Computational Social Science Forum
Date: Monday, February 22, 2021
Time: 12:00-1:30 PM Pacific Time
Location: Register to receive the schedule and access links.
Loops, Ladders and Links: The Recursivity of Social and Machine Learning
Speakers: Marion Fourcade, Professor of Sociology, UC Berkeley; and Fleur Johns, Professor in the Faculty of Law, UNSW
Abstract: Machine learning algorithms reshape how people communicate, exchange and associate; how institutions sort them and slot them into social positions; and how they experience life, down to the most ordinary and intimate aspects. Drawing on this published paper and examples from the field of social media, we will review the commonalities, interactions and contradictions between the dispositions of people and that of machines as they learn from, make sense of, and jointly produce the world.
The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Weekly meetings are hosted by researchers from BIDS and D-Lab, and participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. We welcome social scientists researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. This Forum is organized as part of the Computational Social Science Training Program, and interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact email@example.com for more information.