Cybersecurity for Democracy

Cybersecurity for Democracy is a multi-university center for problem-driven research and research-driven policy. We conduct cutting-edge cybersecurity research to better understand the distorting effects of algorithms and AI tools on large online networks and work with platforms and regulators to help all parties understand the implications of our findings and develop solutions.

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Yaël Eisenstat Joins Cybersecurity for Democracy as Senior Policy Fellow, Focusing on Democratic Discourse and AI-Powered Political Messaging.

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Lab Notebook: Predicting Virality. The ability to predict viral content has clear ramifications for content moderation and harm mitigation. Under the resource constraints that most Trust and Safety teams face, knowledge of which adverse content (e.g. hate, harassment, misinformation etc.) will garner the most engagement, enables more efficient allocation of time and effort to address them. We found that looking at the engagement alone without considering post or account features, we are able to predict with a binary F1 of 0.8 whether a post’s final engagement would be in the top 1% by hours 13–17.

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In the afternoon of January 6, 2021, Facebook leadership announced they were “appalled by the violence at the Capitol today,” and were approaching the situation “as an emergency.”

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An investigation by Global Witness and the Cybersecurity for Democracy (C4D) team at NYU looked at Facebook, TikTok, and Youtube's ability to detect and remove election disinformation in the run-up to the U.S. midterm elections. The results? TikTok approved 90% of the election disinformation ads tested, Facebook had a mixed record. Only YouTube succeeded both in detecting the ads and suspending the channel carrying them.

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Yaël Eisenstat Joins Cybersecurity for Democracy as Senior Policy Fellow, Focusing on Democratic…

Yaël Eisenstat Joins Cybersecurity for Democracy as Senior Policy Fellow, Focusing on Democratic Discourse and AI-Powered Political Messaging We are thrilled to announce the latest addition to the Cybersecurity for Democracy team — Yaël Eisenstat, a seasoned expert and thought…

Predicting Virality: How soon can we tell?

Introduction The ability to predict viral content has clear ramifications for content moderation and harm mitigation. Under the resource constraints that most Trust and Safety teams face, knowledge of which adverse content (e.g. hate, harassment, misinformation etc.) will garner…

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