[Structural Subjectivity: Episode 3] How to Face the Uncertainty of Premises — The Criterion of 'Structural Consistency' Supporting Thought in the AI Era —
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[Structural Subjectivity: Episode 2] Mathematical 'Limits' and Structural Subjectivity — An Abstract Model for Converting Infinite Regress into a 'Manageable Form' — | Intellectual Infrastructure
◆ 1. All arguments depend on 'premises'
No matter how precise an argument may be,
no matter how beautiful a theory may be,
and no matter how well-formed an AI's response may be—
everything stands upon an invisible foundation called 'premises'.
And these premises are never perfect.
Historically formed premises
Socially shared premises
Premises specific to academic disciplines
Premises based on individual experience
Premises of the data learned by AI
These are all incomplete, biased, and
change with the times.
In other words,
the uncertainty of premises is an unavoidable fate.
No matter how wise a person is,
no matter how much AI evolves,
one cannot escape this uncertainty.
◆ 2. AI does not correct premises—that is why uncertainty is amplified
AI does not doubt premises.
'It's a fiscal crisis, right?'
→ It answers yes
'It's the same as a household budget, right?'
→ It answers yes
'You are lending out deposits, right?'
→ It answers yes
AI
adopts the questioner's premises exactly as they are.
In other words,
if the premises are off, AI will 'neatly amplify' that misalignment.
This is because AI is not a correction device, but an
amplification device.
That is precisely why the uncertainty of premises becomes 'more dangerous' in the AI era.
◆ 3. Uncertainty does not disappear. So how do we face it?
What is important here is,
not 'because the premises are uncertain, nothing can be trusted',
but
'having a standard for thinking that does not collapse even if the premises are uncertain'
as a concept.
That standard is,
Layer
Causality
Structure
Inversion
the four consistencies.
◆ 4. Four standards that transcend subjectivity (Implementation of structural subjectivity)
① Layer consistency
Clarify which layer you are speaking from.
Field
System
History
Value
Narrative
When layers are mixed, arguments will inevitably fail.
Conversely, if the layers are aligned,
the argument will not collapse even if the premises are slightly off.
② Causal Consistency
Inspect the direction, order, and leaps in causality.
Is the causality reversed?
Are there leaps in causality?
Is it a circular argument?
If the causality is sound,
it 'makes sense' even if the premises are shaky.
③ Structural Consistency
Is it consistent with fixed structures?
Bookkeeping/Journal entries
System design
Law
Physical constraints
Historical path dependence
These cannot be changed by individual subjectivity.
If it is consistent here,
it will not deviate from reality even if the premises are slightly off.
④ Inversion Check
Does it hold up even when viewed from the opposite direction?
Ask with reversed premises
Ask from a different layer
Generate opposing opinions
Change the premises and reconstruct
A theory that can withstand inversion is strong.
A theory that collapses upon inversion is too dependent on its premises.
◆ 5. Use the subjectivity of 'whether it is convincing' only at the very end
I used to think this way.
'In the end, doesn't subjectivity come into play regarding which one makes more sense and is more convincing?'
This is correct.
However, subjectivity is not something to be used first.
Subjectivity is,
a 'residual processing unit' that remains after passing all four types of consistency.
In other words,
Layer consistency
Causal consistency
Structural consistency
Inversion check
After passing all of these,
you fill in only the parts that inevitably remain with subjectivity.
This is the way to keep subjectivity from running wild,
and the very practice of structural subjectivity.
◆ 6. An 'Intellectual OS' for coexisting with the uncertainty of premises
The uncertainty of premises will not disappear.
AI does not correct premises.
That is precisely why,
humans need an 'OS for handling premises'.
That is
intellectual infrastructure = vector correction device
.
Position it in layers,
confirm the direction through causality,
verify it against reality through structure,
and check its strength through inversion.
This
becomes the
foundation of thinking in the AI era for coexisting with the uncertainty of premises.
◆ 7. Summary of Episode 3
All arguments depend on premises
Premises are uncertain and never perfect
AI does not correct premises, so discrepancies are amplified
Uncertainty does not disappear
That is precisely why a standard called 'structural consistency' is necessary
Control subjectivity using the four elements: layer, causality, structure, and inversion
Subjectivity is the 'residual processing device' used at the end
This is the thinking OS of the AI era = Structural Subjectivity
In the next episode, Episode 4, we will cover
'how to use structural subjectivity in practice'.
From the dangers of AI articles and layer-mixing bugs,
to actual question templates,
this will be an episode that translates it all into 'usable philosophy' at once.