Trust Assessment: Ensuring Research Integrity Through Participant Validation
What is Trust Assessment?
Trust Assessment is Perspective AI's automated fraud detection system that evaluates interview participants for authenticity and trustworthiness. This AI-powered feature analyzes multiple participant signals to help you identify potentially fraudulent respondents and maintain the integrity of your research data.
Why Trust Assessment Matters
Research integrity depends on authentic participant responses. Fraudulent participants can:
- Skew your research findings with inaccurate data
- Waste valuable research budget on unreliable insights
- Compromise decision-making based on flawed data
- Damage the credibility of your research outcomes
Trust Assessment helps you identify these risks before they impact your research, ensuring you can make confident decisions based on verified participant data.
How Trust Assessment Works
Automated Analysis
Once an interview is completed, Trust Assessment automatically analyzes the participant across multiple trust dimensions using advanced AI. The system examines various signals including:
- Identity Verification: Validates provided personal information and professional profiles
- Role & Experience Relevance: Assesses whether the participant's background aligns with research requirements
- Technical Signals Consistency: Examines IP addresses, timezones, and device information for consistency
- Response Quality & Engagement: Evaluates the depth, relevance, and authenticity of responses
- Eligibility Criteria Confirmation: Verifies that participants meet your specific research criteria
Comprehensive Scoring System
Each trust dimension receives:
- Individual Score (0-100): Specific assessment for that dimension
- Confidence Level (Low/Medium/High): How certain the AI is about its evaluation
- Detailed Reasoning: Explanation of factors influencing the score
- Overall Assessment (0-100): Combined trust score across all dimensions
Actionable Recommendations
The system provides specific verification steps you can take, such as:
- Verifying LinkedIn profiles or professional credentials
- Confirming specific eligibility criteria (e.g., company size, tool usage)
- Cross-checking technical signals for consistency
Understanding Your Trust Assessment Results
Trust Score Interpretation
- High Scores (80-100): Participant shows strong trust signals across multiple dimensions
- Medium Scores (60-79): Some concerns identified, but participant may still be reliable with verification
- Low Scores (0-59): Significant trust concerns detected, recommend careful review or exclusion
Summary Classifications
Trust Assessment provides clear guidance with summaries starting with either:
- "Trustworthy": Participant demonstrates strong authenticity signals
- "Suspicious": Multiple red flags detected requiring further investigation
Confidence Levels
- High Confidence: Strong evidence supporting the assessment
- Medium Confidence: Good indicators but some uncertainty remains
- Low Confidence: Limited data available for definitive assessment
When to Use Trust Assessment
Automatic Activation
Trust Assessment runs automatically on all completed interviews, providing immediate fraud detection without manual intervention.
Re-running Assessments
You can manually re-run Trust Assessment if:
- New information becomes available about a participant
- You want a fresh analysis with updated AI models
- Initial assessment had low confidence and you need verification
Integration with Research Workflow
Use Trust Assessment results to:
- Filter participants before including data in analysis
- Weight responses based on trust scores in your findings
- Flag interviews that require manual review
- Validate sample quality across your entire research project
Best Practices
Review All Dimensions
Don't rely solely on the overall score—examine individual trust dimensions to understand specific concerns or strengths.
Act on Recommendations
Follow the specific verification steps provided to increase confidence in borderline cases.
Consider Context
Factor in your research requirements and risk tolerance when interpreting scores. Critical research may require higher trust thresholds.
Document Decisions
Keep records of how Trust Assessment influenced your participant inclusion decisions for research transparency.
Technical Reliability
Trust Assessment leverages advanced AI models specifically trained for fraud detection in research contexts. The system:
- Analyzes patterns across thousands of data points
- Continuously improves through machine learning
- Provides transparent reasoning for all assessments
- Maintains high accuracy rates in identifying fraudulent participants
Getting Started
Trust Assessment is automatically enabled for all interviews. Simply complete your interviews and review the Trust Assessment results in the interview analysis section. Look for the Trust Assessment tab to access detailed scoring, recommendations, and verification steps for each participant.