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On Social.coop, we don’t just post and comment about what’s on our minds; we also decide on our moderation practices and enact them through committees. The Community Working Group handles conflict resolution through accountability processes. Its members are paid with funds from our sliding-scale member dues. The Tech Working Group maintains our servers, while the Finance Working Group keeps an eye on our budget. Any member can propose new activities and policies, and we can all vote on them according to the bylaws. We adjust Mastodon’s moderation settings as we see fit.

a number of servers organized to collectively ban those that harbored white supremacists, like Gab, from the rest of the fediverse — even if it remained active on the network, most people using Mastodon would never see Gab users’ posts.

The theories that make sense when you have huge amounts of data look quite different from those that make sense when you have small amounts

The bigger the dataset, the more inconsistencies the AI learns. The end result is not a theory in the traditional sense of a precise claim about how people make decisions, but a set of claims that is subject to certain constraints.

theory-free predictive engines embodied by Facebook or AlphaFold.

“Explainable AI”, which addresses how to bridge the interpretability gap, has become a hot topic. But that gap is only set to widen and we might instead be faced with a trade-off: how much predictability are we willing to give up for interpretability?