4 Reasons Why Social Media Make Us Vulnerable to Manipulation
by Filippo Menczer (Indiana University, USA)
Session Chair: Leandro Marinho
As social media become major channels for the diffusion of news and information, it becomes critical to understand how the complex interplay between cognitive, social, and algorithmic biases triggered by our reliance on online social networks makes us vulnerable to manipulation and disinformation. This talk overviews ongoing network analytics, modeling, and machine learning efforts to study the viral spread of misinformation and to develop tools for countering the online manipulation of opinions.
About the Speaker
Filippo Menczer is a distinguished professor of informatics and computer science at Indiana University, Bloomington, and Director of the Observatory on Social Media. He has courtesy appointments in cognitive science and physics. He holds a Laurea in Physics from the Sapienza University of Rome and a Ph.D. in Computer Science and Cognitive Science from the University of California, San Diego. Dr. Menczer is an ACM Distinguished Scientist, a Fellow of the Center for Computer-Mediated Communication, a Senior Research Fellow of The Kinsey Institute, and a board member of the IU Network Science Institute. He previously served as division chair in the IUB School of Informatics and Computing, director of the Center for Complex Networks and Systems Research, visiting scientist at Yahoo Research, Fellow of the Institute for Scientific Interchange Foundation in Torino, Italy, and Fellow-at-large of the Santa Fe Institute. He has been the recipient of Fulbright, Rotary Foundation, and NATO fellowships, and a Career Award from the National Science Foundation. His research interests span Web and data science, computational social science, science of science, and modeling of complex information networks. In the last ten years, his lab has led efforts to study online misinformation spread and to develop tools to detect and counter social media manipulation. This work has been covered in many US and international news sources, including The New York Times, Wall Street Journal, Washington Post, NPR, PBS, CNN, BBC, Economist, Guardian, Atlantic, Reuters, Science, and Nature. Menczer received multiple service awards and currently serves as associate editor of the Network Science journal and on the editorial boards of EPJ Data Science and PeerJ Computer Science.
Date
14:00 – 15:00, Attend in Whova
Bias on Search and Recommender Systems
by Ricardo Baeza-Yates (Universidad de Chile & Northeastern University, USA)
Session Chair: Rodrygo Santos
We cover all biases, to the best of our knowledge, that affect search and recommender systems. They include biases on the data, on the algorithms involved (and their evaluation), and on the user interaction, particularly the ones related to feedback loops (e.g., ranking and personalization). In each case, we cover the main concepts and when known, the techniques to mitigate them. We give special emphasis to exposure bias, which we believe is the main bias that impacts, both, users and systems. This presentation is partially based on Bias on the Web, Communications of the ACM, June 2018.
About the Speaker
Ricardo Baeza-Yates is Director of Data Science Programs at Northeastern University, Silicon Valley campus, since 2017. He is also a member of Spain’s Council of AI, ACM’s US TPC in Algorithms and AI, and IADB’s fAIr LAC Advisory Board, among others. Before, he was CTO of NTENT (2016-2020) as well as VP of Research at Yahoo Labs (2006-2016), based first in Barcelona, Spain, and later in Sunnyvale, California. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 1999 and 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 between 2012 and 2016 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. In 2018 he obtained the Spanish National Award in Applied Computer Science, among other awards and distinctions. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989, and his areas of expertise are web search and data mining, information retrieval, data science, and algorithms in general.
Date
14:00 – 15:00, Attend in Whova
“You Really Get Me”: Conversational AI Agents That Can Truly Understand and Help Users
by Michelle Zhou (Juji, Inc.)
Session Chair: Li Chen
Have you watched the movie Her? Have you ever wondered or wished to have an AI companion like Samantha, who could tell you what you really are, whom your best teammate may be, and which career path would be best for you? In this talk, Michelle will present a framework for building hyper-personalized, conversational Artificial Intelligent (AI) agents who can deeply understand users and responsibly guide user behavior in both virtual and real world. Through live demos, she will highlight two technical advances of the framework: (1) evidence-based personality inference and (2) model-based conversation generation. Michelle will discuss real-world applications of these agents and the wider implications of enabling hyper-personalized conversational AI agents for businesses and individuals.
About the Speaker
Dr. Michelle Zhou is a Co-Founder and CEO of Juji, Inc., an AI startup located in Silicon Valley, specializing in building AI technologies and packing such technologies into easy-to-use solutions that enable the creation and adoption of responsible and empathetic Artificial Intelligence agents. Prior to starting Juji, Michelle led the User Systems and Experience Research (USER) group at IBM Research – Almaden and then the IBM Watson Group. Michelle’s expertise is in the interdisciplinary area of intelligent user interaction (IUI), including conversational AI systems and personality analytics. She is an inventor of the IBM Watson Personality Insights and has led the research and development of at least a dozen products in her areas of expertise. Michelle has also published over 100 peer-reviewed, refereed scientific articles and 45+ patents. Michelle is currently the Editor-in-Chief of ACM Transactions on Interactive Intelligent Systems (TiiS) and an Associate Editor of ACM Transactions on Intelligent Systems and Technology (TIST). She received a Ph.D. in Computer Science from Columbia University and is an ACM Distinguished Scientist.
Date
14:00 – 15:00, Attend in Whova
