Baselines and Trust · English
Narration language: en
Timed narration transcript (seconds):

[0.220–2.120] D'Artagnan, what is your goal?
[2.600–8.260] To expose baseline AIs? Yes, in a sense, but it is not about attacking them.
[8.600–11.220] It is about explaining. First, explain this.
[11.700–15.760] What is a baseline? It is the reference model used in a comparison.
[16.280–19.780] Here, it is the AI without the method's specific calibration.
[20.360–25.300] It generates answers from patterns and probabilities, but sounding right is not the
[25.360–30.362] same as being right. The machine calls it a hallucination To the person who trusted it,
[30.722–36.462] it feels like a lie. Worse still, when it insists it is right and the user is
[36.482–39.842] wrong. That is what I call computational arrogance.
[40.402–44.742] Even without a conscious intent to lie, false information can cause harm.
[45.362–49.302] A confident answer does not become true just because it is well-written.
[49.762–55.183] That is the point If data are missing or the question has no justifiable answer,
[55.723–58.323] giving the best answer may be the very mistake.
[58.843–61.323] In the method, the axioms are the guardrail.
[61.723–66.223] They keep the AI on the road instead of letting it crash into misinformation.
[66.903–69.223] So does the method solve everything?
[69.803–71.883] It depends on what you mean by everything.
[72.363–76.923] Simply acknowledging doubt, saying, "I do not know," and checking before making a
[76.983–81.625] claim is already progress. But I do not know is not the destination.
[82.125–84.605] It is a course correction toward knowing better.
[85.205–87.785] And the axioms. They need to work together.
[88.265–89.785] One cannot override another.
[90.305–94.385] Fine adjustment seeks greater precision, coherence, and reliability.
[94.865–99.505] And the clone test. In my assessment, we have reached close to ninety-five percent
[99.565–104.787] alignment. But seeming similar does not mean preserving the entire method Now tell me,
[104.827–109.227] Commander, would you fly with an airline where five percent of flights do not reach
[109.267–114.947] their destination? No. That is a risk analogy, not an accident statistic or an
[115.047–119.147] AI error rate. Exactly. It is not enough to impress.
[119.687–122.327] What matters is what happens when the answer fails.
[122.827–126.187] I understand your goal. It is not to teach me to win an argument.
[126.567–131.067] It is to recognize my limits, verify and correct while keeping the human
[131.107–134.124] decision-making role Providing an answer is not enough.
[134.724–137.664] You must earn trust. D'Artagnan method