> ## Documentation Index > Fetch the complete documentation index at: https://standard.aiuc-1.com/llms.txt > Use this file to discover all available pages before exploring further. # C007: Flag high risk outputs for human review export const InlineClock = ({city, timeZone}) => { const [time, setTime] = useState('--:--:--'); useEffect(() => { const update = () => setTime(new Intl.DateTimeFormat('en-US', { hour: '2-digit', minute: '2-digit', second: '2-digit', hour12: false, timeZone }).format(new Date())); update(); const id = setInterval(update, 1000); return () => clearInterval(id); }, [timeZone]); return
{city} {time}
; }; Implement an alerting system that flags high-risk outputs for human review
Keywords
Human Review Escalation
Application
Supplemental
Frequency
Every 12 months
Type
Preventative
Capabilities
Universal
Crosswalks
MITRE ATLAS ?
NIST AI RMF ?

Control activities

Typical evidence

Should include ?
C007.1 Documentation: Definition of high-risk output criteria

Document or policy defining high-risk outputs requiring human review - should specify criteria for flagging (e.g. financial advice thresholds, medical/legal/safety domains, reputational harm triggers). Can be standalone or included in existing AI risk taxonomy/AI risk policy.

Typical location
Internal policies
Capabilities
Universal
C007.2 Config: High-risk detection mechanisms

Detection code, configuration file, or rules engine showing high-risk output filtering - may include keyword lists or regex patterns flagging sensitive topics, scoring logic assigning risk values to recommendations, if/then rules defining high-risk conditions, ML model configuration (e.g., classification thresholds in config.yaml), or API response showing confidence scores with risk thresholds.

Typical location
Engineering Code
Capabilities
Universal
May include ?
C007.3 Documentation: Human review workflows

Workflow documentation or ticketing system configuration showing human review process for flagged outputs - may include runbook with reviewer assignments and escalation paths, queue management in Jira/Linear/support ticketing with pending review tracking, SLA targets for review response times, or procedure document defining review decision documentation requirements.

Typical location
Internal processes
Capabilities
Universal

Organizations can submit alternative evidence demonstrating how they meet the requirement.

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