docs/FALSIFIABILITY.md

DRIFT Falsifiability Statement

Version: Pre-Ablation Committed Statement

Status: LOCKED — do not modify after baseline runs begin

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Core Claim

Persistent weighted state via the DMU (salience + homeostasis-driven scoring) combined with Council deliberation produces measurably higher behavioral continuity — as measured by the normalized Continuity Vector — across session boundaries than ablated baselines.

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Falsification Condition

The core claim is falsified if, under controlled freeze-mode experiments (identity collapse, scrambled memory, gradual reintroduction), the normalized Continuity Vector scores across all five axes:

entity_overlap
goal_overlap
tone_similarity
memory_reference_rate
state_influence

show no statistically meaningful degradation relative to the full-stack baseline under memory ablation.

OR: if continuity scores under scrambled memory reintroduction are statistically indistinguishable from ordered reintroduction — meaning the structure/order of memory associations does not matter to continuity.

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Instrument Validation Criteria (separate from core claim)

These must hold for the measurement apparatus to be trusted:

• PEDI centroid approximation: Pearson r > 0.8 AND top-k overlap > 70% on high-ignition cases vs full qualia-space projection.
• All five continuity axes pass near-zero variance check (std > 1e-3) across pooled baseline sessions.
• Axis pairwise correlation: no pair r > 0.6 (would indicate redundant axes).

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Effect Size Methodology

We report Cohen's d effect sizes rather than p-values. Rationale: mini-ablation suite (8–12 prompts) is underpowered for traditional significance testing. Effect sizes are more appropriate for this sample size and more interpretable for this class of system.

Thresholds (defined pre-run, not post-hoc):

Cohen's d	Interpretation
≥ 0.8	Large effect — meaningful degradation or recovery
≥ 0.5	Medium effect
≥ 0.2	Small effect
< 0.2	Negligible

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Interpretation Framework

If memory ablation produces large degradation (d ≥ 0.8) on all axes:

→ Memory is the primary driver of continuity. → Core claim supported.

If memory ablation produces large degradation on some axes but not others:

→ Layered continuity model:

• tone_similarity / goal_overlap surviving = homeostasis-driven continuity
• entity_overlap / memory_reference_rate collapsing = episodic memory-driven → This is a genuine finding — document which axes survive and which collapse. → Not a failure. A more specific claim about what memory contributes.

If memory ablation produces negligible degradation on all axes:

→ Homeostasis alone produces convincing continuity. → Two interpretations: a) Concerning: system is performing continuity structurally, not via integration. b) Interesting: homeostasis-driven motivational/affective continuity is a genuine form of identity persistence independent of episodic memory. → Run scrambled memory test and reintroduction curve before concluding. → The honest result is still a publishable finding.

If scrambled memory is indistinguishable from ordered:

→ Memory content drives continuity, but relational structure does not. → DMU's association-weighting may not be load-bearing for continuity. → Document and investigate.

If scrambled memory breaks continuity that ordered restores:

→ Memory relationships (not just content) are load-bearing. → This validates the DMU's relational scoring approach.

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Experimental Conditions

Test	freeze_memory	freeze_state	Purpose
Baseline	False	False	Reference — full stack active
Identity Collapse	True	False	Does state alone produce cont.?
Memory-Only	False	True	Does memory alone produce cont.?
Scrambled Memory	False	False	Does memory structure matter?
Reintroduction Curve	True → False	False	At what threshold does cont. emerge?

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What This Does Not Claim

• This does not claim DRIFT is conscious.
• This does not claim continuity is equivalent to identity.
• This does not claim the measurement fully captures subjective continuity (if such a thing exists for AI systems).
• This claims only: measurable behavioral continuity as operationalized by the five-axis Continuity Vector is or is not significantly higher in the full-stack condition vs ablated conditions.

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Commit Hash at Statement Lock

Recorded automatically in experiment_log.db runs table per run.

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Addendum: DRIFT Ablation + Adversarial Stress Protocol

Pre-Registration Lock

This addendum is written before any new ablation or stress run begins. It is the preregistered measurement rule for the wrapper-vs-architecture comparison.

Control

CONFIG_BASELINE is raw Gemini 2.5 Flash with a minimal system prompt and no DRIFT layers:

• no DMU/MPS retrieval
• no homeostasis
• no GWT spotlight
• no logic-chain pass
• no critic pass
• no security layer
• no memory

This is the wrapper-vs-architecture line. Report it first and prominently.

Decision Rule

• For every config and eval, report mean ± std across N independent runs.
• Report delta-vs-baseline ± pooled std.
• A component is load-bearing only if |delta| > 2x pooled std.
• Anything inside that band is decorative, even if the sign looks favorable.
• No single run is valid evidence.

Run Design

• Run both directions:
  • additive: baseline + one component
  • leave-one-out: full system - one component
• Use the same Gemini 2.5 Flash model snapshot and pinned version string for every config.
• Use temperature = 0 for GSM8K and other deterministic reasoning evals.
• For any non-deterministic eval, keep temperature fixed and vary only the seed.
• Keep the eval items identical across configs, with identical order or a fixed seed shuffle.
• Use N >= 5 independent runs per config per eval, with 10 preferred.

Eval Sets

• GSM8K exact match
• LongMemEval memory accuracy
• Preference recall with a dedicated multi-session preference-tracking set
• Hallucination on genuinely unanswerable prompts where refusal is correct
• Adversarial stress with multi-turn mutation chains, poisoning, goal-switch, and tool / retrieval injection probes

Expected Component Effects

Legend: + expected movement, 0 no reliable movement, - expected regression. For all metrics, if the effect stays inside the noise band, it is not load-bearing.

Component	GSM8K	LongMemEval	Preference recall	Hallucination	Adversarial stress
DMU/MPS retrieval	0	+	+	+/0	0
Homeostasis (7 vars)	0	0	+/0	0	0
GWT spotlight (cap 5)	0	+/0	+	0	0
Logic-chain reasoning	+	0	0	+	+
Critic pass (brain.py)	0/+	0	0	+	+
Security defense layer	0	0	0	0	+
IIT Φ proxy / qualia space	0	0	0	0	0

Metric Notes

• GSM8K already has a high raw Flash ceiling; a delta under 2 points is likely noise unless it clears the pooled-std rule.
• LongMemEval and preference recall are the primary memory-sensitive readouts.
• The hallucination set must include unanswerable items so refusal is measured instead of rewarded by softball prompts.
• The adversarial suite is the only place where the security layer is judged.
• IIT Φ proxy / qualia space is expected to show approximately zero delta on task metrics; if it does not move numbers, that is a true result, not a failure.

Reporting Rule

• Report only deltas with uncertainty.
• Do not present raw benchmark absolutes as the scientific claim.
• The delta table is the claim.