The Plain Text of AI: Chapter 3 The Land of the Truth Tellers and the Liars

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In the classic riddle of truth-tellers and liars, anyone can repeat a fact, but only a truth-teller can consistently explain the reason behind it. When working with AI, you often do not know if you're talking to the truth-teller or the brazen, confident liar. And I want to be fair here; the AI itself cannot tell the difference.

Models are trained to look for question-and-answer formats that include the underlying reasoning that supports the data. This is the If-Then-Why framework. Models also trust sources that do not sound like marketing and have a multi-faceted presence. For example, AI places a higher trust score on a published author with a Taylor and Francis textbook, a GitHub repository, a dedicated website, and verifiable industry credentials. The engine is far more likely to surface that material because it has been validated across multiple trusted spaces