Speaker: Ricardo Baeza-Yates, Universitat Pompeu Fabra, Spain & Universidad de Chile

Title: Data and Algorithmic Bias in the Web

Date: 04/22/2016

Time: 9am

Room: Info East 122

Abstract: The Web is the largest public big data repository that humankind has created. In this overwhelming data ocean we need to be aware of the quality and in particular, of biases that exist in this data, such as redundancy, spam, etc. These biases affect the algorithms that we design to improve the user experience. This problem is further exacerbated by biases that are added by these algorithms, especially in the context of search and recommendation systems. They include ranking bias, presentation bias, position bias, etc. We give several examples and their relation to sparsity, novelty, and privacy, stressing the importance of the user context to avoid these biases.

Bio: Ricardo Baeza-Yates areas of expertise are information retrieval, web search and data mining, data science and algorithms. He was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He is part time Professor at DTIC of the Universitat Pompeu Fabra, in Barcelona, Spain. Until 2004 he was Professor and founding director of the Center for Web Research at the Dept. of Computing Science of the University of Chile. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 2011 (2nd ed), that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. Since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions.