What I learned running an adversarial test on an AI text detector (opens in new tab)

To test this proposition, I ran my own adversarial audit of Pangram over the past few days. In preliminary testing, I found that the tool misidentified AI-generated text as human if the content rhymed or repeated. Taking advantage of this weakness, I was able to get Pangram to falsely label AI text as human 86% of the time in an adversarial set of 588 text samples. I also found that slightly altering the order of words in short passages could cause Pangram to reverse its initial verdict on a ...