My Fascination with Logic Errors

Preamble

As a developer of a theory (aka a methodologist) I was fascinated by the theory that a single logic error could unravel the entire theory. This fascination had its root in my being a capable computer programmer where a single logic error caused the termination of the program.

I decided to use the Google Gemini AI engine in my quest to uncover the origins of the theory that an error in logic (other than in a computer program) could render the theory null and void.

So I asked the following question

Is there a theory that states once an error in logic is discovered it is useless to continue with the theory?

My Research

The Google Gemini AI engine provided me with a response (on page 2) which it then proceeded to write a complete thesis (on page 3) which I have included in this article and one which I have proven more than once,

Conclusion

By failing to rectify the first logic error in a theory causes irreparable damage to future development.

For example:

1. Goals and Objectives: Peter Drucker not being capable of differentiating between a Goal and an Objective
2. Data: Edgar Codd’s logic error in his normalisation theory
3. Conceptual Data Model: Peter Chen's theory when a Data Model is a Logical construct and therefore cannot also be Conceptual
4. Balanced Scorecard: Kaplan and Norton’s 4 perspectives when the use of the conjunction ‘And’ in the ‘Learning and Growth’ perspective
5. DIKW Triangle: The interpretation of a ‘play on words’ by T.S. Eliot’s 1934 play ‘The Rock’ as the foundation of linking Wisdom and Data

Regards

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