If you’ve been following news about artificial intelligence, you’ve probably heard of or seen modified images of pandas and turtles and stop signs that look ordinary to the human eye but cause AI systems to behave erratically. Known as adversarial examples or adversarial attacks, these images—and their audio and textual counterparts—have become a source of growing interest and concern for the machine learning community. But despite the growing body of research on adversarial machine learning, the numbers show that there has been little progress in tackling adversarial attacks in real-world applications. The fast-expanding adoption of machine learning makes it paramount that the tech community traces…
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