That brings me to the second question. If there is no credibly neutral convener, this becomes very difficult, because people will say the criteria were gamed — that someone skewed the pseudo-random generation, or whatever. In that case, you need what I call an adversarially trained network to emerge. A good example: X, when it was still Twitter, adopted this method, and they now call it Community Notes on X. X does not work with a credibly neutral institution,which probably does not exist for the X population. Instead, they open-sourced the algorithm: for any post to receive a Community Note, that note must be reviewed and agreed by people on two opposing sides. So, whatever note goes viral and attaches to a post has been critically examined — almost like a debate — by people who really want to find fault with it. They then trained their system, Grok, on this bridging, adversarially trained corpus, so that I believe about half the notes are now drafted by Grok. Grok knows how to translate climate-justice ideas into biblical creation-care ideas, and to write language in which both sides can see something of themselves.