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Monitoring malicious, user-generated content; contextual AI; adapting to novel evasion attempts: Matar Haller speaks to Jon Krohn about the challenges of identifying, analyzing and flagging malicious information online. In this episode, Matar explains how contextual AI and a \u201cdatabase of evil\u201d can help resolve the multiple challenges of blocking dangerous content across a range of media, even those that are live-streamed.This episode is brought to you by Posit, the open-source data science company, by Anaconda, the world's most popular Python distribution, and by WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.In this episode you will learn:\u2022 How ActiveFence helps its customers to moderate platform content [05:36]\u2022 How ActiveFence finds extreme social media users trying to evade detection [16:32]\u2022 How to monitor live-streaming content and analyze it for dangerous material [29:13]\u2022 The technologies ActiveFence uses to run its platform [35:54]\u2022 Matar\u2019s experience of the Insight Fellows Program (Data Science Fellowship) [40:28]\u2022 Leadership opportunities for women in STEM [1:00:41]\u2022 Israel\u2019s R&D edge for AI [1:13:19]Additional materials: www.superdatascience.com/683