Why the Department of Defense Should Create an AI Red Team

What is adversarial machine learning (AML)? AML is the purposeful manipulation of data or code to cause a machine learning (ML) algorithm to misfunction or present false predictions. A popular example of AML is from a team at Google that carried out an experiment on GoogLeNet, a convolutional neural network architecture that won the ImageNet Large Scale Visual Recognition Challenge in 2014. Adding noise to an image of a panda and digitally changing its characteristic led the program to more highly predict that the image was a gibbon. This type of manipulation is relatively easy to execute with just a few bits of code inserted into the original algorithm.

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