Ever since that paper about "model decay" this has been a common talking point and it's greatly misunderstood. Yes, if you just repeatedly cycle content through AI training over and over through successive generations, you get AIs that lose "fidelity." But that's not what any actual real world training regimen using synthetic data does. The helper AI is usually used to process input data. For example, if you're training an AI to respond in a chat-like format, you could take raw non-conversational text (like a book) and have the helper AI create a conversation about that content for the new AI to learn from. Or to take a real-world example, Dalle3 was trained by having a helper AI look at pictures and create detailed text descriptions of them to use as the caption to associate with the image when training.

OpenAI has put these restrictions in its TOS as a way of trying to "pull up the ladder behind them", preventing rivals from trying to build AIs as good as the ones they have already. Fortunately it's not going to work. There are already open LLMs that can be used as "helpers" without needing OpenAI at all. ByteDance was likely just being lazy here.