How AI Inference Threats Might Influence the Outcome of 2020 Election

Posted on in Presentations

What we have learned from the US 2016 election interfered by Russian. This session will inspect the inference threats on how elections in the international community interfered by inference threats. The session will also analyze the patterns of disinformation and misinformation used in the past elections and how artificial intelligence might be applied to influence the outcome of the 2020 election.

Pre-Requisites: Understanding of Data Privacy Engineering concepts and general information technology background interested in inference threats.

Interested? We have you covered! This popular session will also be overflowed in The Session Viewing Point, West Level 2 Room 2004.

Karel Baloun


Software Architect and Entrepreneur, UC Berkeley

Ken Chang


Cybersecurity Researcher, University of California - Berkeley

Matthew Holmes


Cybersecurity Student, UC Berkeley

Identity Machine Learning & Artificial Intelligence Human Element Analytics Intelligence & Response

threat intelligence identity theft big data analytics artificial intelligence & machine learning



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