Unlocking the Power of Intuition in AI Development
In the quest to enhance AI, we face a crucial challenge: capturing the “Black Box” of intuition held by master craftsmen (Shokunin). Traditional methods focus solely on outcomes, neglecting the deep insights that precede actions. Here’s what you need to know:
- The Gemba Problem: Simply analyzing data tells you what happened, but intuition reveals why it matters.
- Introducing the TAREFC Model: This framework decodes the thought processes (Thinking Volume) behind actions (Action Volume) to improve AI learning.
- Key Shift in Questions: Instead of asking “What did you do?”, ask “What did you think?” This encourages deeper insights.
Explore how Shokunin can evolve into “Shokunin 2.0” as educators, guiding AI in intuition-driven decision-making.
👉 Join the conversation! Share your thoughts on digitizing intuition in AI below.
