Available Soon
Oscar Pastor, Universidad Politécnica de Valencia, Spain
Escaping the Echo Chamber: The Quest for the Normative News Recommender System and a New Notion of Computer Science
Abraham Bernstein, Universität Zürich, Switzerland
Available Soon
Mark Wilkinson, Universidad Politécnica de Madrid, Spain
Keynote Lecture
Oscar Pastor
Universidad Politécnica de Valencia
Spain
http://www.pros.upv.es
![]()
Brief Bio
Oscar Pastor is Full Professor and Director of the "Centro de Investigación en Métodos de Producción de Software (PROS)" at the Universidad Politécnica de Valencia (Spain). He received his Ph.D. in 1992. He was a researcher at HP Labs, Bristol, UK. He has published more than two hundred research papers in conference proceedings, journals and books, received numerous research grants from public institutions and private industry, and been keynote speaker at several conferences and workshops. Chair of the ER Steering Committee, and member of the SC of conferences as CAiSE, ICWE, CIbSE or RCIS, his research activities focus on conceptual modeling, web engineering, requirements engineering, information systems, and model-based software production. He created the object-oriented, formal specification language OASIS and the corresponding software production method OO-METHOD. He led the research and development underlying CARE Technologies that was formed in 1996. CARE Technologies has created an advanced MDA-based Conceptual Model Compiler called OlivaNova, a tool that produces a final software product starting from a conceptual schema that represents system requirements. He is currently leading a multidisciplinary project linking Information Systems and Bioinformatics notions, oriented to designing and implementing tools for Conceptual Modeling-based interpretation of the Human Genome information.
Escaping the Echo Chamber: The Quest for the Normative News Recommender System and a New Notion of Computer Science
Abraham Bernstein
Universität Zürich
Switzerland
![]()
Brief Bio
Abraham Bernstein, Ph.D., is a Full Professor of Informatics at the University of Zurich (UZH), Switzerland. He received a Diploma in Computer Science from ETH Zurich and a Ph.D. in Management with a concentration in Information Technologies from the Sloan School of Management at MIT.
Mr. Bernstein is also a founding Director of the University of Zurich’s Digital Society Initiative (DSI) — a university-wide initiative with more than 280 faculty members and 1200 researchers from all disciplines investigating all aspects of the interplay between society and the digitalization and the President of the Steering Committee of the Swiss National Science Foundation’s Research Priority Program 77 on the Digital Transformation. He was also a member of the Council of Europe’s Committee of Experts on human rights dimensions of automated data processing and different forms of artificial intelligence (MSI-AUT).
Professor Bernstein’s research research focuses on various aspects of the AI/data mining/machine learning, semantic web, recommender systems, crowd computing, and collective intelligence. His work is based on both social science (organizational psychology/sociology/economics) and technical (computer science, artificial intelligence) foundations. His research in this area has been published in leading Computer Science, Management Science, and AI professional outlets. It has also been covered by the Swiss Press. Professor Bernstein has served on the editorial boards of a variety of top journals including as an Editor at the Journal of Web Semantics, Associate Editor at the ACM Transaction on Internet Technologies or ACM Transactions on Interactive Intelligent Systems.
Abstract
Recommender systems and social networks are often faulted to be the cause for creating Echo Chambers – environments where people mostly encounter news that match their previous choices or those that are popular among similar users, resulting in their isolation inside familiar but insulated information silos. Echo chambers, in turn, have been attributed to be one cause for the polarization of society, which leads to the increased difficulty to promote tolerance, build consensus, and forge compromises. To escape these echo chambers, we propose to change the focus of recommender systems from optimizing prediction accuracy only to considering measures for social cohesion.
This proposition raises questions in three spheres: In the technical sphere, we need to investigate how to build “socially considerate” recommender systems. To that end, we develop a novel recommendation framework with the goal of improving information diversity using a modified random walk exploration of the user-item graph. In the social sphere, we need to investigate if the adapted recommender systems have the desired effect. To that end, we present an empirical pilot study that exposed users to various sets (some diverse) of news with surprising results. Finally, in the normative sphere, these studies raise the question what kind of diversity is desirable for the functioning of democracy.
Reflecting the consequences of these findings for our discipline, this talk highlights that computer science needs to increasingly engage with both the social and normative challenges of our work, possibly producing a new understanding of our discipline. It proposes similar consequences for other disciplines in that they increasingly need to embrace all three spheres.
Keynote Lecture
Mark Wilkinson
Universidad Politécnica de Madrid
Spain
Brief Bio
Available Soon