Course Overview
This AI course develops advanced critical thinking and analytical skills specifically designed for evaluating artificial intelligence outputs in professional settings. Participants master systematic analysis techniques used by elite forecasters to dissect AI recommendations, identify logical flaws, and apply rigorous evidence-based reasoning when AI-generated insights inform important decisions.
This intensive and carefully designed course transforms participants from passive AI consumers into sophisticated analysts who can critically examine, validate, and strategically leverage artificial intelligence while avoiding the pitfalls that trap less-discerning users.
Target Audience
This AI course is suitable for:
- Business leaders making AI-assisted strategic decisions
- Professionals currently using AI tools (LLM’s) Managers integrating AI into workflows and decision-making
- Anyone who needs to critically evaluate AI outputs and underlying data
Attendee Prerequisites
No technical background required – this in-depth mentoring session focuses on judgment skills, not coding.
- Highly interactive with hands-on exercises using real AI outputs
- Practical focus – skills participants can apply immediately
- Small group format (max 10) for personalized attention
- Research-based methodology with tournament scoring and calibration exercises
- Structured framework for evaluating any AI output
- Calibration tools to improve decision accuracy
- Elite forecasting techniques from DARPA’s superforecaster research for evaluating AI accuracy
- Quantitative uncertainty assessment using 90% confidence intervals
- Rapid validation methods including Doug Hubbard’s Rule of Five for efficient AI testing Advanced bias detection in AI outputs and training data
- Strategic prompt engineering for more reliable AI responses
- Structured frameworks for measuring “unmeasurable” AI claims
SESSION OUTLINE: 09:30 – 16:30 HRS
MORNING: Foundations & Framework
- Science of elite judgment in the AI era
- DARPA* – validated superforecaster techniques applied to AI
- Hands-on lab: Structured AI evaluation using research-based methods
AFTERNOON: Advanced Analysis & Implementation
- Data scepticism and statistical reasoning for AI outputs
- Strategic AI partnership through better human judgment
- Real-world simulation with tournament-style accuracy scoring
- Unique Value Proposition
- Unlike generic “AI literacy” courses, this is grounded in scientifically validated judgment research.
- Participants learn the same techniques that consistently outperform experts in prediction tournaments – now applied specifically to AI evaluation.
*The DARPA project is the Good Judgement Project which is talked about in the book Superforecasting by Philip E. Tetlock et al.
