This talk describes how multiple selections can be used to automate repetitive text editing.  A multiple selection is inferred from positive and negative examples given by the user. The selection is then used for typing, deleting, copying, pasting, or other editing. Multiple selection editing has been evaluated by user studies and shown to be fast and usable by novices. "Outlier finding" is a new way to reduce errors by drawing the user’s attention to inconsistent data that may indicate errors. Miller has developed an outlier finder for text that can suggest both false positives and false negatives in a multiple selection. When integrated into the multiple-selection editor and tested in a user study, outlier finding reduced errors. From the Series:CSE Colloquia - 2002