⚖️ Trust Calibration Practice

Learn when to trust AI recommendations and when to apply your own judgment

The Art of Calibrated Trust

Working effectively with AI security tools requires calibrated trust—knowing when to follow AI recommendations and when to override them with your own judgment. This isn't about blind trust or complete skepticism; it's about making informed decisions based on evidence, context, and confidence levels.

Practice with the scenarios below. Each presents a situation where AI has made a security recommendation. Your job is to decide whether to trust the AI or override it based on the evidence provided.

Trust Decision Framework

✅ Trust AI When:

  • High confidence (>85%) with clear evidence
  • Multiple corroborating indicators
  • Specific, verifiable reasoning provided
  • No conflicting personal context

❓ Investigate When:

  • Medium confidence (50-85%)
  • Vague or general reasoning
  • Single indicator without support
  • Situation seems unusual but explainable

🚫 Override AI When:

  • You have context AI doesn't have
  • Low confidence (<50%) with weak evidence
  • Recommendation contradicts known facts
  • AI reasoning doesn't make logical sense

Interactive Scenarios

For each scenario, decide whether to trust AI's recommendation or override it with your own judgment. Click your choice to see feedback and learn the reasoning.

Key Principles of Trust Calibration

Understanding Confidence Levels

AI confidence percentages tell you how certain the system is, but they're not the whole story:

  • High Confidence (85-100%): Usually reliable, especially with specific evidence. Trust unless you have strong contradictory context.
  • Medium Confidence (50-85%): Warrants investigation. AI has detected something but isn't certain. Verify through additional channels.
  • Low Confidence (<50%): AI is unsure. Rely more on your own judgment and additional verification methods.

    • Important: Confidence level alone isn't enough. A 95% confidence based on one vague indicator is less trustworthy than 75% confidence based on three specific, verifiable indicators.

    Context Is Your Superpower

    AI systems analyze data, but they don't know your personal context. This is where human judgment is essential:

    🗓️ Your Schedule

    AI flags a login from Tokyo as suspicious. You're currently on a business trip to Tokyo. Your context overrides the AI alert.

    👥 Your Relationships

    AI questions an email from a colleague. You just discussed this exact topic with them this morning. Your context confirms legitimacy.

    🎯 Your Workflows

    AI flags unusual file access. You're running a scheduled backup process you initiated. Your context explains the anomaly.

    ⚠️ When Context Doesn't Help

    AI detects phishing with specific technical indicators. Your personal context doesn't override technical evidence. Trust the AI.

    Common Calibration Mistakes

    Avoid These Pitfalls

  • Over-trusting AI: Following high-confidence recommendations without checking if they make sense in your context
  • Over-trusting yourself: Ignoring strong AI warnings because "it looks fine to me" when you lack technical expertise
  • Ignoring confidence levels: Treating 55% confidence the same as 95% confidence
  • Dismissing without investigation: Overriding AI without verifying your reasoning is correct
  • Analysis paralysis: Spending too much time on low-risk decisions instead of acting decisively

    • Building Your Calibration Skills

    Trust calibration improves with practice. The more you work with AI security tools, the better you'll understand:

    Learn AI Literacy Fundamentals → Explore AI Defense Capabilities →