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Who Owns the Objective Function? — The Implicit Judgments Embedded in Scores and the Problem of the Values Humans Did Not Write Down —

AI is often believed to be fair.It evaluates through numbers, remains unaffected by emotion, and produces consistent jud...

2026.02.18

ICT技術:ICT Technology人工知能:Artificial Intelligence

Why AI Cannot Possess “Common Sense” — Common Sense as a Collection of Discontinuities, and Common Sense as Ontology —

AI knows an enormous amount. Wider than an encyclopedia.Faster than a specialist. And yet, at a certain moment, we fee...

2026.02.17

ICT技術:ICT Technology人工知能:Artificial Intelligence

Why “Explainable AI” Does Not Constitute a Fundamental Explanation — The Difference Between Explanation and Justification, and the Division of Roles Between Logic and Accountability

There is a term called “Explainable AI (XAI).”AI that is not a black box.AI that can explain the grounds of its decision...

2026.02.16

ICT技術:ICT Technology人工知能:Artificial Intelligence

Probability Is Not for Reducing Uncertainty — The True Role of Probability and the Perspective of Designing to Preserve Ambiguity

When probabilities are presented, people feel reassured. Success probability: 82%Risk: 18%Confidence: 0.91 When number...

2026.02.15

ICT技術:ICT Technology人工知能:Artificial Intelligence

What Happens When Optimization Runs Wild — The Moment a Loss Function Distorts the World, and How to Design for Goodhart’s Law

AI Is Good at Optimization.In fact, that is all it can do. Precisely because of that,when optimization runs wild, the w...

2026.02.14

ICT技術:ICT Technology人工知能:Artificial Intelligence

Why AI Cannot Bear Responsibility — Why Judgment and Responsibility Cannot Be Separated, and Why Logic Must Be Externalized

AI produces answers with astonishing accuracy.Sometimes faster than humans, more comprehensive, more consistent, more ca...

2026.02.13

ICT技術:ICT Technology人工知能:Artificial Intelligence

e and π — the numbers that allow the world to be computed smoothly.

Up to this point, we have examined the structure of decision-making —judgment, optimization, inference, and execution. ...

2026.02.12

ICT技術:ICT Technology人工知能:Artificial Intelligence

Where Do Humans Remain? — Redefining Human-in-the-loop

Let Us Summarize What We Have Discussed So Far AI does not understand the world. What AI handles is nothin...

2026.02.11

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Describe the Discontinuities — Fixing Decision Structures with Ontologies and DSLs

In yesterday’s article,I started from the premise that judgment is not singular,and discussed a multi-agent design that ...

2026.02.10

Uncategorized

Judgment Is Not Singular — Multi-Agent Design Built on Structural Discontinuity

As argued in the previous chapter,AI does not understand the world.What it does is nothing more than smooth function app...

2026.02.09

Uncategorized

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Who Owns the Objective Function? — The Implicit Judgments Embedded in Scores and the Problem of the Values Humans Did Not Write Down —

Why AI Cannot Possess “Common Sense” — Common Sense as a Collection of Discontinuities, and Common Sense as Ontology —

Why “Explainable AI” Does Not Constitute a Fundamental Explanation — The Difference Between Explanation and Justification, and the Division of Roles Between Logic and Accountability

Probability Is Not for Reducing Uncertainty — The True Role of Probability and the Perspective of Designing to Preserve Ambiguity

What Happens When Optimization Runs Wild — The Moment a Loss Function Distorts the World, and How to Design for Goodhart’s Law

Why AI Cannot Bear Responsibility — Why Judgment and Responsibility Cannot Be Separated, and Why Logic Must Be Externalized

e and π — the numbers that allow the world to be computed smoothly.

Where Do Humans Remain? — Redefining Human-in-the-loop

Describe the Discontinuities — Fixing Decision Structures with Ontologies and DSLs

Judgment Is Not Singular — Multi-Agent Design Built on Structural Discontinuity

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