Towards Understanding, and Defending Against Algorithmically Curated Misinformation

Abstract: Search engines and social media platforms are an indispensable part of our lives. Despite their increasing popularity, their search, ranking, and recommendation algorithms remain a black box to the users. The relevance of results produced by these search engines is driven by market factors and not by the quality of the content of those results. There is no guarantee that the information presented to people on online platforms is credible. To make matters worse, there are increasing concerns that online platforms amplify inaccurate information, making it easily accessible via search results and recommendations. My research takes a step towards understanding and designing defenses against algorithmically curated and amplified misinformation.

In this talk, I will first present the results of a series of algorithmic audits I performed on online platforms to determine the extent to which algorithms contribute to the spread of misinformation and under which conditions they do so. Additionally, I will discuss strategies to combat online misinformation by supporting the fact-checking process, emphasizing the importance of collaboration with fact-checkers. I will then introduce an online fact-checking system that I designed in collaboration with fact-checkers, specifically tailored to monitor misinformation on the YouTube platform. Finally, I will discuss the opportunities in the space of algorithm auditing and the various ways in which we can redress the harms caused by online algorithms.

Supervisory Committee
Chair: Tanushree Mitra, Assistant Professor, Information School
GSR: Sean Munson, Associate Professor, Department of Human Centered Design & Engineering (HCDE)
Member: Bill Howe, Associate Professor, Information School
Member: Chirag Shah, Professor, Information School

This event will be hybrid. Please note the in-person location change to MGH 258.