Trust-But-Verify AI Approach

A Trust-But-Verify AI Approach is an AI Governance Approach that is a Human-AI Collaboration Framework that can support validated AI decision-making tasks.

• AKA: AI Verification Framework, Human-Validated AI Method, Supervised AI Automation Approach.
• Context:
  • It can typically require Human Expert Validation of AI-generated recommendations before business action execution.
  • It can typically establish Confidence Thresholds for automated decisions through risk-based assessment.
  • It can typically implement Audit Trail Mechanisms for AI decision history via validation logging.
  • It can typically enable Override Protocols for AI recommendations using human judgment priority.
  • It can typically maintain Performance Feedback Loops between human validators and AI systems through continuous learning.
  • ...
  • It can often provide Explanation Interfaces for AI reasoning processes via interpretability features.
  • It can often support Selective Automation of low-risk decisions through risk stratification.
  • It can often enable Batch Review Modes for high-volume validation using efficient review workflows.
  • It can often implement Escalation Pathways for complex cases through tiered review structure.
  • ...
  • It can range from being a Minimal Trust-But-Verify AI Approach to being a Comprehensive Trust-But-Verify AI Approach, depending on its verification requirement stringency.
  • It can range from being a Synchronous Trust-But-Verify AI Approach to being an Asynchronous Trust-But-Verify AI Approach, depending on its validation timing model.
  • It can range from being a Single-Reviewer Trust-But-Verify AI Approach to being a Multi-Reviewer Trust-But-Verify AI Approach, depending on its validation team structure.
  • ...
  • It can integrate with AI Contract Metadata Extraction Systems for contract data validation.
  • It can connect to Compliance Management Systems for regulatory requirement enforcement.
  • It can interface with Quality Assurance Platforms for validation metric tracking.
  • It can synchronize with Training Data Repositorys for model improvement feedback.
  • It can communicate with Risk Management Systems for risk-based review prioritization.
  • ...
• Example(s):
  • Domain-Specific Trust-But-Verify Implementations, such as:
    • Legal Contract Trust-But-Verify System requiring attorney validation of AI-extracted contract terms before obligation commitment.
    • Medical Diagnosis Trust-But-Verify System mandating physician review of AI diagnostic suggestions before treatment decision.
    • Financial Trading Trust-But-Verify System enforcing trader approval of AI trading recommendations before order execution.
    • Regulatory Compliance Trust-But-Verify System requiring compliance officer review of AI risk assessments before regulatory filing.
  • Verification Depth Levels, such as:
    • Spot-Check Verification Mode for routine low-stakes decisions with random sampling validation.
    • Threshold-Based Verification Mode for medium-risk decisions exceeding defined confidence limits.
    • Full Manual Verification Mode for high-stakes decisions requiring complete human review.
    • Dual-Review Verification Mode for critical decisions needing multiple validator consensus.
  • Industry Applications, such as:
    • Insurance Claim Trust-But-Verify System for claim assessment validation and payout authorization.
    • Loan Underwriting Trust-But-Verify System for credit decision review and risk evaluation.
    • HR Screening Trust-But-Verify System for candidate assessment validation and hiring recommendation.
  • ...
• Counter-Example(s):
  • Fully Autonomous AI System, which executes AI decisions without human validation requirement.
  • Manual Override System, which allows human intervention but doesn't require systematic verification.
  • Post-Hoc AI Audit System, which reviews AI decisions after execution rather than requiring pre-execution validation.
• See: AI Governance Approach, Human-AI Collaboration Framework, AI Contract Metadata Extraction System, AI Validation Protocol, Human-in-the-Loop System, AI Risk Management Framework.

---