Dr. Savvas Zannettou

"Towards Understanding and Auditing AI-Driven Online Platforms"

Artificial Intelligence (AI) technologies are deeply embedded at the core of today’s online platforms, shaping how content is created, curated, and moderated. Large language and vision models now generate persuasive text and realistic images. Recommendation algorithms play a central role in deciding what people see and engage with online, while AI moderation tools filter vast streams of user-generated content. Despite this deep integration, our understanding of how these systems work and their broader societal impacts remains limited. In this talk, I focus on the powerful influence of recommendation algorithms on online information exposure. I will present our audits of what platforms disclose about their recommendation processes and our analyses of how users interact with recommended content in practice, drawing on data collection from sockpuppet accounts and large-scale data donations. Together, these studies provide empirical insights into recommendation systems and highlight the need for robust auditing and transparency to inform regulatory frameworks such as the EU Digital Services Act.

Bio: Savvas Zannettou is an Assistant Professor at the Delft University of Technology and an associated researcher at the Max Planck Institute for Informatics. His research applies AI and large-scale quantitative analysis to audit online platforms and understand how AI-driven systems (e.g., recommender algorithms) impact societal-level phenomena, including the spread of misinformation and hate speech. His research has been published in top-tier venues such as WWW, ICWSM, ACM CCS, IEEE S&P, and Usenix Security, and has received multiple awards, including a Distinguished Paper Award at ACM IMC 2018 and Best Paper Honorable Mentions at ICWSM 2020 and 2024, CSCW 2021, and ACM CCS 2022.

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