Tanushree Mitra, Assistant Professor, Information School, University of Washington, Seattle
– 12 September 2023
Talk summary: Today, online social systems have become integral to our daily lives. Yet, these systems and the algorithms driving them surface problematic content, whether they be harmful misinformation or damaging conspiracy theories. Left unchecked, these problems can negatively impact our democracy. How do we systematically investigate algorithmic misinformation? How do we govern algorithmic systems to safeguard against problematic content? In her talk, Tanushree Mitra presented the results of algorithmic audits for misinformation conducted on the search and recommendation algorithms driving two platforms: 1) YouTube, the most popular video search platform and 2) Amazon, the world’s leading e-commerce platform. She presented ideas on how we can develop effective long-term algorithmic governance, the challenges in doing so and the new governance challenges and opportunities that are emerging with the recent advances in the field of large language models.
Speaker bio: Tanushree Mitra is an Assistant Professor in the Information School at the University of Washington, where she leads the Social Computing and ALgorithmic Experiences (SCALE) lab group. Her research focuses on studying and building large-scale social computing systems to understand and counter problematic information online. Her work employs a range of interdisciplinary methods from the fields of human computer interaction, data mining, machine learning, and natural language processing. Her work has been supported by grants from the DoD, Social Science One, and other Foundations. Her research has been recognised through multiple awards and honours, including an NSF-CRII, an early career ONR-YIP, the Adamic-Glance Distinguished Young Researcher award, and the Virginia Tech College of Engineering Outstanding New Assistant Professor award, along with several best paper awards. Mitra received her PhD in Computer Science from Georgia Tech and Master’s in Computer Science from the Texas A&M University.
[Talk organised in collaboration with the Department of Computational and Data Sciences]