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The Universal Reasoning Triad and the Causal Pertinence Test A woman with a stable income, who meets the bank's requirements and has never missed a payment, has her loan application rejected by an automated system. The reason is that she lives in a zip code statistically associated with higher default rates. Is that correlation enough to justify a decision about her? This video summarizes the essay in which I propose the Universal Reasoning Triad: Objective, Verifiable Link, and Goal Attained. The decisive question lies in the link: is it pertinent and sufficient to support the conclusion in the specific case? The issue, addressed by traditions ranging from Aristotle and Confucius to Kant and Peirce, becomes urgent with artificial intelligence. A fluent answer, even one with steps that seem to explain it, does not guarantee that it faithfully reconstructs the process that produced it. And getting the right answer is not always the same as justifying it. To audit the link, I propose, by analogy, the Causal Pertinence Test. It applies to human and algorithmic decisions alike: we must always be able to examine what supports a conclusion and whether that foundation is enough for the specific case at hand. Read the full essay (in Spanish). Most browsers can translate it automatically: https://medium.com/@ernesto.celdeiro/la-tr%C3%ADada-del-razonamiento-universal-y-el-l%C3%ADmite-de-la-atinencia-causal-dc0d745c89d8

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