My Chatbot is Hallucinating about your Digital Trace.  A discussion about the future of computational social sciences in the era of AI. 

Moderator:  Dr. Ellie Graeden, Georgetown University

Panelists:

Emily Hadley, RTI.   

Emily Hadley is a Research Data Scientist with the RTI International Center for Data Science. Her technical contributions include machine learning, natural language processing, and predictive modeling efforts for education, criminal justice, and public health research projects. Her recent publications have focused on Long COVID, health equity and disparities, and responsible AI. Emily is a proponent of ethical development of AI and actively leading research related to addressing bias and equity in data science.

Dr. Jan Höhne, Leibniz University Hannover.

Jan is a junior professor at the Leibniz University Hannover in association with the German Centre for Higher Education and Science Research and research fellow at the Research and Expertise Centre for Survey Methodology at the University of Pompeu Fabra in Barcelona.  His research combines survey research and computational social science. He works on measuring political and social attitudes and investigates new, digital data sources and forms for empirical social research. For this purpose, he programs JavaScript-based tools, such as the open-source SurveyVoice (SVoice) tool for recording respondents’ voice answers in web-based surveys, and apply Automatic Speech Recognition, Natural Language Processing, and Text-as-Data Methods.

Laura Wronski, Survey Monkey. 

Laura Wronski is Director of Research at SurveyMonkey, where she leads a team of researchers developing best practices in online polling. She works with media outlets and key business partners to generate newsworthy insights from public opinion data. She joined SurveyMonkey in September 2015, after working as an economist at the Bureau of Labor Statistics. She has a master's degree from the Joint Program in Survey Methodology at the University of Maryland.

 Dr. Josh Pasek, University of Michigan. 

Josh Pasek is Associate Professor of Communication and Media and Political Science, Faculty Associate at the Center for Political Studies, Institute for Social Research, and Associate Director of the Michigan Institute for Data Science at the University of Michigan. His research explores how new media and psychological processes each shape political attitudes, public opinion, and political behaviors. Josh also examines issues in the measurement of public opinion including techniques for reducing measurement error and improving survey design. Current research explores how political information might influence public opinion and voter decision-making, evaluates whether the use of online social networking sites such as Facebook and Twitter might be changing the political information environment, and assesses the differences between survey results obtained from Internet volunteers as opposed to traditional samples. His work has been published in Public Opinion Quarterly, Political Communication, Communication Research, and the Journal of Information Technology and Politics among other outlets.