Why is this the case?
In this talk, we take a closer look at this question, and pinpoint some of the roots of this observed brittleness. Specifically, we discuss how the way current ML models “learn” and are evaluated gives rise to widespread vulnerabilities, and then outline possible approaches to alleviate these deficiencies.