Verification Learning Theory: A Process Model of Checking and Retention in AI-Assisted Judgment
Summary
- Verification Learning Theory (VLT) is introduced as a process model of checking and retention in AI-assisted judgment.
- The model links perceived assistant reliability to evidence checking and relates checking history to retained rule use.
- VLT predicts that perceived assistant fallibility can improve delayed unaided judgment even without observed errors.
- Simulations and comparisons with depth-of-processing accounts help test and define the proposed mechanism.
Why it matters
Understanding how AI assistance affects human learning and skill retention is critical for designing educational and professional workflows that prevent skill atrophy.