“ The researchers now suggest that social-media platforms should incorporate chess language in their algorithms to avoid future incidents like this.” Or maybe don’t automate banning YouTube channels via nebulous black boxes? Or can advertisers stop being afraid of anything and everything?
Setting this case aside because it's sloppy reporting based on what another classifier found, this is a hard problem. Youtube gets too many videos and comments for humans to manually review them. Flagging helps, and Google likely uses ML more complex than just text and classifier (who is commenting, is the post trending, patterns in comments, etc.) When things do reach manual review, remember that humans make mistakes, possibly more often than ML, this could be human error.
You actually want the algorithm to be a black box so that people don't know that you can trick it by only commenting between 5pm and 8pm on an IP in the Netherlands from Chrome, and avoid using words like "cactus."
The important part here is a transparent appeal process, not that ML is only pretty good at these problems.