Opening of SFI MediaFutures

Opening remarks

• Henrik Asheim, Norwegian Minister for Research and Higher Education
• University of Bergen by Rector Margareth Hagen
• Department of information science and media studies by Head of Department Leif Ove Larsen
• Research Council of Norway

• University of Oslo
• NORCE
• University of Stavanger 

Moderator: Christoph Trattner, Centre Director, MediaFutures, UiB 

In the panel:

• Ingrid Agasøster, Chief Operating Officer, Fonn Group
• Eirik Solheim, NRK Norwegian Broadcasting Cooperation
• Christian Birkeland, Digital director/director TV2 Sumo, TV2 

Sinan Aral is a Global Authority on Business Analytics; Award-winning Researcher; Entrepreneur and Venture Capitalist; Director of MIT’s Initiative on the Digital Economy and Social Analytics Lab and a founding partner at Manifest Capital. He is a managerial economist and econometrician by training whose expertise spans social networks, causal inference, the design and analysis of large-scale digital experiments, machine learning, predictive modeling, natural language processing, AI, big data, marketing, IT, social commerce, ecommerce, behavior change and economic productivity. He earned his PhD at MIT and completed his Master’s degrees at the London School of Economics and at Harvard. 

• Amedia
• Bergens Tidende
• Fonn
• Highsoft
• IBM
• NRK
• Schibsted
• TV2
• Vimond
• Vizrt

Ricardo Baeza-Yates is currently a Research Professor at the Institute for Experiential AI of Northeastern University (half-time)". Between 2016 and 2020 he was CTO of NTENT, a search technology company based in California. Previously, he was VP of Research at Yahoo Labs. He is part-time professor at  the University of Chile and Universitat Pompeu Fabra in Barcelona, Spain, and an adjunct professor at the CS department of the University of Waterloo, Canada

His research interests includes algorithms and data structures, information retrieval, web search and data mining, and data science and visualization.

He is ACM Fellow and IEEE Fellow.

In his presentation, titled Bias on Search and Recommender Systems, he covers all biases that affect search and recommender systems. They include biases on the data, the algorithms as well as the user interaction, in particular the ones related to relevance feedback loops (e.g., ranking and personalization).  In each case he covers the main concepts and when known, the techniques to ameliorate them, as well as biases that might be product of the evaluation methods used. This presentation is partially based on Bias on the Web, Communications of ACM, June 2018.