Epistemic Transfer in AI-Assisted Verification: A Framework and Evaluation Protocol
This paper introduces the Epistemic Transfer Effect (ETE), which compares delayed unassisted performance across conditions, and Tool-Removal Cost (TRC), which measures the immediate drop in performance when the tool is taken away, and turns these ideas into a practical evaluation protocol that can be used in online experiments or field studies.
Christoph Trattner
· 0 citations