Inductive reasoning

Metadata

• Slug: 00205-inductive-reasoning
• Type: PARADOX
• Tags: probability
• Sources: 1

Axioms

• Assume the rules of the domain apply uniformly.
• Assume the observer’s criteria remain fixed.
• Assume classification boundaries stay consistent.
• Assume the model describes the real case.
• Assume repeated steps do not change the outcome.
• Assume no hidden variables are introduced midstream.

Contradictions

• Two reasonable lines of inference yield opposite conclusions
• A global rule conflicts with a local judgment
• A stable resolution appears to violate a starting premise
• Changing the framing reverses the outcome
• Intuition and formalism diverge at the same step

Prompts

• Which assumption is doing the most hidden work?
• What changes if you relax the smallest constraint?
• Does the paradox dissolve or relocate when reframed?
• What is conserved, and what is sacrificed?

Notes

Sources

• https://en.wikipedia.org/wiki/Inductive_reasoning

Overview

Inductive reasoning refers to a variety of methods of reasoning in which the conclusion of an argument is supported not with deductive certainty, but at best with some degree of probability. Unlike deductive reasoning (such as mathematical induction), where the conclusion is certain, given the premises are correct, inductive reasoning produces conclusions that are at best probable, given the evidence provided.

Tension

• Two reasonable lines of inference yield opposite conclusions.
• A global rule conflicts with a local judgment.
• A stable resolution appears to violate a starting premise.
• Changing the framing reverses the outcome.
• Intuition and formalism diverge at the same step.

Why It Matters

This entry tests how a stable rule-set can yield unstable conclusions under certain assumptions.

Prompts

• Which assumption is doing the most hidden work?
• What changes if you relax the smallest constraint?
• Does the paradox dissolve or relocate when reframed?
• What is conserved, and what is sacrificed?