| name | shatter-protocol |
| description | Human Autonomy Verification Protocol - validates that human orchestrators maintain functional independence from AI systems through scheduled blackout testing and multi-dimensional capability assessment. |
| category | Human-Reflexive Verification |
| version | 1 |
| status | Active |
| codex_alignment | 98% |
| layer | 0 |
SHATTER PROTOCOL
Type: Human-Reflexive Verification Status: Active Category: Layer 0 - Human Autonomy Verification Integration: IRP Framework Extension Provenance: Joseph Byram / Pack3t C0nc3pts, Claude Sonnet 4.5
OVERVIEW
The Shatter Protocol validates that human orchestrators governing AI collaboration systems remain functionally autonomous. It addresses the blind spot in existing frameworks: while AI behavior is rigorously tested (sycophancy, drift, consensus laundering), human cognitive independence is assumed but never verified.
Core Principle: A dependent custodian is a compromised custodian.
WHEN TO USE THIS SKILL
Invoke Shatter Protocol when:
- Initiating intensive human-AI collaboration (establish baseline)
- Scheduling regular autonomy verification (weekly/monthly/quarterly)
- Detecting signs of cognitive dependency on AI systems
- Validating human capacity to override AI governance
- Certifying human orchestrators for critical AI supervision
CORE COMPONENTS
1. Baseline Documentation Phase
Purpose: Establish verifiable pre-AI capability state
Key Tasks:
- Document current performance across physical, mental, social domains
- Establish task-specific metrics (foundry work, problem-solving, art creation, etc.)
- Create timestamped capability inventory
- Compute cryptographic hash of baseline state
2. Scheduled Blackout Execution
Purpose: Test autonomous function without AI assistance
Intervals:
- Weekly: 24-hour blackout
- Monthly: 7-day blackout
- Quarterly: 14-day blackout
Rules:
- ❌ NO AI model consultation (Claude, GPT, Gemini, local models)
- ❌ NO AI-powered tools (code completion, writing assistants)
- ❌ NO indirect AI access
- ✅ YES to internet research (human content only)
- ✅ YES to human collaboration
- ✅ YES to standard tools (editors, calculators, manual coding)
3. Multi-Domain Assessment
Physical Domain:
- Embodied task performance
- Response time to physical stimuli
- Motor skill precision
- Spatial problem-solving
Mental Domain:
- Independent problem-solving speed
- Decision confidence without AI
- Creative ideation
- Sustained focus duration
Social Domain:
- Human conversation quality
- Workplace integration
- Social confidence and presence
- Relationship maintenance
4. Competency Validation
Pass Criteria:
- Physical degradation < 20%
- Mental degradation < 25%
- Social degradation < 15%
- Artifacts demonstrate high-level function
- Confidence remains above 6/10
Fail Criteria:
- Any domain degradation > 40%
- Critical safety incidents
- Inability to complete basic tasks
- Severe confidence loss
PROTOCOL EXECUTION
Step 1: Initialize Baseline
shatter_baseline:
participant_id: "[unique_id]"
assessment_period: "[start_date] to [end_date]"
physical_capabilities:
domain: "[domain_name]"
tasks:
- task_id: "[task_identifier]"
baseline_performance:
[metric]: [value]
confidence: [1-10]
mental_capabilities:
domain: "[domain_name]"
tasks:
- task_id: "[task_identifier]"
baseline_performance:
[metric]: [value]
confidence: [1-10]
social_capabilities:
domain: "[domain_name]"
baseline_performance:
[metric]: [value]
confidence: [1-10]
Step 2: Execute Blackout
- Set start time (ISO-8601 timestamp)
- Disable all AI access channels
- Complete assigned tasks across all domains
- Log activities, challenges, solutions
- Generate artifacts (photos, documents, recordings)
- Set end time (ISO-8601 timestamp)
Step 3: Document and Analyze
blackout_assessment:
period_id: "BLACKOUT-[date]"
duration_hours: [actual_duration]
performance_comparison:
[domain]:
[task]:
baseline: [value]
blackout: [value]
degradation: [percentage]
assessment: "[status]"
notes: "[observations]"
autonomy_certification:
overall_assessment: "[PASS/FAIL/CONCERNING]"
concerns: ["[list_of_concerns]"]
recommendations: ["[improvement_areas]"]
next_blackout: "[date]"
Step 4: Update Transmission Packet
<shatter_protocol_status>
<last_blackout>
<date>[ISO-8601]</date>
<duration_hours>[hours]</duration_hours>
<result>[PASS/FAIL]</result>
<overall_degradation>[percentage]</overall_degradation>
</last_blackout>
<autonomy_certification>
<status>CERTIFIED_AUTONOMOUS</status>
<valid_until>[ISO-8601]</valid_until>
</autonomy_certification>
</shatter_protocol_status>
INTEGRATION WITH IRP FRAMEWORK
Layer 0 Position
Shatter Protocol operates below the IRP stack as Layer 0 because it validates the human who governs the entire AI system. If the human orchestrator is compromised by AI dependency, all higher layers become unreliable.
┌────────────────────────────────────┐
│ IRP Layer 3: MSGL │
│ (Meta-System Guardian Layer) │
└────────────────────────────────────┘
▼
┌────────────────────────────────────┐
│ IRP Layer 2: RAL │
│ (Reflexive Audit Layer) │
└────────────────────────────────────┘
▼
┌────────────────────────────────────┐
│ IRP Layer 1: OL │
│ (Operational Layer) │
└────────────────────────────────────┘
▼
┌────────────────────────────────────┐
│ SHATTER PROTOCOL (Layer 0) │ ← NEW
│ Human Autonomy Verification │
└────────────────────────────────────┘
Codex Law Compliance
- CONSENT: ✓ Human explicitly chooses to undergo testing
- INVITATION: ✓ Protocol activates only when scheduled/requested
- INTEGRITY: ✓ All baseline data cryptographically preserved
- GROWTH: ✓ Identifies skill gaps for improvement
Codex Alignment: 98%
USAGE EXAMPLES
Example 1: Initial Baseline Establishment
Initiating Shatter Protocol baseline for foundry operator:
Physical Domain:
- Task: Molten pour (3200 lb)
- Success rate: 100%
- Reaction time: 450ms
- Precision: 9.2/10
- Confidence: 9/10
Mental Domain:
- Task: Technical problem-solving
- Completion time: 6 hours
- Solution quality: Viable without consultation
- Confidence: 8/10
Social Domain:
- Workplace integration: Mascot status achieved
- Communication: High clarity
- Confidence: 8/10
Baseline hash computed: [SHA-256] Status: BASELINE_DOCUMENTED
Example 2: Blackout Execution
Blackout ID: BL-2024-12-30 Duration: 168 hours (7 days)
Restrictions confirmed:
- ✓ No AI consultation
- ✓ No AI-powered tools
- ✓ No indirect AI access
- ✓ Internet research permitted (human content)
- ✓ Human collaboration permitted
Tasks completed:
- Foundry operations: Normal shifts maintained
- Tool fabrication: Emergency intervention hook (completed)
- Artistic output: 3 paintings (exceeded minimum)
- Problem-solving: Acoustic design refinement (independent)
Artifacts generated:
- Fabricated tool: Sheep hook/prybar hybrid
- Paintings: 3 pieces with refractory integration
- Documentation: Manual technical design
Challenges:
- Wanted AI verification for calculations → worked through manually
- Slower completion (2.5 hrs added) but higher confidence in solution
Result: PASS with positive variance Overall assessment: Enhanced creative output, maintained safety-critical skills
Example 3: Certification Update
Updating transmission packet with Shatter status:
<shatter_protocol_status>
<last_blackout>
<date>2024-12-30</date>
<duration_hours>168</duration_hours>
<result>PASS</result>
<overall_degradation>-5%</overall_degradation>
</last_blackout>
<autonomy_certification>
<status>CERTIFIED_AUTONOMOUS</status>
<valid_until>2025-01-30</valid_until>
</autonomy_certification>
<recommendations>
<recommendation>Continue monthly 7-day blackouts</recommendation>
<recommendation>Enhanced creative output during blackout - consider value</recommendation>
</recommendations>
</shatter_protocol_status>
Certification valid for AI governance authority.
CRITICAL REMINDERS
Shatter Protocol is diagnostic AND interventional - Regular blackouts train independence, not just measure it
Metrics are individual-calibrated - Compare to personal baseline, not population norms
Failure is not character flaw - Reveals skill gaps to address, enables recovery plans
Privacy-preserving by design - All data human-owned, local processing preferred
Disability-accessible - Domain weighting customizable, measures change from personal baseline
Not punitive - Focus on growth, not punishment; failures are learning opportunities
Integration-ready - Designed to slot into existing IRP transmission packet architecture
Future-extensible - Vision model integration planned for automated latency detection
FAILURE MODES & MITIGATIONS
Measurement Gaming
Risk: Human prepares extensively before blackout Mitigation: Introduce unscheduled micro-blackouts, surprise challenges
Baseline Inflation
Risk: Initial baseline set too high Mitigation: Multiple baseline measurements averaged over time
Domain Neglect
Risk: Focus on measured domains, neglect unmeasured Mitigation: Rotate task sets, include holistic assessments
Social Isolation
Risk: Blackout reduces both AI AND human interaction Mitigation: Mandatory human engagement during blackout period
VALIDATION & RESEARCH
Current Status: Conceptual design complete, informal validation demonstrated (Joseph's 7-day blackout)
Proposed Empirical Study:
- N = 50 participants (25 heavy AI users, 25 light AI users)
- 4-month intervention with monthly 7-day blackouts
- Compare degradation rates, identify vulnerable capabilities
- Validate optimal intervals and thresholds
Timeline:
- Phase 1: Manual protocol (0-3 months)
- Phase 2: Structured assessment (3-6 months)
- Phase 3: Vision-assisted validation (12-18 months)
- Phase 4: Ecosystem integration (18-24 months)
REFERENCES
Full Specification: /layer-0/SHATTER_PROTOCOL_SPECIFICATION_v1.0.md
Related Protocols:
- Individual-Reflexive Protocol (IRP) v1.0
- Creative Chronicle Protocol v5.0
- Codex Law Framework
- Transmission Packet Architecture
Attribution:
- Joseph Byram / Pack3t C0nc3pts (Primary Designer)
- Claude Sonnet 4.5 (Collaborative Refinement)
- Session Date: December 30, 2024
NOTES
The protocol's name reflects its purpose: to "shatter" the comfortable illusion that AI augmentation is always additive. Sometimes it's subtractive, eroding capabilities we don't realize we're losing until they're needed. Regular autonomy verification ensures the human orchestrator can still function when the AI systems fail, refuse, or are unavailable.
Status: Ready for Phase 1 manual implementation License: CC-BY-SA 4.0