OPENBOX aims at bringing an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in various areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series.

In this podcast we have Kathrin Grosse. Kathrin Grosse is a Post Doc researcher with Battista Biggio at the University of Cagliari working on Adversarial learning.

In this podcast we cover a paper titled “Machine Learning Security against Data Poisoning: Are We There Yet? ” published in April 2022, which she co-authored.

This is part 1 of the podcast. In this podcast, she covers the thoughts around the impracticality of some threat models considered for poisoning attacks in a real-world application and scalability of poisoning attacks against large-scale models

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