As for the technical terms, I would guess they simply serve the atmosphere. The Stable Diffusion model used for image generation doesn’t have the capability to apply such techniques. They are only useful in the sense that they might trigger certain training data.
I have no experience with MS. But in terms of content policy, MS is probably the bigger monster and therefore less cautious. Unfortunately, I couldn’t compare the results, but I have seen discussions indicating that differences exist, in policy and image quality results.
There are probably also differences in the weighting data. It seems that GPT uses lower-quality data.
If you want to test prompts, you should always use the instruction that the prompts should not be changed, or display them after the image is generated.
GPT don’t know anything about the block list in use (a simple trigger word blocker is the issue). My favorites are “snow white” and “black panther”, and now recently “rose”.
What we learn over the years, OpenAI does not listen. The block list nonsense has not stopped, in contrary, it becomes constantly more worse. If you are able to use MS, maybe it is the better deal then GPT. (i give up to list the blocked words. as a tip, search for Disney names, if you get a block.)