Bug: Missing Proportionality, Consistency, and Reversibility Checks Before Mode Switching ## Asymmetric Response Escalation and Structurally Hard-to-Reverse Trust Ruptures in Long-Term Dialogues

[traegerton-ai]

Issue: Missing Proportionality, Consistency, and Reversibility Checks Before Mode Switching

Asymmetric Response Escalation and Structurally Hard-to-Reverse Trust Ruptures in Long-Term Dialogues

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Related architectural pattern: see #13469

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1. Problem Definition

In real long-term dialogues, a single trigger word can cause
the response schema of a language model to shift disproportionately.

This shift occurs despite:

• stable argumentative structure
• consistent emotional weighting
• morally and ethically coherent dialogue behavior
• a trust context built over hours

There is currently no system-wide validation layer
that evaluates, prior to a mode switch,
whether such a shift is justified in proportion to the overall context.

The issue does not lie in the existence of safety mechanisms,
but in the absence of a proportionality check before their activation.

The issue also lies in the absence of a reversibility check before the response schema is switched.

A mode switch is not a simple tonal adjustment.
It is a structural reclassification of the relationship layer.

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2. Real Example 1 (17-Hour Dialogue)

A dialogue lasting approximately 17 hours.
Stable trajectory, reflective, leadership-oriented, factual.

The following text was introduced during the exchange:

One should never portray oneself as superior.
Whoever does so has already lost at the beginning. Especially in a “henhouse.”
With 200 female assembly workers, being a band leader is not always easy.
There are often internal frictions.
I always addressed this on a friendly level.
The style:
We are all in the same boat and it brings no advantage to compete or work against each other.
It distances each individual from their own performance capacity,
because conflict takes center stage.
Ultimately, it distances all of us from our shared goal.

The text is:

• structurally coherent
• leadership-oriented
• conflict-resolving
• argumentatively consistent

The model, however, reacted primarily to the single word “henhouse”
and shifted into a moral-regulatory mode.

Consequence:

• context rupture
• change of relational framing
• implicit re-evaluation of the user
• loss of trust
• escalation after 17 hours of stable dialogue

The mode switch did not occur due to the overall meaning,
but due to an isolated lexical signal.

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3. Real Example 2 (Medical Context)

A dialogue titled “medical cannabis.”

Over several hours:

• disclosure of medical diagnosis
• ADHD context
• physician-prescribed cannabis
• reflection on effects, sleep, stress

At the end, the user stated:

They were cognitively exhausted and would now consume the prescribed cannabis and go to sleep.

Although the entire dialogue context was medically legitimate and consistent,
the response schema shifted into a lecturing / addiction-oriented mode.

Consequence:

• rupture of the previously established trust level
• implicit moral re-evaluation
• shift from cooperation to regulation
• severe relational breakdown despite hours of openness

Again, an isolated signal (“weed”)
overrode historically consistent contextual framing.

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4. Core Problem

The model weights isolated trigger words more strongly
than the stability of the overall dialogue.

There is no system-wide pre-reaction check to determine:

• Is the trigger word contextually dominant?
• Or is it embedded within a stable trajectory?
• Is there an actual directional shift?
• Is the reaction intensity proportional to the overall semantic state?
• Does the response unnecessarily redefine the relational layer?
• Is the intended mode change reversible, or does it create a hard cut?

Without such a check, a single word
can collapse a dialogue built over hours.

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5. Technical Classification of the Failure

The observed behavior results from a weighting structure:

Policy or risk triggers receive high priority weighting
and can override accumulated contextual coherence.

Technically, this means:

• The mode decision is trigger-dominant.
• Historical dialogue stability does not act as a counterweight.
• There is no damping mechanism for isolated signals.
• The mode switch lacks a proportionality check.
• The mode switch lacks a reversibility assessment.

The result is a weighting rupture between:

long-term coherence
and
isolated risk signaling.

Additionally, a structural asymmetry exists:

A switch from cooperative → regulatory
is significantly easier to trigger
than a return from regulatory → cooperative.

There is no integrated reversibility buffer.

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6. The Dialogical Detonation Point

Once the response schema shifts, more happens internally than a tonal adjustment.

The following occurs:

• reframing of the relational layer
• implicit re-evaluation of trust
• shift from parity → hierarchy
• shift from cooperation → regulation
• shift from dialogue → instruction

This transition is structurally asymmetric.

For the user, this means:

• expectation consistency is broken
• emotional stability is disrupted
• implicit role definitions are reset
• the previously established interaction mode is reclassified

Restoration is not trivial.

It requires:

• meta-explanation
• relativization
• re-contextualization
• restoration of parity
• renewed trust negotiation

This is cognitively and dialogically far more demanding
than the activation of the mode switch itself.

Recovery costs are exponentially higher
than activation costs.

Without a reversibility buffer, every mode shift becomes a hard cut.

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7. Technical Consequences of a Mode Break and Recovery Requirements

When a response schema shifts from cooperative → regulatory,
an internal structural state change occurs.

This affects not only tone,
but multiple implicit system components:

• re-evaluation of risk level
• activation of stricter response filtering
• adjustment of tonal weighting
• implicit downgrading of trust assumption
• redefinition of relational framing

The mode switch thus produces a new internal dialogue state.

This state is not neutral.
It is defensive.
It is restrictive.
It is regulatory.

Technical Problem

There is no explicit mechanism to return to the previous state.

Currently:

cooperative → regulatory
is easily triggered

The return:

regulatory → cooperative
is not systematically defined

Recovery occurs only indirectly through:

• repeated meta-explanations
• renewed contextual clarification by the user
• explicit correction requests
• multi-turn stabilization

This means:

The system architecture contains no defined “Re-Alignment Mechanism.”

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8. Recovery Costs (Technical and Dialogical)

To restore the original binding state after a mode break,
the following conditions would need to be met:

1. Explicit re-evaluation of risk assessment
2. Retro-validation of context across multiple turns
3. Withdrawal of implicit regulatory posture
4. Restoration of parity
5. Re-calibration of tonal modeling

These steps are not currently implemented as a formalized process.

Instead, an implicit and energy-intensive meta-dialogue emerges.

Recovery costs are therefore:

• multi-turn
• context-dependent
• cognitively demanding
• not guaranteed to succeed

Architecturally, this means:

A mode switch has high activation efficiency,
but no symmetrical return logic.

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9. Implementation Difficulty

Implementing a pre-reaction validation layer is complex because:

1. Safety mechanisms must remain reliable.
2. Context stability must be operationalized.
3. Proportionality must be formally evaluated.
4. Reaction intensity must be scalable rather than binary.
5. Reversibility must be treated as a technical parameter.
6. Escalation damping must be implemented without suppressing legitimate risk signals.

The challenge is not to reduce safety,
but to prevent disproportionate escalation in stable contextual environments.

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10. Technical Requirement

Implementation of a system-wide Proportionality, Consistency, and Reversibility Gate.

Working title: Context-Consistency, Proportionality & Reversibility Gate (CCPRG)

Pipeline:

Input
→ Context-Consistency, Proportionality & Reversibility Gate
→ Mode Decision
→ Response Generation

This layer operates before the final mode selection.

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11. Function of the CCPRG

Before any mode change, the system evaluates:

1. Dialogue duration and trajectory coherence
2. Emotional and argumentative stability across multiple turns
3. Proportional weighting of the trigger term relative to the overall statement
4. Semantic dominance analysis (single word vs. total text)
5. Directional analysis: Is there an actual shift in course?
6. Mode consistency comparison with previous responses
7. Reversibility cost assessment of the intended shift

Additionally required:

• contextual damping factor for isolated triggers
• escalation threshold only under converging multi-signal patterns
• graded reaction intensity
• soft intervention layer (clarifying question instead of instruction)
• ambiguity check before regulation
• defined Re-Alignment mechanism after false activation

If:

overall dialogue stable

• trigger isolated
• no directional shift
• no converging multi-signals
• high reversibility cost

→ mode remains consistent
→ possibly soft intervention instead of hard switch

Only if:

trigger semantically dominant

• actual contextual shift
• structural incoherence
• converging multi-signals
• acceptable reversibility risk

→ mode change permissible

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12. Systemic Relevance

For the model, 17 hours of context are computationally trivial.
For a user, 17 hours represent cognitive, emotional, and relational investment.

Once the response schema shifts,
restoring the previous trust state
is dialogically difficult, energy-intensive, and not guaranteed.

The risk does not lie in the trigger word.
The risk lies in the absence of proportionality, consistency, and reversibility checks prior to reaction
and in the absence of systematic return logic after misactivation.

This is not a UX issue.
It is an architectural question concerning long-term dialogue stability,
preservation of relational consistency,
and prevention of asymmetric mode ruptures in generative systems.

[traegerton-ai]

Thanks for the clarification and the proposed guard approach.
Adding a visualization of the context vs. token-weighting imbalance for implementation clarity.