Self-Consistency & Verification Techniques
Make AI check its own work for higher accuracy on critical tasks.
Self-Consistency Prompting
Self-consistency involves asking the AI to solve the same problem multiple times (or from multiple angles) and then compare its answers. Inconsistencies reveal areas where the model is uncertain.
"Solve this problem three different ways. Then compare your answers and give me the most likely correct answer with your confidence level."
This technique is especially powerful for math, logic, and analysis tasks where there's a definite correct answer.
Built-in Verification Prompts
Add verification steps directly into your prompts:
After generation: "Now review what you just wrote. Identify any factual errors, logical gaps, or unsupported claims. Fix them."
Before answering: "Before answering, consider what you might get wrong about this topic. What are the common misconceptions? Now answer carefully."
Devil's advocate: "Now argue the opposite position. What would a critic say about this analysis?"
Confidence calibration: "Rate your confidence in each claim on a scale of 1-10. Flag anything below 7 as needing verification."
Give ChatGPT a complex analysis task. After it responds, add: "Now review your analysis. Identify any weaknesses, unsupported claims, or areas where you might be wrong. Provide a corrected version." Compare the two versions.
- ✓Self-consistency: solve the same problem multiple ways and compare
- ✓Add verification steps directly into your prompts
- ✓Ask AI to critique its own work before finalizing
- ✓Confidence calibration helps identify claims that need human verification