Winning the


Toxicity Arms Race


Mike Pappas, CEO of Modulate, explains how automated voice moderation has a natural advantage over methods of combatting abuse through text


A


utomated content moderation has, ever since its earliest incarnations, always been understood to be in an


arms race of sorts. A well-intentioned developer might build a tool to recognise certain hateful behaviors; and mere moments later, trolls and other bad actors will conceive of a way to work around it. Trying to look for certain keywords? No


problem, we’ll just replace the letter e with 3, o with 0, etc. Oh, you figured out common replacements?


We’ll get fancier, then, and use more obscure replacement characters, like the greek letter ο (that’s an omicron, not the letter ‘o’ - totally different to a computer program, but still completely readable to a person.) Text filters figure that one out, too? Well, we can just get fancier by strategically misspelling


28 | MCV/DEVELOP March 2022


words; adding spaces or punctuation marks between the letters, or other fancy techniques. The best text moderation tools today handle


all of these special cases and more… yet there are few forces more powerful than the ingenuity of people, even when the people in question are just really determined to type a racial slur. As such, any platform implementing text moderation needs to constantly be on watch for the next shot fired in this eternal war, and invest heavily to evolve their tools over time as new evasion techniques are developed. Given this situation, it’s understandable that


most people assume all content moderation efforts will be caught in this sort of perpetual cycle. Indeed, image and video moderation tends to suffer from the same challenges, as computers interpret pixels quite differently from the human eye, leaving plenty of room for the same sorts


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