One of the problems with this is opening up to criticism, liability, and further argumentation.
If you say "We removed them because of their political views," then you get criticized for being openly partisan.
If you say "We removed them because their comments were inciting violence," you'll get arguments about how their comments didn't actually tell people to do violent things (for example, in the US I'm sure for the near future, a lot of people will be arguing very loudly whether the specific phrases "fight like hell" and "trial by combat" are metaphorical rhetorical devices or literal instructions to take violent actions.)
People will start finding and pointing out situations where you made different decisions in near-identical circumstances, and criticize you for that too.
It's better for users if the platform's transparent.
But the platform has no incentive to do so. Less than 1% of the time will users say "Okay you told us why this person was banned, we now see the ban's fair, and we'll shut up and go home." Instead, 99% of the time they'll turn your explanation into another reason to be enraged at you, or argue you need to reconsider, or even sue you because that line of reasoning makes you liable.
From the platform's point of view, it's usually better to let the reasoning behind a ban be a question mark.
> "a big neural network said so"
This is part of it too. With ML-driven bans or other actions, it's possible that nobody understands what criteria it uses to make decisions.