Adaptive Threshold Tuner

Software componentHuman OversightExperience & Human Oversightarc:AdaptiveThresholdTuner

A feedback component that analyses human approval, modification, and rejection rates and adjusts escalation thresholds to observed user or team risk tolerance.

Responsibility. Tunes escalation thresholds from approval outcomes.

Also known as: Smart thresholds, Approval-rate tracker, Rejection reason analyzer

Direct neighbourhood (hover for relationship types)

Relationships

reads dependency

writes dependency

Escalation Threshold Policy Ch1.1B Ch9.2 +4

receives data from dynamic

Override Pattern Analyzer Ch10.2 Ch10.4 +1

Design guidance

SHOULD track approval rates and relax thresholds when reviewers approve nearly everything, tightening them when rejections are frequent.
SHOULD adjust confidence thresholds and policy parameters from shadow-period comparisons of human judgments with agent recommendations before activating enforcement.

Quantitative guidance

As stated by the sources; verify before use.

Approving >80% of requests without modification suggests the threshold is too low (Ch1.1A).
If users approve 95% of refunds under $1,000, raise auto-approval to $1,200 then $1,500; if 40% of flagged contracts are rejected, lower the escalation threshold (Ch1.1B).

Classification

Patterns: Adaptive thresholdsCategorized rejection reasons for statistical policy-gap analysis
Quality attributes: Performance efficiency (ISO/IEC 25010)Flexibility (ISO/IEC 25010)
Risks mitigated: Approval fatigueMissed edge cases

Sources

Ch1.1A: T. Nguyen, "Designing User Interfaces for Intuitive Human-Agent Interaction," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.1A. ISBN: 9798244538229.
Ch1.1B: T. Nguyen, "Human-in-the-Loop Patterns and Accessible Design," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.1B. ISBN: 9798244538229.
Ch9.2: T. Nguyen, "Action Constraints and Permission Models," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 9.2. ISBN: 9798244538229.
Ch10.2: T. Nguyen, "Proactive Agents," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.2. ISBN: 9798244538229.
Ch10.4: T. Nguyen, "Human-in-the-Loop," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.4. ISBN: 9798244538229.
Ch10.5: T. Nguyen, "Human-over-the-Loop," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.5. ISBN: 9798244538229.
Ref10.01: "Human-in-the-Loop Systems for Agent Interactions," unpublished reference note (01-Human-in-the-Loop-Systems.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note