Sometimes the most profound insights emerge from unexpected moments. While waiting for my Thanksgiving ham to cook, I discovered something unsettling about AI that would challenge my assumptions about enterprise implementation. As an IEEE CertifAIEd Lead Assessor, I’ve evaluated countless AI systems, but this holiday experiment in my kitchen revealed a critical gap between AI confidence and competence that every technology leader needs to understand.
The results were stark: leading AI models showed remarkably high confidence while failing at basic rule-following tasks. ChatGPT achieved 13% accuracy, Claude reached 21%, and Gemini performed best at 46% – yet all displayed confidence levels above 90%. This disconnect mirrors patterns I’ve witnessed in enterprise settings, where sophisticated AI implementations often mask fundamental governance gaps.
In this article, I share both personal insights from this unexpected experiment and professional guidance for implementing effective AI governance. Drawing from years of certification experience and real-world testing, I offer a practical framework for ensuring your AI systems don’t just appear competent, but actually follow critical operational rules.
[Read more to discover the four pillars of effective AI governance and a practical implementation roadmap for 2025…] […]
When AI Can’t Follow Simple Rules: Personal Insights from an Unexpected Experiment Part 2 of The AI Ethics Puzzle Series
