  Online community moderators often rely on social signals such as whether or
not a user has an account or a profile page as clues that users may cause
problems. Reliance on these clues can lead to overprofiling bias when
moderators focus on these signals but overlook the misbehavior of others. We
propose that algorithmic flagging systems deployed to improve the efficiency of
moderation work can also make moderation actions more fair to these users by
reducing reliance on social signals and making norm violations by everyone else
more visible. We analyze moderator behavior in Wikipedia as mediated by
RCFilters, a system which displays social signals and algorithmic flags, and
estimate the causal effect of being flagged on moderator actions. We show that
algorithmically flagged edits are reverted more often, especially those by
established editors with positive social signals, and that flagging decreases
the likelihood that moderation actions will be undone. Our results suggest that
algorithmic flagging systems can lead to increased fairness in some contexts
but that the relationship is complex and contingent.
