Automation

Version 1.4 by Robert Schaub on 2025/12/11 21:34

Automation

Automation in FactHarbor amplifies human capability but never replaces human oversight.
All automated outputs require human review before publication.

This chapter defines:

  • What must remain human-only
  • What AI (AKEL) can draft
  • What can be fully automated
  • How automation evolves through POC → Beta 0 → Release 1.0

Manual vs Automated Responsibilities

Human-Only Tasks

These require human judgment, ethics, or contextual interpretation:

  • Definition of key terms in claims
  • Approval or rejection of scenarios
  • Interpretation of evidence in context
  • Final verdict approval
  • Governance decisions and dispute resolution
  • High-risk domain oversight
  • Ethical boundary decisions (especially medical, political, psychological)

Semi-Automated (AI Draft → Human Review)

AKEL can draft these, but humans must refine/approve:

  • Scenario structures (definitions, assumptions, context)
  • Evaluation methods
  • Evidence relevance suggestions
  • Reliability hints
  • Verdict reasoning chains
  • Uncertainty and limitations
  • Scenario comparison explanations
  • Suggestions for merging or splitting scenarios
  • Draft public summaries

Fully Automated Structural Tasks

These require no human interpretation:

  • Claim normalization
  • Duplicate & cluster detection (vector embeddings)
  • Evidence metadata extraction
  • Basic reliability heuristics
  • Contradiction detection
  • Re-evaluation triggers
  • Batch layout generation (diagrams, summaries)
  • Federation integrity checks

Automation Roadmap

Automation increases with maturity.

POC (Low Automation)

Automated

  • Claim normalization
  • Light scenario templates
  • Evidence metadata extraction
  • Simple verdict drafts (internal only)

Human

  • All scenario definitions
  • Evidence interpretation
  • Verdict creation
  • Governance

Beta 0 (Medium Automation)

Automated

  • Detailed scenario drafts
  • Evidence reliability scoring
  • Cross-scenario comparisons
  • Contradiction detection (local + remote nodes)
  • Internal Truth Landscape drafts

Human

  • Scenario approval
  • Final verdict validation

Release 1.0 (High Automation)

Automated

  • Full scenario generation (definitions, assumptions, boundaries)
  • Evidence relevance scoring and ranking
  • Bayesian verdict scoring across scenario sets
  • Multi-scenario summary generation
  • Anomaly detection across nodes
  • AKEL-assisted federated synchronization

Human

  • Final approval of all scenarios and verdicts
  • Ethical decisions
  • Oversight and conflict resolution

Automation Levels

Level 0 — Human-Centric (POC)

AI is purely advisory, nothing auto-published.

Level 1 — Assisted (Beta 0)

AI drafts structures; humans approve each part.

Level 2 — Structured (Release 1.0)

AI produces near-complete drafts; humans refine.

Level 3 — Distributed Intelligence (Future)

Nodes exchange embeddings, contradiction alerts, and scenario templates.
Humans still approve everything.


Automation Matrix

Always Human

  • Final verdict approval  
  • Scenario validity  
  • Ethical decisions  
  • Dispute resolution  

Mostly AI (Human Validation Needed)

  • Claim normalization  
  • Clustering  
  • Evidence metadata  
  • Reliability heuristics  
  • Scenario drafts  
  • Contradiction detection  

Mixed

  • Definitions of ambiguous terms  
  • Boundary choices  
  • Assumption evaluation  
  • Evidence selection  
  • Verdict reasoning  

Diagram References