AI to Learn 2.0: Governance Framework for Opaque AI in Learning
A recent publication on arXiv (2604.19751) presents AI to Learn 2.0, a governance framework focused on deliverables for AI-supported tasks in learning-heavy fields. This framework tackles the issue of proxy failure, which occurs when refined AI results do not align with human comprehension. It reinterprets established concepts concerning the end product, separating artifact residual from capability residual. Included in the framework are a five-part package, a seven-dimension maturity rubric, gate thresholds, and a capability-evidence ladder, facilitating the use of opaque AI during the exploration and drafting phases.
Key facts
- Paper published on arXiv with ID 2604.19751
- Title: AI to Learn 2.0: A Deliverable-Oriented Governance Framework and Maturity Rubric for Opaque AI in Learning-Intensive Domains
- Central problem is proxy failure in AI-assisted work
- Framework distinguishes artifact residual from capability residual
- Includes five-part package, seven-dimension maturity rubric, gate thresholds, and capability-evidence ladder
- Allows opaque AI during exploration and drafting
Entities
Institutions
- arXiv