Feasibility of implementing deployment corrections at scale

Investigate technical strategies to implement user‑based restrictions, access frequency limits, capability or feature restrictions, use‑case restrictions, and model shutdown in deployed AI systems, assessing feasibility and impacts on continuity and reproducibility.

Background

Deployment corrections aim to mitigate risks after deployment but may cause disruption or conflict with research reproducibility.

Technical pathways are needed to operationalize corrections across diverse systems while minimizing negative impacts.