In my free time, I help run a small Mastodon server for roughly six hundred queer leatherfolk. When a new member signs up, we require them to write a short application—just a sentence or two. There’s a small text box in the signup form which says:

Please tell us a bit about yourself and your connection to queer leather/kink/BDSM. What kind of play or gear gets you going?

This serves a few purposes. First, it maintains community focus. Before this question, we were flooded with signups from straight, vanilla people who wandered in to the bar (so to speak), and that made things a little awkward. Second, the application establishes a baseline for people willing and able to read text. This helps in getting people to follow server policy and talk to moderators when needed. Finally, it is remarkably effective at keeping out spammers. In almost six years of operation, we’ve had only a handful of spam accounts.

I was talking about this with Erin Kissane last year, as she and Darius Kazemi conducted research for their report on Fediverse governance. We shared a fear that Large Language Models (LLMs) would lower the cost of sophisticated, automated spam and harassment campaigns against small servers like ours in ways we simply couldn’t defend against.