Runtime Fairness & Drift Correction
A model’s internal state can change over time, changing the fairness of its decisions. R3 connects detection of that drift with fairness judgments, correction and independent verification, then relates the evidence to conditions for each execution request.
Discuss this technology
Intervene and evaluate
Verify for execution
Follow fairness through changing model behavior and test the consequences of an intervention.
A clear process.
Traceable decisions.
Detect meaningful change
Observe changes in internal state and evaluate whether they create a fairness issue that calls for intervention.
Intervene and evaluate
Address the cause of the change, then examine the correction’s intended effect, possible side effects and preservation of performance.
Verify for execution
Use independent verification and relevant request conditions to assess the evidence before it supports execution, keeping the correction and its evaluation connected.
Where the architecture
can make a difference.
- Runtime fairness monitoring and optional drift or correction signals for Competition AOS.
A valid certificate signature alone is insufficient evidence that a particular request meets execution conditions.
Discuss Runtime Fairness & Drift Correction.
Explore the architecture, relevant licensing scope and a concrete application.
