The Web is the most powerful communication medium and the largest public data repository that humankind has created. Its content ranges from great reference sources such as Wikipedia to ugly fake news. Indeed, social (digital) media is just an amplifying mirror of ourselves. Hence, the main challenge of search engines and other websites that rely on web data is to assess the quality of such data. However, as all people has their own biases, web content as well as our web interactions are tainted with many biases. Data bias includes redundancy and spam, while interaction bias includes activity and presentation bias. In addition, sometimes algorithms add bias, particularly in the context of search and recommendation systems. As bias generates bias, we stress the importance of debiasing data as well as using the context and other techniques such as explore & exploit, to break the filter bubble. The main goal of this talk is to make people aware of the different biases that affect all of us on the Web. Awareness is the first step to be able to fight and reduce the vicious cycle of bias.
About the speaker
Dr. Ricardo Baeza-Yates is CTO at NTENT (http://www.ntent.com/), and prior to that Ricardo spent 10 years at Yahoo! ultimately rising to Vice President and Chief Research Scientist. He has also served as a professor at Universidad de Chile since 1985, where he founded and acted as the Director of the Center for Web Research and twice served as Computer Science Department Chair; as well as professor at Universitat Pompeu Fabra in Barcelona since 2005 where he founded and acted as director of the Web Research Group. Ricardo is an ACM and IEEE Fellow with over 500 publications, tens of thousands of citations, multiple awards and several patents. He has co-authored several books including “Modern Information Retrieval”, the most widely used textbook on search.
He earned Bachelor’s and Master’s Degrees in Computer Science and Electrical Engineering from the University of Chile and a Ph.D. in Computer Science from the University of Waterloo.