Appeals as System Feedback

Decision problem

How can recourse correct individual harm and improve the decision system without turning appeals into a biased label stream?

Working model

An appeal is selected by awareness, language, effort, stakes, account access, and belief that review is meaningful. Therefore overturn rate is informative but is not the full false-positive rate.

Research questions

• Which users never appeal and how can their errors be detected?
• How should reviewer evidence differ from model features?
• How are corrections propagated to linked sanctions, rewards, and training data?
• Can explanation quality improve valid appeals without giving adversaries a precise oracle?

Affected chapters

Chapters 6, 17, 18, 19, and 21.