum.inesctec.pt/orsum2022/keynote.php

Abstract: Artificial intelligence (AI) systems, when applied in practical applications, have an impact on human behaviour. On the one hand, AI provides cognitive assistance to humans, such as helping us to interpret data more efficiently and discover hidden knowledge in large data resources. On the other hand, these AI systems also affect human decision making and cognitive and socio-emotional development. In this seminar I will provide an overview of the research carried out at HUMAINT (Human Behaviour and Machine Intelligence), an interdisciplinary research project carried out at the European Commission's Joint Research Centre. The goal of the project is to study the impact of AI on human behaviour, and aims to provide evidence-based scientific support to the European policymaking process in this field. I will present our policy context, project approach and outcomes, focusing on four core applications (facial processing, automated driving, child-AI interaction and music recommendation) and connected to practical methodologies for fairness, diversity, transparency and human oversight.

In addition, the paper "Diversity by Design in Music Recommender Systems" (Lorenzo Porcaro, Carlos Castillo, Emilia Gómez ) has been awarded TOP 2 Paper in the "senior" category of the Women in RecSys Journal Paper of the Year Awards.

Information about the conference: 

https://recsys.acm.org/recsys22/